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Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accuracies for the classical sleep stages of Wake, REM, and Non-REM. Meanwhile, it has been recognized that the statistics of transitional stages such as pre-REM, found between Non-REM and REM, may hold additional insight into the physiology of sleep and are now under vivid investigation. We propose a classification system based on a simple neural network architecture that scores the classical stages as well as pre-REM sleep in mice. When restricted to the classical stages, the optimized network showed state-of-the-art classification performance with an out-of-sample F1 score of 0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1 scores on pre-REM (0.5) compared to the classical stages. The result is comparable to previous attempts to score transitional stages in other species such as transition sleep in rats or N1 sleep in humans. Nevertheless, we observed that the sequence of predictions including pre-REM typically transitioned from Non-REM to REM reflecting sleep dynamics observed by human scorers. Our findings provide further evidence for the difficulty of scoring transitional sleep stages, likely because such stages of sleep are under-represented in typical data sets or show large inter-scorer variability. We further provide our source code and an online platform to run predictions with our trained network.
Quantitative nuclear magnetic resonance (qNMR) is considered as a powerful tool for multicomponent mixture analysis as well as for the purity determination of single compounds. Special attention is currently paid to the training of operators and study directors involved in qNMR testing. To assure that only qualified personnel are used for sample preparation at our GxP-accredited laboratory, weighing test was proposed. Sixteen participants performed six-fold weighing of the binary mixture of dibutylated hydroxytoluene (BHT) and 1,2,4,5-tetrachloro-3-nitrobenzene (TCNB). To evaluate the quality of data analysis, all spectra were evaluated manually by a qNMR expert and using in-house developed automated routine. The results revealed that mean values are comparable and both evaluation approaches are free of systematic error. However, automated evaluation resulted in an approximately 20% increase in precision. The same findings were revealed for qNMR analysis of 32 compounds used in pharmaceutical industry. Weighing test by six-fold determination in binary mixtures and automated qNMR methodology can be recommended as efficient tools for evaluating staff proficiency. The automated qNMR method significantly increases throughput and precision of qNMR for routine measurements and extends application scope of qNMR.
Extension fractures are typical for the deformation under low or no confining pressure. They can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. In this article, it is shown that the simple extension strain criterion makes unrealistic strength predictions in biaxial compression and tension. To overcome this major limitation, a new extension strain criterion is proposed by adding a weighted principal shear component to the simple criterion. The shear weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr–Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting extension failure modes, which are unexpected in the classical understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain leading to dilatancy. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak stress CP. Different from compressive loading, tensile loading requires only a limited number of critical cracks to cause failure. Therefore, for tensile stresses, the failure criteria must be modified somehow, possibly by a cut-off corresponding to the CI stress. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.
This study investigated the anaerobic digestion of an algal–bacterial biofilm grown in artificial wastewater in an Algal Turf Scrubber (ATS). The ATS system was located in a greenhouse (50°54′19ʺN, 6°24′55ʺE, Germany) and was exposed to seasonal conditions during the experiment period. The methane (CH4) potential of untreated algal–bacterial biofilm (UAB) and thermally pretreated biofilm (PAB) using different microbial inocula was determined by anaerobic batch fermentation. Methane productivity of UAB differed significantly between microbial inocula of digested wastepaper, a mixture of manure and maize silage, anaerobic sewage sludge, and percolated green waste. UAB using sewage sludge as inoculum showed the highest methane productivity. The share of methane in biogas was dependent on inoculum. Using PAB, a strong positive impact on methane productivity was identified for the digested wastepaper (116.4%) and a mixture of manure and maize silage (107.4%) inocula. By contrast, the methane yield was significantly reduced for the digested anaerobic sewage sludge (50.6%) and percolated green waste (43.5%) inocula. To further evaluate the potential of algal–bacterial biofilm for biogas production in wastewater treatment and biogas plants in a circular bioeconomy, scale-up calculations were conducted. It was found that a 0.116 km2 ATS would be required in an average municipal wastewater treatment plant which can be viewed as problematic in terms of space consumption. However, a substantial amount of energy surplus (4.7–12.5 MWh a−1) can be gained through the addition of algal–bacterial biomass to the anaerobic digester of a municipal wastewater treatment plant. Wastewater treatment and subsequent energy production through algae show dominancy over conventional technologies.
We study the possibility to fabricate an arbitrary phase mask in a one-step laser-writing process inside the volume of an optical glass substrate. We derive the phase mask from a Gerchberg–Saxton-type algorithm as an array and create each individual phase shift using a refractive index modification of variable axial length. We realize the variable axial length by superimposing refractive index modifications induced by an ultra-short pulsed laser at different focusing depth. Each single modification is created by applying 1000 pulses with 15 μJ pulse energy at 100 kHz to a fixed spot of 25 μm diameter and the focus is then shifted axially in steps of 10 μm. With several proof-of-principle examples, we show the feasibility of our method. In particular, we identify the induced refractive index change to about a value of Δn=1.5⋅10−3. We also determine our current limitations by calculating the overlap in the form of a scalar product and we discuss possible future improvements.
This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual
labour and increased productivity.
Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model’s performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance.
Halophilic and halotolerant microorganisms represent a promising source of salt-tolerant enzymes suitable for various biotechnological applications where high salt concentrations would otherwise limit enzymatic activity. Considering the current growing enzyme market and the need for more efficient and new biocatalysts, the present study aimed at the characterization of a high-alkaline subtilisin from Alkalihalobacillus okhensis Kh10-101T. The protease gene was cloned and expressed in Bacillus subtilis DB104. The recombinant protease SPAO with 269 amino acids belongs to the subfamily of high-alkaline subtilisins. The biochemical characteristics of purified SPAO were analyzed in comparison with subtilisin Carlsberg, Savinase, and BPN'. SPAO, a monomer with a molecular mass of 27.1 kDa, was active over a wide range of pH 6.0–12.0 and temperature 20–80 °C, optimally at pH 9.0–9.5 and 55 °C. The protease is highly oxidatively stable to hydrogen peroxide and retained 58% of residual activity when incubated at 10 °C with 5% (v/v) H2O2 for 1 h while stimulated at 1% (v/v) H2O2. Furthermore, SPAO was very stable and active at NaCl concentrations up to 5.0 m. This study demonstrates the potential of SPAO for biotechnological applications in the future.
Miniaturized electrolyte–insulator–semiconductor capacitors (EISCAPs) with ultrathin gate insulators have been studied in terms of their pH-sensitive sensor characteristics: three different EISCAP systems consisting of Al–p-Si–Ta2O5(5 nm), Al–p-Si–Si3N4(1 or 2 nm)–Ta2O5 (5 nm), and Al–p-Si–SiO2(3.6 nm)–Ta2O5(5 nm) layer structures are characterized in buffer solution with different pH values by means of capacitance–voltage and constant capacitance method. The SiO2 and Si3N4 gate insulators are deposited by rapid thermal oxidation and rapid thermal nitridation, respectively, whereas the Ta2O5 film is prepared by atomic layer deposition. All EISCAP systems have a clear pH response, favoring the stacked gate insulators SiO2–Ta2O5 when considering the overall sensor characteristics, while the Si3N4(1 nm)–Ta2O5 stack delivers the largest accumulation capacitance (due to the lower equivalent oxide thickness) and a higher steepness in the slope of the capacitance–voltage curve among the studied stacked gate insulator systems.