Characterization and exploration of dynamic variation of volatile compounds in vine tea during processing by GC-IMS and HS-SPME/GC-MS combined with machine learning algorithm.

It is imperative to unravel the dynamic variation of volatile components of vine tea during processing to provide guidance for tea quality evaluation. In this study, the dynamic changes of volatile compounds of vine tea during processing were characterized by GC-IMS and HS-SPME/GC-MS. As a result, 103 volatile compounds were characterized by the two technologies with three overlapped ones. The random forest approach was employed to develop the models and explore key volatile compounds. 23 key compounds were explored, among which 13 were derived from GC-IMS and ten were from HS-SPME/GC-MS. Moreover, the area under the receiver operating characteristics curve with 100 cross validations by the pair-wised models were all 1 for the established models. Furthermore, the primary aroma formation mechanism for the key volatile compounds were mainly involved in fatty acid and amino acid metabolism. Besides, this study provides a theoretical support for directed processing and quality control of vine tea.

A lipidomic and volatilomic approach to map the lipid profile and related volatile compounds in roasted quail meat using circulating non-fried roast technology.

Lipids play a significant role in aroma formation. However, lipid variations and their impact on aroma during the processing of quail meat remain unknown. Therefore, a comprehensive analysis of lipids and aroma compounds was conducted in circulating non-fried roasted quail meat. Nineteen odorants were identified as key aroma compounds in the roasted quail meat at 40 min with OAVs of >1. The concentrations of most key odorants significantly increased in circulating non-fried roasted (CNR) quail meat within the first 30 min of roasting, reaching maximum values at 40 min. Phospholipids, neutral lipids, and sphingolipids emerged as potential markers for distinguishing different samples. Neutral lipids had the highest peak areas and significantly contributed to the aroma retention. Phospholipids and neutral lipids with unsaturated fatty acids, particularly C18 acyl groups, played a crucial role in aroma formation. This study provides valuable insights into the role of lipids in determining aroma quality.

Molecular interactions of the chaperone CcmS and carboxysome shell protein CcmK1 that mediate ß-carboxysome assembly.

The carboxysome is a natural proteinaceous organelle for carbon fixation in cyanobacteria and chemoautotrophs. It comprises hundreds of protein homologs that self-assemble to form a polyhedral shell structure to sequester cargo enzymes, ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) and carbonic anhydrases. How these protein components assemble to construct a functional carboxysome is a central question in not only understanding carboxysome structure and function but also synthetic engineering of carboxysomes for biotechnological applications. Here, we determined the structure of the chaperone protein CcmS, which has recently been identified to be involved in ß-carboxysome assembly, and its interactions with ß-carboxysome proteins. The crystal structure at 1.99 Å resolution reveals CcmS from Nostoc sp. PCC 7120 forms a homodimer, and each CcmS monomer consists of five α-helices and four ß-sheets. Biochemical assays indicate that CcmS specifically interacts with the C-terminal extension of the carboxysome shell protein CcmK1, but not the shell protein homolog CcmK2 or the carboxysome scaffolding protein CcmM. Moreover, we solved the structure of a stable complex of CcmS and the C-terminus of CcmK1 at 1.67 Å resolution and unveiled how the CcmS dimer interacts with the C-terminus of CcmK1. These findings allowed us to propose a model to illustrate CcmS-mediated ß-carboxysome assembly by interacting with CcmK1 at the outer shell surface. Collectively, our study provides detailed insights into the accessory factors that drive and regulate carboxysome assembly, thereby improving our knowledge of carboxysome structure, function, and bioengineering.

Dynamic Compressive Stress Relaxation Model of Tomato Fruit Based on Long Short-Term Memory Model.

Tomatoes are prone to mechanical damage due to improper gripping forces during automated harvest and postharvest processes. To reduce this damage, a dynamic viscoelastic model based on long short-term memory (LSTM) is proposed to fit the dynamic compression stress relaxation characteristics of the individual fruit. Furthermore, the classical stress relaxation models involved, the triple-element Maxwell and Caputo fractional derivative models, are compared with the LSTM model to validate its performance. Meanwhile, the LSTM and classical stress relaxation models are used to predict the stress relaxation characteristics of tomato fruit with different fruit sizes and compression positions. The results for the whole test dataset show that the LSTM model achieves a RMSE of 2.829×10-5 Mpa and a MAPE of 0.228%. It significantly outperforms the Caputo fractional derivative model by demonstrating a substantial enhancement with a 37% decrease in RMSE and a 36% reduction in MAPE. Further analysis of individual tomato fruit reveals the LSTM model's performance, with the minimum RMSE recorded at the septum position being 3.438×10-5 Mpa, 31% higher than the maximum RMSE at the locule position. Similarly, the lowest MAPE at the septum stands at 0.375%, outperforming the highest MAPE at the locule position by a significant margin of 90%. Moreover, the LSTM model consistently reports the smallest discrepancies between the predicted and observed values compared to classical stress relaxation models. This accuracy suggests that the LSTM model could effectively supplant classical stress relaxation models for predicting stress relaxation changes in individual tomato fruit.

Dynamical Attention Hypergraph Convolutional Network for Group Activity Recognition.

Recently, group activity recognition (GAR) has drawn growing interests in video analysis and computer vision communities. The current models of GAR tasks are often impractical in that they suppose that all interactions between actors are pairwise, which only models and leverages part of the information in real entire interactions. Motivated by this, we design a distinct dynamical attention hypergraph convolutional network framework, referred to as DAHGCN, for precise GAR, modeling the entire interactions and capturing the high-order relationships among involved actors in a real-life scenario. Specifically, to learn complementary feature representations for fine-grained GAR, a multilevel feature descriptor (MLFD) module is proposed. Furthermore, for learning higher order interaction relationships, we construct a DAHGCN to accommodate complex group interactions, which can dynamically change the topology of the hypergraph and learn these key representations by virtue of the "similarity-based shared nearest-neighbor (SSNN) clustering" and "attention mechanisms" on hypergraph. Finally, a multiscale temporal convolution (MSTC) module is utilized to explore various long-range temporal dynamic correlations across different frames. In addition, comprehensive experiments on three commonly used GAR datasets clearly demonstrate that, when compared with the state-of-the-art methods, our proposed method can achieve the most optimal performance.

Formation and retention of aroma compounds in pigeons roasted by circulating non-fried roast technique by means of UHPLC-HRMS and GC-O-MS.

Lipids are key aroma contributors in meat products. However, the role of different lipids in the presence of aroma compounds in roasted pigeons has not been studied. The formation of aroma compounds and lipids during the circulating non-fried roasting of pigeons was investigated. The results presented that 18 aroma compounds, including 5-methy-2,3-diethylpyrazine, were identified as key aroma compounds. A total of 6324 lipids were classed into 47 categories, such as phosphatidylcholine (PC), phosphatidylethanolamine (PE), and triglyceride (TG). Nine lipids, containing PA(P-20:0/22:4(7Z,10Z,13Z,16Z)) and LPC 16:0-SN1, showed promise as potential biomarkers for discriminating differential pigeons using OPLS-DA. PC (13.76%), TG (13.58%), and their products were major lipids, among which TG 16:0 16:0 18:2, LPC 18:2-SN1, and PC 18:1_18:1 played a crucial role in the presence of aroma compounds. Interestingly, the linoleic acid, an important aroma contributor, was predominantly bonded to the sn-2 position of phospholipid and sn-3 position of neutral lipids.

Achieving enhanced multifunctional performance for structural composite supercapacitors by reinforcing interfaces with polymer coating.

Carbon fiber structural composite supercapacitors possess the multifunctionality of storing electrochemical energy and withstanding mechanical loads simultaneously, attracting increased attention in electric vehicles, drones, and aircraft sectors. A polymer-based coating was meticulously constructed at the electrode/electrolyte interface to enhance adhesion and stability between active materials and the carbon fiber fabric collector under diverse conditions, especially mechanical stress. Mechanical testing and corresponding physical characterization substantiated the superior performance of the polymer coating. With the protective polymer coating, the optimized structural composite Zn-ion supercapacitor (SZSC), consisting of carbon fiber@active carbon-P (CF@AC-P) cathode, ionogel electrolyte, and Zn anode, displayed a maximum energy density of 164.6 mWh kg-1, at power density of 563.3 mW kg-1. Moreover, the optimized SZSC demonstrated stable operation over more than 8000 cycles at 0.3 mA cm-2 without capacity degradation. The optimized SZSC exhibited a tensile strength of 399.7 MPa and Young's modulus of 11.5 GPa. Furthermore, employing vacuum infusion techniques, the fabricated three-dimensional (3D) wing skin model shell and tube shell curved-surface structural composite Zn-ion supercapacitor component composites showcased exceptional electrochemical performance. These achievements further validate the practicality of 3D multifunctional composites. Consequently, this research presented a practical and straightforward interface engineering approach to develop multifunctional structural devices with remarkable electrochemical and mechanical properties.

Advancing High-Throughput MS-Based Protein Quantification: A Case Study on Quantifying 10 Major Food Allergens by LC-MS/MS Using a One-Sample Multipoint External Calibration Curve.

The LC-MS-based method has emerged as the preferred approach for quantifying food allergens. However, the preparation of a traditional calibration curve (MSCC) is labor-intensive and error-prone. Here, a sensitive and robust LC-MS/MS method for quantifying 10 major food allergens was developed and validated, where the one-sample multipoint external calibration curve (OSCC) was employed instead of MSCC. By employing the multiple isotopologue reaction monitoring (MIRM) technique with only one spiked level in the blank, OSCC can be effectively established. Results demonstrate that the proposed method exhibits excellent performance in selectivity, sensitivity, accuracy, and precision, comparable to that of the traditional MSCC. Additionally, this strategy allows for isotope sample dilution by monitoring the less abundant MIRM channel. Moreover, the developed method was successfully applied to investigate the contamination of 10 food allergens in commercial food products. With its high throughput and robustness, the MIRM-OSCC-LC-MS/MS methodology has many potential applications, especially in the MS-based protein quantification analysis.

An integrated calibration strategy for the development and validation of an LC-MS/MS method for accurate quantification of egg allergens (Gal d 1-6) in foods.

Accurate determination of egg allergens in food is vital for allergen management and labeling. However, quantifying egg allergens with mass spectrometry poses challenges and lacks validation methods. Here, we developed and validated an LC-MS/MS method for quantifying egg allergens (Gal d 1-6) in foods. Sample extraction, enzymatic digestion, purification, proteins/peptides selection, and calibration curves were optimized. VMVLC[+57]NR (Gal d 1) and GTDVQAWIR (Gal d 5) exhibited outstanding sensitivity and stability, serving as quantitation markers for egg white and yolk. Using a matrix-matched calibration curve with allergen ingredients as calibrants and labeled peptides as standards, we achieved highly accurate quantitation. Validation involved spiking egg protein into egg-free foods, showing excellent sensitivity (LOQ: 1-5 mg/kg), accuracy (62.4 %-88.5 %), and reproducibility (intra-/inter-day precision: 3.5 %-14.2 %/8.2 %-14.6 %). Additionally, we successfully applied this method to commercial food analysis. These findings demonstrate optimal allergen selection, peptides, and calibration strategy are crucial parameters for food allergen quantification via MS-based methods.

Hydrophobic Hydrogen-Bonded Polymer Network for Efficient and Stable Perovskite/Si Tandem Solar Cells.

The pursuit of highly efficient and stable wide-band gap (WBG) perovskite solar cells (PSCs), especially for monolithic perovskite/silicon tandem devices, is a key focus in achieving the commercialization of perovskite photovoltaics. In this study, we initially designed poly(ionic liquid)s (PILs) with varying alkyl chain lengths based on density functional theory calculations. Results pinpoint that PILs with longer alkyl chain lengths tend to exhibit more robust binding energy with the perovskite structure. Then we synthesized the PILs to craft a hydrophobic hydrogen-bonded polymer network (HHPN) that passivates the WBG perovskite/electron transport layer interface, inhibits ion migration and serves as a barrier layer against water and oxygen ingression. Accordingly, the HHPN effectively curbs nonradiative recombination losses while facilitating efficient carrier transport, resulting in substantially enhanced open-circuit voltage (Voc ) and fill factor. As a result, the optimized single-junction WBG PSC achieves an impressive efficiency of 23.18 %, with Voc as high as 1.25 V, which is the highest reported for WBG (over 1.67 eV) PSCs. These devices also demonstrate outstanding thermostability and humidity resistance. Notably, this versatile strategy can be extended to textured perovskite/silicon tandem cells, reaching a remarkable efficiency of 28.24 % while maintaining exceptional operational stability.

Comprehensive evaluation of aroma and taste properties of different parts from the wampee fruit.

Wampee is a tropical fruit having high medicinal value. To fully realize the fruit's potential, it is essential to reveal the flavor characteristics. In this study, a comprehensive analysis of the aroma and taste profiles of different parts from the wampee fruit was conducted. The aroma profile was analyzed by E-nose, and 67 volatile components were identified through HS-SPME-GC-MS. Among them, 11 were considered as crucial compounds. Additionally, 42 volatile components were identified by HS-GC-IMS, with 22 compounds showing a variable importance in projection scores greater than 1.0. Moreover, the taste profile and representative compounds were analyzed by E-tongue and HPLC, and 12 compounds were considered as important taste contributors based on taste activity value. These findings shed light on the various compounds responsible for the unique aroma and taste of the wampee fruit, providing theoretical foundation for exploring ways for its comprehensive utilization and development.

Dietary exposure risk assessment of pyrethroids in fruits and vegetables: a national scale investigation.

The pyrethroids (PYRs) were extensively used to increase agriculture outputs. However, the cumulative exposures of PYRs would bring about potential risks through food intake. It is an urgent requirement to explore the cumulative exposures on the fruits and vegetables. In this study, a total of 1720 samples incorporating eight primary fruits and vegetables collected around China were investigated to assess the health risk for adults and children from eight PYRs. The relative potency factor (RPF) method was employed to reveal both chronic and acute cumulative exposure. As a result, the hazard index (HI) were 0.004 ~ 0.200% and 11.85 ~ 99.19% for chronic and acute cumulative dietary exposure, respectively. The national wide investigation indicated the cumulative assessments were not hazardous. Besides, the acute intake of pear, grape, and lettuce should be paid on more attention, particularly. This study provides compelling evidence to develop relative policy and regulation to improve the food quality and safety.

A Novel Wide-Band Directional MUSIC Algorithm Using the Strength Proportion.

The directional multiple signal classification (Dir-MUSIC) algorithm based on the antenna gain array manifold has been proposed to find the direction of the partial discharge (PD) source in substations. However, PD signals are wideband signals and the antenna gain pattern functions are always different at different frequencies; therefore, the accuracy can be improved using a wideband Dir-MUSIC algorithm. In this paper, wideband Dir-MUSIC algorithms are discussed and a novel wideband Dir-MUSIC algorithm using the strength proportion (DirSP) is proposed. This algorithm estimates a focusing PD signal at a certain frequency using the strength proportion among different directions, and then the Dir-MUSIC algorithm can process the focusing PD signal at this frequency. In simulations, when the antenna gain functions among different frequency bins are quite different, the Dir-MUSIC algorithm loses accuracy; meanwhile, DirDP performs very well. In the experiments, we deal with six sets of samples, and the mean error and standard deviation are both smaller than 4° better than other methods.

Advances in mechanisms and engineering of electroactive biofilms.

Electroactive biofilms (EABs) are electroactive microorganisms (EAMs) encased in conductive polymers that are secreted by EAMs and formed by the accumulation and cross-linking of extracellular polysaccharides, proteins, nucleic acids, lipids, and other components. EABs are present in the form of multicellular aggregates and play a crucial role in bioelectrochemical systems (BESs) for diverse applications, including biosensors, microbial fuel cells for renewable bioelectricity production and remediation of wastewaters, and microbial electrosynthesis of valuable chemicals. However, naturally occurred EABs are severely limited owing to their low electrical conductivity that seriously restrict the electron transfer efficiency and practical applications. In the recent decade, synthetic biology strategies have been adopted to elucidate the regulatory mechanisms of EABs, and to enhance the formation and electrical conductivity of EABs. Based on the formation of EABs and extracellular electron transfer (EET) mechanisms, the synthetic biology-based engineering strategies of EABs are summarized and reviewed as follows: (i) Engineering the structural components of EABs, including strengthening the synthesis and secretion of structural elements such as polysaccharides, eDNA, and structural proteins, to improve the formation of biofilms; (ii) Enhancing the electron transfer efficiency of EAMs, including optimizing the distribution of c-type cytochromes and conducting nanowire assembly to promote contact-based EET, and enhancing electron shuttles' biosynthesis and secretion to promote shuttle-mediated EET; (iii) Incorporating intracellular signaling molecules in EAMs, including quorum sensing systems, secondary messenger systems, and global regulatory systems, to increase the electron transfer flux in EABs. This review lays a foundation for the design and construction of EABs for diverse BESs applications.

Migration behavior and dietary exposure risk assessment of pesticides residues in honeysuckle (Lonicera japonica Thunb.) based on modified QuEChERS method coupled with tandem mass spectrometry.

The honeysuckle was widely appreciated as tea beverage owing to the biological activities and the unique aroma and flavor. It is in urgent requirement to explore the migration behavior and dietary exposure as the pesticide residues would bring about potential risks through honeysuckle intake. The optimized QuEChERS procedure coupled with the HPLC-MS/MS and GC-MS/MS methods were employed to determine 93 pesticide residues of seven classifications including carbamates, pyrethroid, triazoles, neonicotinoids, organophosphorus, organochlorine, and others for 93 honeysuckle samples from four primary production bases. As a result, 86.02% of the samples were contaminated by at least one pesticide. Unexpectedly, the banned pesticide of carbofuran was also identified. The migration behavior of metolcarb was the highest, whereas thiabendazole contributed less risk to the infusion with relative lower transfer rate. Both the chronic and acute exposure yielded low risk for human health with five high risk pesticides of dichlorvos, cyhalothrin, carbofuran, ethomyl, and pyridaben. Besides, this study provides foundation of dietary exposure risk assessment for honeysuckle and other likewise products.

Flavoromics Approach in Critical Aroma Compounds Exploration of Peach: Correlation to Origin Based on OAV Combined with Chemometrics.

It is essential to seek the critical aroma compounds to identify the origins of peach as well as provide a guidance for quality evaluation. In this study, the peach was characterized by HS-SPME/GC-MS. Subsequently, the odor activity value (OAV) was calculated to specify the primary aroma-active compounds. Afterwards, the chemometrics methods were employed to explore the potentially critical aroma on the basis of p value, fold change (FC), S-plot, jack-knifing confidence interval, variable importance for projection (VIP), and the Shared and Unique Structures (SUS) plots. As a result, five compounds (methyl acetate, (E)-hex-2-enal, benzaldehyde, [(Z)-hex-3-enyl] acetate, and 5-ethyloxolan-2-one) were considered as critical aromas. Moreover, the multi-classification model was developed with an outstanding performance (accuracy of 100%) using the five critical aroma. Moreover, the potential chemical basis of odors was sought through sensory evaluation. In addition, this study provides the theoretical and practical foundation for geographical origin traceability and quality evaluation.

Novel one-point calibration strategy for high-throughput quantitation of microcystins in freshwater using LC-MS/MS.

Precise quantification of microcystins (MCs) in freshwater is crucial for environmental monitoring and human health. However, the preparation of traditional multi-sample external calibration curve (MSCC) is time consuming and prone to error. Here, a novel one-point calibration strategy including one sample multi-point calibration curve (OSCC) and in sample calibration curve (ISCC) is proposed for the quantitation of eight MCs in freshwater lakes using liquid chromatography tandem mass spectrometry (LC-MS/MS). The multiple isotopologue reaction monitoring (MIRM) of MCs and its 15N-labelled internal standards were used for OSCC and ISCC, respectively. The isotopic abundance of each MIRM channel could be calculated and measured accurately. Additionally, this strategy was comprehensively validated and showed good performance in selectivity, sensitivity, accuracy and precision as the traditional MSCC. Interestingly, OSCC could realize sample dilution by monitoring the less abundant MIRM transitions, while ISCC remove blank matrixes and generate calibration curve in each study samples. Furthermore, the proposed methodology was successfully applied to analyze several freshwater lake samples contaminated by MCs. Considering the advantages of excluding the MSCC preparation, simplified workflows and improved throughput, OSCC and ISCC will be favored for MCs monitoring and as an emerging approach in environmental pollutant control and prevention.

Value-driven career attitude and job performance: An intermediary role of organizational citizenship behavior.

Background: Value-driven career attitude (VDCA) is considered a dimension of a protean career attitude (PCA). Individuals with this attitude seek out personally meaningful experiences and set their own psychological career success standards. This study investigates the association between value-driven career attitude and job performance. It looks at how organizational citizenship behavior affects the relationship between value-driven career attitudes and job performance. Methods: A self-reported questionnaire was used to collect data from 400 random employees of SMEs in Pakistan during the early pandemic. We chose Cochran's formula to determine the appropriate sample size, and PLS-SEM was used to analyze the model. P-O fit and self-determination theory is the theoretical lenses used in this study. The underpinning theories to this study enable the researchers to establish a link between VDCA, OCB, and job performance. Results: By analyzing a sample of 400 employees from active enterprises, we discover that VDCA contributes to an improvement in job performance. Furthermore, OCB plays an intervening effect in the relationship between VDCA and job performance. Thus, the study provided evidence for the underpinning models of P-O fit and self-determination theory. Conclusion: This study adds to the body of knowledge by investigating the connections between VDCA, OCB, and job performance in SMEs. The existing literature sheds scant light on these linkages, leaving a gap that this study will address. The current study expands on other themes to provide an in-depth analysis of many under-explored PCA outcomes, which may open up new avenues for future researchers to broaden and strengthen PCA with other constructs.

Development of Network Security Based on the Neural Network PSD Algorithm.

The more frequent occurrence of network security incidents has an impact on network security. Through the research on network security situational awareness, this paper constructs a multilevel network security situation evaluation index system from various aspects and uses the Elman neural network optimized by the genetic algorithm to evaluate network security situation. Aiming at the disadvantage of subjective dependence in the traditional assignment method of basic probability assignment function, Elman neural network is used to obtain the basic probability assignment function to increase its objectivity, and it is optimized with the PSD algorithm. In addition, the neural network is further improved by the genetic algorithm. In the traditional D-S evidence theory, an evidence correction step is added to optimize the situation that the final judgment result is incorrect due to evidence conflict. Finally, the fusion rules of the D-S evidence theory are used to fuse the support degrees of the four first-level situations to different security levels to obtain the final network security situation assessment result. The results show that the prediction accuracy of the GA-Elman neural network model is as high as 80%, which is significantly higher than that of the traditional D-S model, indicating that the model proposed in this paper has improved the accuracy of the assessment and prediction results. In conclusion, this study provides feasible theoretical prediction guidance for the accurate assessment of network security posture, reveals the improvement ideas for network security development, and is of great significance for the maintenance of network environment security.

Optimization of Multi-Objective Mobile Emergency Material Allocation for Sudden Disasters.

The mobile emergency system is a new emergency mode that provides a solution to deal with increasingly frequent sudden disasters by reasonably allocating mobile emergency facilities and optimizing the allocation of mobile emergency materials. We consider mobile emergency cost and mobile emergency time as two objective functions. This paper establishes a multi-objective mobile emergency material allocation model, and transforms the multi-objective. We choose the emergency material transportation path for coding, and apply the hybrid leapfrog algorithm for material allocation to obtain the optimal solution. Finally, the feasibility of the model is verified by taking Zhengzhou urban area under the "21.7" severe rainstorm and flood disaster in Henan Province. The result analyses show that the model can correspond to each stage of mobile emergency material allocation based on the value of cost preference, and put forward suggestions on the location of mobile emergency facilities and the amount of material allocation.