State of energy estimation of lithium-ion battery based on long short-term memory optimization Adaptive Cubature Kalman filter.

State of energy (SOE) is an important parameter to ensure the safety and reliability of lithium-ion battery (LIB) system. The safety of LIBs, the development of artificial intelligence, and the increase in computing power have provided possibilities for big data computing. This article studies SOE estimation problem of LIBs, aiming to improve the accuracy and adaptability of the estimation. Firstly, in the SOE estimation process, adaptive correction is performed by iteratively updating the observation noise equation and process noise equation of the Adaptive Cubature Kalman Filter (ACKF) to enhance the adaptive capability. Meanwhile, the adoption of high-order equivalent models further improves the accuracy and adaptive ability of SOE estimation. Secondly, Long Short-term Memory (LSTM) is introduced to optimize Ohmic internal resistance (OIR) and actual energy (AE), further improving the accuracy of SOE estimation. Once again, in the process of OIR and AE estimation, the iterative updating of the observation noise equation and process noise equation of ACKF were also adopted to perform adaptive correction and enhance the adaptive ability. Finally, this article establishes a SOE estimation method based on LSTM optimized ACKF. Validate the LSTM optimized ACKF method through simulation experiments and compare it with individual ACKF methods. The results show that the ACKF estimation method based on LSTM optimization has an SOE estimation error of less than 0.90% for LIB, regardless of the SOE at 100%, 65%, and 30%, which is more accurate than the SOE estimation error of ACKF alone. It can be seen that this study has improved the accuracy and adaptability of LIB's SOE estimation, providing more accurate data support for ensuring the safety and reliability of lithium batteries.

Antidiabetic activity of Armillaria mellea polysaccharides: Joint ultrasonic and enzyme assisted extraction.

Armillaria mellea polysaccharides (AMPs) were obtained by ultrasonic assisted extraction (U), enzyme assisted extraction (E) and ultrasonic-enzyme assisted extraction (UE), respectively. The yield of UE-AMPs (6.32 ± 0.14%) was 1.64 times higher than that of U-AMPs (3.86 ± 0.11%) and 1.21 times higher than that of E-AMPs (5.21 ± 0.09%); meanwhile, the highest total sugar content and the lowest protein content were found in UE-AMPs. AMPs obtained from the three extraction methods had the same monosaccharide composition but in different proportions, allowing UE-AMPs to have the most potent antioxidant activity. The antidiabetic activity of UE-AMPs was investigated in streptozotocin (STZ)-induced diabetic mice. UE-AMPs, when given by gavage, greatly prevented weight loss, increased water intake, and considerably decreased blood glucose levels in diabetic mice, which were dose-dependent (P < 0.05). In addition, UE-AMPs also had a positive effect on the reduction of lipid levels in the blood, oxidative damage and liver function impairment. The pathological observation by hematoxylin-eosin staining (HE) revealed that UE-AMPs protected the organs of mice from diabetic complications (liver disease and nephropathy). Hence, our findings demonstrate that UE-AMPs are a suitable choice for improving diabetes and its complications and have great application prospects in the fields of natural medicine and functional food.

A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction.

The deep learning methods for various disease prediction tasks have become very effective and even surpass human experts. However, the lack of interpretability and medical expertise limits its clinical application. This paper combines knowledge representation learning and deep learning methods, and a disease prediction model is constructed. The model initially constructs the relationship graph between the physical indicator and the test value based on the normal range of human physical examination index. And the human physical examination index for testing value by knowledge representation learning model is encoded. Then, the patient physical examination data is represented as a vector and input into a deep learning model built with self-attention mechanism and convolutional neural network to implement disease prediction. The experimental results show that the model which is used in diabetes prediction yields an accuracy of 97.18% and the recall of 87.55%, which outperforms other machine learning methods (e.g., lasso, ridge, support vector machine, random forest, and XGBoost). Compared with the best performing random forest method, the recall is increased by 5.34%, respectively. Therefore, it can be concluded that the application of medical knowledge into deep learning through knowledge representation learning can be used in diabetes prediction for the purpose of early detection and assisting diagnosis.

Covalent Interaction between High Hydrostatic Pressure-Pretreated Rice Bran Protein Hydrolysates and Ferulic Acid: Focus on Antioxidant Activities and Emulsifying Properties.

Rice bran protein hydrolysates (RBPH) pretreated with high hydrostatic pressure (HHP) covalently interacted with ferulic acid (FA) (0.5 to 2.5 mg/mL) under alkaline conditions. The structural and functional properties of the conjugates were investigated. The results revealed that the FA binding equivalent on RBPH increased from 6.03 to 207.64 nmol/mg. FTIR spectral analysis indicated that the content of α-helix increased, whereas the contents of ß-sheet, ß-turn, and random coil decreased. The surface hydrophobicity (H0) of RBPH increased, the fluorescence intensity decreased, and the tertiary structure changed because of covalent interactions between RBPH and FA. The emulsifying activity index of RBPH-FA (1.5 mg/mL) was 35.10% higher than that of the control, whereas FA concentrations higher than 1.5 mg/mL had a negative effect on emulsifying properties. RBPH-FA (2.5 mg/mL) exhibited the strongest antioxidant activity. This study provides a new reference for the application of RBPH-FA conjugates in food processing.

'Unqueer' kinship? Critical reflections on 'marriage fraud' in mainland China.

This article explores the controversial kinship practice in mainland China of 'gay' men marrying unwitting women. It questions the 'marriage fraud' discourse that condemns the men involved while pitying their wives, or tongqis. Taking an ethnographic approach, this article considers the major flaws of this popular discourse: the idealized-package of marriage-love-sex, the oft-neglected difficulties of living outside marriage, and most importantly, the essentialization of homosexuality. It also examines the im/possibility for married 'gay' men to be honest in their marriages. Finally, it cautions that honesty, if used as a decontextualized ethical yardstick for queer kinship, may obscure the racist and homophobic prejudices that exist both outside and inside queer communities. Accordingly, this article proposes that we shift to 'opacity' as an epistemological, methodological and ethical parameter that radically queers kinship (studies).

Cluster cytometry for high-capacity bioanalysis.

Flow cytometry specializes in high-content measurements of cells and particles in suspension. Having long excelled in analytical throughput of single cells and particles, only recently with the advent of HyperCyt sampling technology, flow cytometry's multiexperiment throughput has begun to approach the point of practicality for efficiently analyzing hundreds-of-thousands of samples, the realm of high-throughput screening (HTS). To extend performance and automation compatibility, we built a HyperCyt-linked Cluster Cytometer platform, a network of flow cytometers for analyzing samples displayed in high-density, 1,536-well plate format. To assess the performance, we used cell- and microsphere-based HTS assays that had been well characterized in the previous studies. Experiments addressed important technical issues: challenges of small wells (assay volumes 10 µL or less, reagent mixing, cell and particle suspension), detecting and correcting for differences in performance of individual flow cytometers, and the ability to reanalyze a plate in the event of problems encountered during the primary analysis. Boosting sample throughput an additional fourfold, this platform is uniquely positioned to synergize with expanding suspension array and cell barcoding technologies in which as many as 100 experiments are performed in a single well or sample. As high-performance flow cytometers shrink in cost and size, cluster cytometry promises to become a practical, productive approach for HTS, and other large-scale investigations of biological complexity.

Effects of polynitrogen compounds on the activity of recombinant human HIF-1α prolyl hydroxylase 3 in E. coli.

Hypoxia inducible factor 1α (HIF-1α) becomes an important regulation factor within the histiocyte when it is under the hypoxia condition. Recently, prolyl hydroxylases (PHDs) have been identified to inactivation HIF-lα by hydroxylation. In this study, polynitrogen compounds were screened as HIF-1α PHD3 inhibitors. The coding region of human PHD3 DNA was optimized by using synonymous codons according to the code bias of Escherichia coli. Soluble and active human PHD3 was expressed in the E. coli with a Trx fusion tag under a lower induction temperature of 25°C. Mass spectrometry analysis of the resultant peptide product indicated a mass increase of 16 daltons, consistent with hydroxylation of the proline residue in the HIF-1α (556-574) peptide substrate. Polynitrogen compounds (1-4) inhibited the enzymatic hydroxylation of HIF-1α peptide in a concentration-dependent manner, and the apparent IC(50) values were 29.5, 16.0, 12.8 and 60.4 µM respectively. Double reciprocal (1/V versus 1/[HIF-1α peptide]) plots showed that these compounds are noncompetitive inhibitors of the hydroxylation by recombinant human PHD3 with K(i) values of 67.0, 25.3, 67.3, and 82.1 µM respectively. On the other hand, the metal complexes of these polynitrogen compounds (1-4) cannot inhibit the catalytical activity of PHD3. We hypothesized that the inhibitory mechanism of PHD3 activity by polynitrogen compounds is due to their binding to iron to form stable coordination complexes. Our results in this study indicated that polynitrogen compounds (1-4) could be potential inhibitors of PHD3 to regulate the transcriptional activity of HIF-1α.

Microsphere-based flow cytometry protease assays for use in protease activity detection and high-throughput screening.

This protocol describes microsphere-based protease assays for use in flow cytometry and high-throughput screening. This platform measures a loss of fluorescence from the surface of a microsphere due to the cleavage of an attached fluorescent protease substrate by a suitable protease enzyme. The assay format can be adapted to any site or protein-specific protease of interest and results can be measured in both real time and as endpoint fluorescence assays on a flow cytometer. Endpoint assays are easily adapted to microplate format for flow cytometry high-throughput analysis and inhibitor screening.

Structure-function roles of four cysteine residues in the human arsenic (+3 oxidation state) methyltransferase (hAS3MT) by site-directed mutagenesis.

Cysteine (Cys) residues are often crucial to the function and structure of proteins. Cys157 and Cys207 in recombinant mouse arsenic (+3 oxidation state) methyltransferase (AS3MT) are shown to be related to enzyme activity and considered to be the catalytic sites. The roles of some conserved Cys residues in the N-terminal region of the rat AS3MT also have been examined. However, little is known about the roles of the Cys residues in the middle region. The metabolism of inorganic arsenic in human is different from rat and mouse in some aspects though the AS3MT has a high degree of similarity in these species. In order to determine whether the Cys156 and Cys206 (corresponding to the catalytic sites, Cys157 and Cys207 in the mouse AS3MT) in the hAS3MT act as the catalytic sites and to study the roles of the Cys residues (Cys226 and Cys250) near the catalytic center in the middle region, we designed and prepared four mutants (C156S, C206S, C226S, and C250S) in which one Cys residue replaced by serine by PCR-based site-directed mutagenesis. The native form and cysteine/serine mutants were assayed for enzyme activity, free thiols, and the secondary structures by circular dichroism and Fourier transform infrared. Our data show that, besides C156S and C206S, C250S is another potential important site. C226S seems to have the same action as the wild-type hAS3MT with the consistent K(M) and V(max) values. Meanwhile, selenium can also inhibit the methylation of inorganic arsenic by C226S. All the mutants except C226S are calculated to have dramatic changes in the secondary structures. Cys250 might form an intramolecular disulfide bond with another Cys residue. These findings demonstrate that Cys residues at positions 156, 206, and 250 play important roles in the enzymatic function and structure of the hAS3MT.