Precision fermentation is a promising route to develop recombinant proteins with improved functionality. Protein functionality is highly influenced by protein structure, which can be significantly affected by conforma...
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We present a shared industry-academic perspective on the principles and opportunities for Quality by Digital Design (QbDD) as a framework to accelerate medicines development and enable regulatory innovation for new me...
While the demand for milk proteins is on the rise, sustainability concerns dictate a reduction in animal-based agriculture. Microbial cell factories can be a viable alternative, but their inability to phosphorylate re...
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While the demand for milk proteins is on the rise, sustainability concerns dictate a reduction in animal-based agriculture. Microbial cell factories can be a viable alternative, but their inability to phosphorylate recombinant caseins is a major bottleneck, since phosphorylation is needed for calcium binding and functionality. We propose a solution that involves engineering bacteria to co-express bacterial protein kinases, resulting in recombinant caseins with the native phosphorylation pattern and functional properties. We successfully phosphorylated α s1 -casein in Escherichia coli using bacterial kinases, achieving phosphorylation at all native sites. To complement this approach, we developed an alternative phosphomimetic strategy by substituting serine residues with aspartate to mimic phosphorylation. Structural and functional characterization of all the phosphorylated/phosphomimetic recombinant α s1 -caseins demonstrated properties comparable with those of bovine α-casein, including calcium-binding affinity, digestibility, and structural integrity. Notably, phosphomimetic α s1 -casein may offer a simpler system, while phosphorylated casein more closely resembles bovine casein. This approach has significant implications for the development of alternative protein sources, addressing both sustainability and functional demands in the food industry.
In order to improvement of the efficiency of the gas turbine and heat recovery of waste heat, a novel power and fresh water production system is proposed. This system is included combined supercritical CO2 regenerativ...
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This paper proposes a method to simulate odor diffusion process under the wing-in-ground aerodynamic olfactory effect for gas-sensitive rotorcrafts and verifies its correctness by experiments. When an aircraft is flyi...
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This paper proposes a method to simulate odor diffusion process under the wing-in-ground aerodynamic olfactory effect for gas-sensitive rotorcrafts and verifies its correctness by experiments. When an aircraft is flying close to the ground,the flow characteristics will be affected by the ground, the induced drag and wake volocity will be changed, which is called the wing-in-ground effect. The diffusion of odor plume under the wing-in-ground effect is different from the normal *** this paper, the wing-in-ground effect is simulated by the opposite flow of two mirrored wakes. This method converts the influence of ground on wake vortexes into that of mirrored wake vortexes. Inspired by the PIV(particle image velocimetry)principle, a simple and easy-to-operate device that can be realized in the offices is designed and built to verify the accuracy of the simulation. The Hu invariant moments are used to compare the envelope lines of odor-plumes images in the simulation and experiment, and the results are converted into a number indicating the similarity between them. The comparison results show that the simulation model of the wing-in-ground aerodynamic olfactory effect is basically the same as the experimental one, that is to say, the proposed model is a reliable method to simulate the odor diffusion process under the wing-in-ground effect of rotorcrafts.
At the beginning of the 21st century, many consumers show interest in purchasing safe, healthy, and nutritious foods. The intent requirement of end-users and many food product manufacturers are trying to feature a new...
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Analyzing the response of the human brain to odors is critical to assess the function of olfactory and cognition. In this paper, an EEG(electroencephalograph)-based odor perception dataset is collected from ten subjec...
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Analyzing the response of the human brain to odors is critical to assess the function of olfactory and cognition. In this paper, an EEG(electroencephalograph)-based odor perception dataset is collected from ten subjects using thirteen odors stimuli. Based on the developed dataset, we employ channel-frequency convolutional neural network(CFCNN), combined with differential entropy(DE) features from different channels and frequency bands, to classify five odors that were consistently considered pleasant by the ten subjects. Meanwhile, the k-nearest neighbor(k-NN), linear discriminant analysis(LDA), support vector machine(SVM) and back propagation neural network(BPNN) are used as competing methods. The experimental results show that CFCNN is superior to the classic baselines and yields the highest accuracy in distinguishing five pleasant odors. Furthermore, compared with other four frequency bands, the gamma band presents the best classification accuracy, proving the closed relation between the olfaction and gamma band activity of the brain.
This study investigates the robust stability of uncertain interval systems subject to impulsive effects, with comprehensive consideration given to uncertainties in both the system dynamics and the impulse time sequenc...
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As a source searching method, infotaxis has been used in mobile olfactory robots equipped with contact-type MOS(metal oxide semiconductor) gas sensors. This method navigates a robot to explore more cues in the global ...
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As a source searching method, infotaxis has been used in mobile olfactory robots equipped with contact-type MOS(metal oxide semiconductor) gas sensors. This method navigates a robot to explore more cues in the global space and therefore costs much time at the early stage. To solve this problem, this paper presents a line integral infotaxis(LII) algorithm which is realized by applying a remote-type TDLAS(tunable diode laser absorption spectroscopy) gas sensor to the infotaxis. In addition, the robot often gets stuck in the place of high concentration during the infotaxis searching process, so an odor source declaration procedure which is implemented by calculating the odor particle flux on a closed curve is added to the LII. Simulation results show that the LII algorithm can enormously save time of exploration and solve the local convergence problem.
Currently, pointer-type meters in natural gas stations are read manually, which causes a waste of human *** have proposed lots of methods to realize automatic reading of such meters. However, these methods need high q...
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Currently, pointer-type meters in natural gas stations are read manually, which causes a waste of human *** have proposed lots of methods to realize automatic reading of such meters. However, these methods need high quality source image rigorously so that they cannot perform well in real environments. To solve this problem, an automatic detection and recognition method for pointer-type meters is proposed, which consists of R-FCNs(region-based fully convolutional networks),an improved local threshold segmentation method and a probability-circle method. The experimental results show that the method performs well when the source image is blurred, the illumination is complex or the camera's angle is tilted. It has good robustness and accuracy to detect and recognize the pointer-type meters automatically.
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