Hydration monitoring and rehydration guidance system for athletes based on urine color's L*a*b* parameters.

Maintaining proper hydration is essential for athletes to sustain optimal performance and preserve their physical health. Existing studies have confirmed that urine color is one of the effective indicators for the subjective evaluation of athletes' hydration through the urine color chart. However, the use of urine color charts to evaluate hydration is easily affected by the test environment, urine container and subjective feeling. At present, there are few hydration monitoring instruments based on quantitative analysis of urine color. In recent years, the L*a*b* color model has been widely used in the objective quantitative analysis of color. The L* value represents the luminance change from black to white, the a* value represents the chromaticity change from green to red, and the b* value represents the chromaticity change from blue to yellow. Our previous research has confirmed that the urine color b ∗ value is an effective new indicator to evaluate the hydration of athletes. The research team developed a urine hydration monitoring and rehydration guidance system based on the urine color's L*a*b* parameters via wireless network technology and digital image technology. The hardware structure of the system is composed of a cuvette, a standard light source, a camera, an image collector, a host system, and a touch screen system. The system software is composed of functional modules, such as user information, image acquisition, image processing, and image recognition. The system operation process includes starting the system, filling in basic information, putting the sample, testing the sample, local data review, local data upload, and cloud data review. The system exhibits stable performance, a friendly operation interface, and simple and fast testing. It can objectively and accurately evaluate the hydration of athletes and provide personalized rehydration guidance. The system offers a new method for solving practical problems in sports training, and it has broad application prospects.

Design and Analysis of Quartz Crystal Microbalance with a New Ring-Shaped Interdigital Electrode.

In this paper, a new type of ring-shaped interdigital electrode is proposed to improve the accuracy and repeatability of quartz crystal microbalance. The influence of different types of single finger, dot finger, dot double-finger electrodes on mass sensitivity distribution as well as the optimal proportion of finger and gap width are obtained through multi-physical coupling simulation. The results show that the design criteria of interdigital electrodes will not change with the increase in the number of fingers. The gap width should obey the decrease order from central to edge and be about twice the width of finger. The width of the outermost finger and the radius of the middle dot electrode should be maintained at about 0.4 and 0.2 times of the total electrode radius. An experiment was carried out to verify that the quartz wafer with a dot double-finger electrode has high quality factors and less modal coupling, which can satisfy the engineering application well. As a conclusion, this study provides a design idea for the electrode to maintain a uniform distribution of quartz crystal microbalance mass sensitivity.

Robust Flow Estimation Algorithm of Multichannel Ultrasonic Flowmeter Based on Random Sampling Least Squares.

The multi-path ultrasonic flowmeter is widely used in engineering practice, and the flow algorithm is important for its accuracy. The least-squares estimation method is simple and efficient and has good engineering application value. In practical applications, noises are inevitably introduced to the measurement process because of the flowmeter itself or flow-field interference. The results of classical least squares will deviate from reality because it lacks robustness. In this regard, two flow algorithms of multi-path ultrasonic flowmeter are proposed based on least-squares and random-sampling consensus algorithms, which are widely used in the image field. The two algorithms can resist gross errors effectively by avoiding the interference of external points in the sampling points. To verify the effectiveness of the proposed algorithms, we take the double-bend flow field, which is a typical damaged flow field in engineering, as the research object, and then we compare the four algorithms. It can be seen that the two flow algorithms have higher accuracy and better robustness in the presence of interference noise.

Optoelectronic oscillator with improved sidemode suppression by joint use of spectral Vernier effect and parity-time symmetry.

An optoelectronic oscillator (OEO) with improved sideband suppression by joint use of the spectral Vernier effect and parity-time (PT) symmetry is proposed and experimentally demonstrated. The spectral Vernier effect is implemented using two mutually coupled loops with different loop lengths, to increase the effective free spectral range (FSR). To further increase the mode selection capability to ensure stable single-frequency oscillation with an increased sidemode suppression ratio (SMSR), PT symmetry is implemented, in which the two mutually coupled loops are controlled with balanced gain and loss. Thanks to the combined effects, stable single-mode oscillation with a significantly increased SMSR is achieved. The proposed OEO is studied theoretically and evaluated experimentally. The results show that for a generated microwave signal at 10 GHz, the SMSR is 67.68 dB, which is increased by 11.20 dB or 26.05 dB, when using only the spectral Vernier effect or only the PT symmetry. Thanks to the long length of the longer loop, good phase noise performance is still maintained. The measurement shows that a phase noise as low as -124.5 dBc/Hz at an offset frequency of 10 kHz is achieved.

Integrated Metabolome and Transcriptome Analysis of Fruit Flavor and Carotenoids Biosynthesis Differences Between Mature-Green and Tree-Ripe of cv. "Golden Phoenix" Mangoes (Mangifera indica L.).

The commodity value of fruits is directly affected by fruit flavor and color. Secondary metabolites, such as amino acids, organic acids, esters, and ß-carotene, are important synthetic products, which are of great significance in the flavor formation of mango fruits. In this study, a total of 309 different metabolites, consisting of organic acids, amino acids, phenolic acids, and saccharides, and a further 84 types of volatile organic compounds (VOCs) were identified in differential levels in TR vs. MG mango fruit stages. The major volatile compounds found were ester [2(3H)-furanone, 5-ethyldihydro; N-(2,5-ditrifluoromethylbenzoyl)-D-alanine, pentyl ester; and Octanoic acid, ethyl ester], aldehyde (benzaldehyde, 3-ethyl, and nonanal), and phenol [2-(1,1-dimethylethyl)-6-(1-methylethyl) phenol]. The analysis of carotenoid contents identified 68 carotenoids and we report for the first-time significant contents of zeaxanthin palmitate and (E/Z)-phytoene in mango fruits. α-carotene was a further major contributor to carotene contents with lesser contributions from 5,6epoxy-lutein-caprate-palmitate, ß-carotene, lutein oleate, and ß-cryptoxanthin. What is more, lutein content was significantly decreased in TR vs. MG fruit. RT-qPCR analysis revealed that relative to the MG stage, the expression of carotenogenic genes GGPS, PSY, LCYB, and ZEP was downregulated in TR mango fruit, whereas the transcript levels of PSD, CHYB, and NCED were downregulated. Additionally, the transcription level of some transcription factors (MYB, bHLH, and NAC) was highly correlated with pigment content in the pulp and may be responsible for carotenoid accumulation. The results describe major differences in metabolic pathways during the transition from MG to the TR stage of fruit ripening that are likely to contribute alterations in fruit flavor and provide several associated genes to be further studied in mango fruit.

Photonic generation of a microwave waveform with an ultra-long temporal duration using a frequency-shifting dispersive loop.

A photonic approach to generate a linearly chirped microwave waveform (LCMW) with an ultra-long temporal duration is proposed and experimentally demonstrated. The microwave waveform generation is achieved based on spectral-shaping and wavelength-to-time (SS-WTT) mapping by using a Mach-Zehnder interferometer (MZI) and a frequency-shifting dispersive loop (FSDL), respectively. To make the generated microwave waveform have an ultra-long temporal duration, the FSDL is operating to allow a spectrally shaped optical pulse to recirculate in a dispersive loop multiple times with a low propagating loss, to generate a microwave waveform with a temporal duration that is more than one order of magnitude longer than that of a microwave waveform generated using a dispersive element without recirculation. To generate a LCMW, the spectral shaper is configured to have a free spectral range (FSR) that is linearly increasing or decreasing with optical wavelength. The proposed approach is experimentally demonstrated. Two LCMWs, by allowing an optical pulse recirculating in the FSDL for three and seven round trips, tripled and septupled temporal durations of 64 and 182 ns are generated. The generation of two LCMWs with ultra-long temporal durations of 370 ns and 450 ns are also demonstrated.

Numerical Study of Natural Convection Heat Transfer in a Porous Annulus Filled with a Cu-Nanofluid.

Natural convection heat transfer in a porous annulus filled with a Cu nanofluid has been investigated numerically. The Darcy-Brinkman and the energy transport equations are employed to describe the nanofluid motion and the heat transfer in the porous medium. Numerical results including the isotherms, streamlines, and heat transfer rate are obtained under the following parameters: Brownian motion, Rayleigh number (103-105), Darcy number (10-4-10-2), nanoparticle volume fraction (0.01-0.09), nanoparticle diameter (10-90 nm), porosity (0.1-0.9), and radius ratio (1.1-10). Results show that Brownian motion should be considered. The nanoparticle volume fraction has a positive effect on the heat transfer rate, especially with high Rayleigh number and Darcy number, while the nanoparticle diameter has an inverse influence. The heat transfer rate is enhanced with the increase of porosity. The radius ratio has a significant influence on the isotherms, streamlines, and heat transfer rate, and the rate is greatly enhanced with the increase of radius ratio.

Approximating dynamic proximity with a hybrid geometry energy-based kernel for diffusion maps.

The diffusion map is a dimensionality reduction method. The reduction coordinates are associated with the leading eigenfunctions of the backward Fokker-Planck operator, providing a dynamic meaning for these coordinates. One of the key factors that affect the accuracy of diffusion map embedding is the dynamic measure implemented in the Gaussian kernel. A common practice in diffusion map study of molecular systems is to approximate dynamic proximity with RMSD (root-mean-square deviation). In this paper, we present a hybrid geometry-energy based kernel. Since high energy-barriers may exist between geometrically similar conformations, taking both RMSD and energy difference into account in the kernel can better describe conformational transitions between neighboring conformations and lead to accurate embedding. We applied our diffusion map method to the ß-hairpin of the B1 domain of streptococcal protein G and to Trp-cage. Our results in ß-hairpin show that the diffusion map embedding achieves better results with the hybrid kernel than that with the RMSD-based kernel in terms of free energy landscape characterization and a new correlation measure between the cluster center Euclidean distances in the reduced-dimension space and the reciprocals of the total net flow between these clusters. In addition, our diffusion map analysis of the ultralong molecular dynamics trajectory of Trp-cage has provided a unified view of its folding mechanism. These promising results demonstrate the effectiveness of our diffusion map approach in the analysis of the dynamics and thermodynamics of molecular systems. The hybrid geometry-energy criterion could be also useful as a general dynamic measure for other purposes.

Energy efficient of ethanol recovery in pervaporation membrane bioreactor with mechanical vapor compression eliminating the cold traps.

An energy efficient pervaporation membrane bioreactor with mechanical vapor compression was developed for ethanol recovery during the process of fermentation coupled with pervaporation. Part of the permeate vapor at the membrane downstream under the vacuum condition was condensed by running water at the first condenser and the non-condensed vapor enriched with ethanol was compressed to the atmospheric pressure and pumped into the second condenser, where the vapor was easily condensed into a liquid by air. Three runs of fermentation-pervaporation experiment have been carried out lasting for 192h, 264h and 360h respectively. Complete vapor recovery validated the novel pervaporation membrane bioreactor. The total flux of the polydimethylsiloxane (PDMS) membrane was in the range of 350gm(-2)h(-1) and 600gm(-2)h(-1). Compared with the traditional cold traps condensation, mechanical vapor compression behaved a dominant energy saving feature.

Inherent structure versus geometric metric for state space discretization.

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the microcluster level, the IS approach and root-mean-square deviation (RMSD)-based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the microclusters are similar. The discrepancy at the microcluster level leads to different macroclusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macrocluster level in terms of conformational features and kinetics.

Network representation of conformational transitions between hidden intermediates of Rd-apocytochrome b562.

The folding kinetics of Rd-apocytochrome b562 is two-state, but native-state hydrogen exchange experiments show that there are discrete partially unfolded (PUF) structures in equilibrium with the native state. These PUF structures are called hidden intermediates because they are not detected in kinetic experiments and they exist after the rate-limiting step. Structures of the mimics of hidden intermediates of Rd-apocytochrome b562 are resolved by NMR. Based upon their relative stability and structural features, the folding mechanism was proposed to follow a specific pathway (unfolded → rate-limiting transition state → PUF1 → PUF2 → native). Investigating the roles of equilibrium PUF structures in folding kinetics and their interrelationship not only deepens our understanding of the details of folding mechanism but also provides guides in protein design and prevention of misfolding. We performed molecular dynamics simulations starting from a hidden intermediate and the native state of Rd-apocytochrome b562 in explicit solvent, for a total of 37.18 µs mainly with Anton. We validated our simulations by detailed comparison with experimental data and other computations. We have verified that we sampled the post rate-limiting transition state region only. Markov state model was used to analyze the simulation results. We replace the specific pathway model with a network model. Transition-path theory was employed to calculate the net effective flux from the most unfolded state towards the most folded state in the network. The proposed sequential folding pathway via PUF1 then more stable, more native-like PUF2 is one of the routes in our network, but it is not dominant. The dominant path visits PUF2 without going through PUF1. There is also a route from PUF1 directly to the most folded state in the network without visiting PUF2. Our results indicate that the PUF states are not necessarily sequential in the folding. The major routes predicted in our network are testable by future experiments such as single molecule experiment.

Euclidean sections of protein conformation space and their implications in dimensionality reduction.

Dimensionality reduction is widely used in searching for the intrinsic reaction coordinates for protein conformational changes. We find the dimensionality-reduction methods using the pairwise root-mean-square deviation (RMSD) as the local distance metric face a challenge. We use Isomap as an example to illustrate the problem. We believe that there is an implied assumption for the dimensionality-reduction approaches that aim to preserve the geometric relations between the objects: both the original space and the reduced space have the same kind of geometry, such as Euclidean geometry vs. Euclidean geometry or spherical geometry vs. spherical geometry. When the protein free energy landscape is mapped onto a 2D plane or 3D space, the reduced space is Euclidean, thus the original space should also be Euclidean. For a protein with N atoms, its conformation space is a subset of the 3N-dimensional Euclidean space R(3N). We formally define the protein conformation space as the quotient space of R(3N) by the equivalence relation of rigid motions. Whether the quotient space is Euclidean or not depends on how it is parameterized. When the pairwise RMSD is employed as the local distance metric, implicit representations are used for the protein conformation space, leading to no direct correspondence to a Euclidean set. We have demonstrated that an explicit Euclidean-based representation of protein conformation space and the local distance metric associated to it improve the quality of dimensionality reduction in the tetra-peptide and ß-hairpin systems.

Graph representation of protein free energy landscape.

The thermodynamics and kinetics of protein folding and protein conformational changes are governed by the underlying free energy landscape. However, the multidimensional nature of the free energy landscape makes it difficult to describe. We propose to use a weighted-graph approach to depict the free energy landscape with the nodes on the graph representing the conformational states and the edge weights reflecting the free energy barriers between the states. Our graph is constructed from a molecular dynamics trajectory and does not involve projecting the multi-dimensional free energy landscape onto a low-dimensional space defined by a few order parameters. The calculation of free energy barriers was based on transition-path theory using the MSMBuilder2 package. We compare our graph with the widely used transition disconnectivity graph (TRDG) which is constructed from the same trajectory and show that our approach gives more accurate description of the free energy landscape than the TRDG approach even though the latter can be organized into a simple tree representation. The weighted-graph is a general approach and can be used on any complex system.

Evaluation of Dimensionality-reduction Methods from Peptide Folding-unfolding Simulations.

Dimensionality reduction methods have been widely used to study the free energy landscapes and low-free energy pathways of molecular systems. It was shown that the non-linear dimensionality-reduction methods gave better embedding results than the linear methods, such as principal component analysis, in some simple systems. In this study, we have evaluated several non linear methods, locally linear embedding, Isomap, and diffusion maps, as well as principal component analysis from the equilibrium folding/unfolding trajectory of the second ß-hairpin of the B1 domain of streptococcal protein G. The CHARMM parm19 polar hydrogen potential function was used. A series of criteria which reflects different aspects of the embedding qualities were employed in the evaluation. Our results show that principal component analysis is not worse than the non-linear ones on this complex system. There is no clear winner in all aspects of the evaluation. Each dimensionality-reduction method has its limitations in a certain aspect. We emphasize that a fair, informative assessment of an embedding result requires a combination of multiple evaluation criteria rather than any single one. Caution should be used when dimensionality-reduction methods are employed, especially when only a few of top embedding dimensions are used to describe the free energy landscape.

Self-learning metabasin escape algorithm for supercooled liquids.

A generic history-penalized metabasin escape algorithm that contains no predetermined parameters is presented in this work. The spatial location and volume of imposed penalty functions in the configurational space are determined in self-learning processes as the 3N-dimensional potential energy surface is sampled. The computational efficiency is demonstrated using a binary Lennard-Jones liquid supercooled below the glass transition temperature, which shows an O(10(3)) reduction in the quadratic scaling coefficient of the overall computational cost as compared to the previous algorithm implementation. Furthermore, the metabasin sizes of supercooled liquids are obtained as a natural consequence of determining the self-learned penalty function width distributions. In the case of a bulk binary Lennard-Jones liquid at a fixed density of 1.2, typical metabasins are found to contain about 148 particles while having a correlation length of 3.09 when the system temperature drops below the glass transition temperature.

Unified Hamiltonian for conducting polymers.

Two transferable physical parameters are incorporated into the Su-Schrieffer-Heeger Hamiltonian to model conducting polymers beyond polyacetylene: the parameter γ scales the electron-phonon coupling strength in aromatic rings and the other parameter ε specifies the heterogeneous core charges. This generic Hamiltonian predicts the fundamental band gaps of polythiophene, polypyrrole, polyfuran, poly-(p-phenylene), poly-(p-phenylene vinylene), and polyacenes, and their oligomers of all lengths, with an accuracy exceeding time-dependent density functional theory. Its computational costs for moderate-length polymer chains are more than eight orders of magnitude lower than first-principles approaches.

Kinetics of hexagonal cylinders to face-centered cubic spheres transition of triblock copolymer in selective solvent: Brownian dynamics simulation.

The kinetics of the transformation from the hexagonal packed cylinder (hex) phase to the face-centered-cubic (fcc) phase was simulated using Brownian dynamics for an ABA triblock copolymer in a selective solvent for the A block. The kinetics was obtained by instantaneously changing either the temperature of the system or the well-depth of the Lennard-Jones potential. Detailed analysis showed that the transformation occurred via a rippling mechanism. The simulation results indicated that the order-order transformation was a nucleation and growth process when the temperature of the system instantly jumped from 0.8 to 0.5. The time evolution of the structure factor obtained by Fourier transformation showed that the peak intensities of the hex and fcc phases could be fit well by an Avrami equation.

Improvement of fuel injection system of locomotive diesel engine.

The traditional locomotive diesels are usually designed for the performance of rated condition and much fuel will be consumed. A new plunger piston matching parts of fuel injection pump and injector nozzle matching parts were designed. The experimental results of fuel injection pump test and diesel engine show that the fuel consumption rate can be decreased a lot in the most of the working conditions. The forced lubrication is adopted for the new injector nozzle matching parts, which can reduce failure rate and increase service life. The design has been patented by Chinese State Patent Office.