Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A Novel Wireless Sensor Networks Structure Based on the SDN

Since the SDN (Software Defined Network) technology based on OpenFlow was born, domestic and foreign research institutions have had increasing attention to this emerging field. The OpenFlow technology which is known for standardization and compatibility network virtualization has brought a lot of innovative solutions in the field of research. As the wireless sensor network node is complex and difficult to move and the network topology is changing rapidly with time, this requires a routing protocol for it to be able to adapt to this high topology change. Because traditional WSNS protocol communication needs to consider energy consumption, load balancing and other factors, it is difficult to find one to take into account all aspects of network algorithms. In this paper, we put forward a new solution for WSNS in accordance with the OpenFlow technology research in the application of traditional network

Towards Communication-Learning Trade-off for Federated Learning at the Network Edge

In this letter, we study a wireless federated learning (FL) system where network pruning is applied to local users with limited resources. Although pruning is beneficial to reduce FL latency, it also deteriorates learning performance due to the information loss. Thus, a trade-off problem between communication and learning is raised. To address this challenge, we quantify the effects of network pruning and packet error on the learning performance by deriving the convergence rate of FL with a non-convex loss function. Then, closed-form solutions for pruning control and bandwidth allocation are proposed to minimize the weighted sum of FL latency and FL performance. Finally, numerical results demonstrate that 1) our proposed solution can outperform benchmarks in terms of cost reduction and accuracy guarantee, and 2) a higher pruning rate would bring less communication overhead but also worsen FL accuracy, which is consistent with our theoretical analysis.Comment: This paper has been accepted by IEEE Communications Letter

Study of Motion Sickness Model Based on fNIRS Multiband Features during Car Rides

Motion sickness is a common physiological discomfort phenomenon during car rides. In this paper, the functional near-infrared spectroscopy (fNIRS) technique was used in real-world vehicle testing. The fNIRS technique was utilized to model the relationship between changes in blood oxygenation levels in the prefrontal cortex of passengers and motion sickness symptoms under different motion conditions. To enhance the accuracy of motion sickness classification, the study utilized principal component analysis (PCA) to extract the most significant features from the test data. Wavelet decomposition was used to extract the power spectrum entropy (PSE) features of five frequency bands highly related to motion sickness. The correlation between motion sickness and cerebral blood oxygen levels was modeled by a 6-point scale calibration for the subjective evaluation of the degree of passenger motion sickness. A support vector machine (SVM) was used to build a motion sickness classification model, achieving an accuracy of 87.3% with the 78 sets of data. However, individual analysis of the 13 subjects showed a varying range of accuracy from 50% to 100%, suggesting the presence of individual differences in the relationship between cerebral blood oxygen levels and motion sickness symptoms. Thus, the results demonstrated that the magnitude of motion sickness during the ride was closely related to the change in the PSE of the five frequency bands of cerebral prefrontal blood oxygen, but further studies are needed to investigate individual variability

A Study of Strength Parameter Evolution and a Statistical Damage Constitutive Model of Cemented Sand and Gravel

Cemented sand and gravel (CSG) has a wide range of applications in dam construction, and its properties are between rockfill and roller compacted concrete (RCC). A difference in gel content will result in a variance in CSG’s structure and mechanical properties. To investigate the intricate structural mechanical properties of CSG, this study conducted a series of laboratory tests and associated discrete element analyses. Accordingly, the evolution law of the strength parameters of CSG is explored and a statistical damage constitutive model suitable for CSG is established. The main contributions of this study are as follows: (1) The failure mechanism of the CSG was described from the microscopic level, and the evolution law of the strength parameter cohesion and friction angle of the CSG was analyzed and summarized. (2) Based on the particle flow model, the energy development law and the spatiotemporal distribution law of acoustic emission (AE) provide illustrations of the strain hardening–softening transition features and the interaction between cohesion and friction of CSG. (3) The evolution function between the strength parameter and the strain softening parameter was built, and the critical strain softening parameter was determined by the microcrack evolution law of the particle flow model. (4) The accuracy of the evolution curve was confirmed by comparing it to experimental results. (5) Based on the relationship between cohesion loss and material damage, a statistical damage constitutive model was developed using the improved Mohr–Coulomb strength criterion as the micro strength function. The constitutive model can accurately describe the stress–strain curves of CSG with different gel content. Furthermore, the model reflects the strain hardening–softening properties of CSG and reveals the relationship between the weakening of cohesion and material damage at the microscopic level. These findings provide valuable guidelines for investigating the damage laws and microcosmic failure features of CSG and other relevant materials

Model Predictive Control with Reach-avoid Analysis

In this paper we investigate the optimal controller synthesis problem, so that the system under the controller can reach a specified target set while satisfying given constraints. Existing model predictive control (MPC) methods learn from a set of discrete states visited by previous (sub-)optimized trajectories and thus result in computationally expensive mixed-integer nonlinear optimization. In this paper a novel MPC method is proposed based on reach-avoid analysis to solve the controller synthesis problem iteratively. The reach-avoid analysis is concerned with computing a reach-avoid set which is a set of initial states such that the system can reach the target set successfully. It not only provides terminal constraints, which ensure feasibility of MPC, but also expands discrete states in existing methods into a continuous set (i.e., reach-avoid sets) and thus leads to nonlinear optimization which is more computationally tractable online due to the absence of integer variables. Finally, we evaluate the proposed method and make comparisons with state-of-the-art ones based on several examples

Rapid, simple and quantitative detection of metolcarb residues in apples by surface-enhanced Raman scattering

A rapid and simple detection method of metolcarb residues in apples with spectral analysis technology was achieved drawing support from the high sensitive and flexible silver/dragonfly wing (Ag/DW) surface-enhanced Raman scattering (SERS) substrates. The three steps “spray”, “press” and “separate” greatly simplified the procedures of extraction and sampling of pesticide molecules, resulting in the entire detection process was completed just in a few minutes. Importantly, the Ag nanoislands offered strong electromagnetic (EM) field enhancement near metallic nanostructures and significantly improved the sensitivity and reproducibility of the Raman signals. Meanwhile, surface plasmon coupling at the nanogaps between adjacent nanoislands created abundant “hot spots”, which became enormous enhancement necessary for high sensitivity SERS detection of metolcarb. Taking the apple peels as carriers, the trace detection of metolcarb residues on them was realized, whose detection limit reached 1×10-9 g/cm2. In addition, the linear relationship (R2 = 0.98666) between the logarithmic concentrations of metolcarb residues and the logarithmic peak areas at 1581 cm-1 was established, which was the more accurate reference for the prediction of the unknown concentration of metolcarb residues. In order to carry out the actual emulation, we studied metolcarb in mixed solution, and its obvious characteristic peaks were observed. These results indicated that SERS technology coupled with “spray-press-separate-test” method had the potential to qualitatively and quantitatively analyse metolcarb residues on complex apple peels

Purification and Characterization of a Biofilm-Degradable Dextranase from a Marine Bacterium

This study evaluated the ability of a dextranase from a marine bacterium Catenovulum sp. (Cadex) to impede formation of Streptococcus mutans biofilms, a primary pathogen of dental caries, one of the most common human infectious diseases. Cadex was purified 29.6-fold and had a specific activity of 2309 U/mg protein and molecular weight of 75 kDa. Cadex showed maximum activity at pH 8.0 and 40 °C and was stable at temperatures under 30 °C and at pH ranging from 5.0 to 11.0. A metal ion and chemical dependency study showed that Mn2+ and Sr2+ exerted positive effects on Cadex, whereas Cu2+, Fe3+, Zn2+, Cd2+, Ni2+, and Co2+ functioned as inhibitors. Several teeth rinsing product reagents, including carboxybenzene, ethanol, sodium fluoride, and xylitol were found to have no effects on Cadex activity. A substrate specificity study showed that Cadex specifically cleaved the α-1,6 glycosidic bond. Thin layer chromatogram and high-performance liquid chromatography indicated that the main hydrolysis products were isomaltoogligosaccharides. Crystal violet staining and scanning electron microscopy showed that Cadex impeded the formation of S. mutans biofilm to some extent. In conclusion, Cadex from a marine bacterium was shown to be an alkaline and cold-adapted endo-type dextranase suitable for development of a novel marine agent for the treatment of dental caries

Microstructural Characterization and Formation Mechanism of Nitrided Layers on Aluminum Substrates by Thermal Plasma Nitriding

Nitrided layers on 6082 aluminum alloy substrates and 1060 aluminum substrates are formed at atmospheric pressure using thermal nitrogen plasma, which only takes seconds to form a millimeter-level layer. The nitrided layers are composed of aluminum nitride (AlN) and aluminum solid solution phases. Microstructures in these nitrided layers can be divided into three regions from bottom to top: the transition region, the dendrite region, and the lamella region. These regions are formed in sequence. The formation mechanisms and processes of the three regions are discussed in detail. Furthermore, we found that Al melt is transported upward through the voids and the capillaries in the AlN structures, and reacts with N plasma in the melt surface. The growth of the AlN structures promotes this transport. With the increase of N2 flow rates from 1 L/min to 7.5 L/min, both the hardness and the wear resistance of the nitrided layers are improved, and the nitrided layer becomes thicker