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Objective To prevent water leakage issues in large-diameter shield tunnel, ensure high-speed train operational safety and normal tunnel functionality, it is necessary to carry out analysis and research on tunnel segment joint deformation and waterproof performance under high-speed train vibration. Method Relying on the Zhanjiang Bay Subsea Tunnel project, a soil-tunnel three-dimensional model and a sealing gasket-groove two-dimensional refined model are established using finite element software. First, the dynamics response and deformation characteristics of segment joints under high-speed train vibration in large-diameter shield tunnel are studied, with longitudinal joints as example. Then, the waterproof performance of a sealing gasket is analyzed based on the most adverse joint deformation working condition. Result & Conclusion The research results indicate that under the vibration of a single high-speed train, the displacement response process of segment joints can be divided into three stages: deformation increase, deformation being danger, and deformation decline. During the second stage, significant joint opening and misalignment occur at the upper part and both ends of the segment ring, while adjacent joints experience reduced opening and misalignment due to compression from both adjacent side segments. There is almost no deformation at the joints below the track bed, as the tunnel track bed significantly mitigates the impact of train vibration on segment linings. The contact stress between sealing gaskets follows a U-shaped distribution, decreasing from the central contact area towards both edges between the sealing gasket and the segment groove. Leakage is more likely to occur at the contact surfaces between the sealing gaskets than along the contact path between the sealing gasket and the segment groove. Under the most adverse working condition of this project, a provided triangular perforated sealing gasket is found to meet the tunnel waterproof requirements.

Abstract Background Fatigue is a relatively prevalent condition among hemodialysis patients, resulting in diminished health-related quality of life and decreased survival rates. The purpose of this study was to investigate the relationship between fatigue and body composition in hemodialysis patients. Methods This cross-sectional study included 92 patients in total. Fatigue was measured by Functional Assessment of Chronic Illness Therapy – Fatigue (FACIT-F) (cut-off ≤ 34). Body composition was measured based on quantitative computed tomography (QCT), parameters including skeletal muscle index (SMI), intermuscular adipose tissue (IMAT), and bone mineral density (BMD). Handgrip strength was also collected. To explore the relationship between fatigue and body composition parameters, we conducted correlation analyses and binary logistic regression. Results The prevalence of fatigue was 37% (n = 34), abnormal bone density was 43.4% (n = 40). There was a positive correlation between handgrip strength and FACIT-F score (r = 0.448, p

Abstract In high energy heavy-ion collisions, the high speed valence charges will produce intense electromagnetic fields within the resulting quark-gluon plasma. Utilizing the AMPT model, this paper presents a comprehensive analysis of the magnetic field distribution generated from non-central collisions between $$\mathrm{Au+Au}$$ Au + Au nuclei at $$\sqrt{s_{\text{NN}}}={200}\;{\text{GeV}}$$ s NN = 200 GeV . The initial geometric parameters of the collision and the electric conductivity of the quark-gluon plasma have a dominant influence on the evolution of the magnetic field, while the plasma diffusion and the CME effect have a lesser impact and only slightly involve the original magnetic field by inducing new magnetic fields. This finding suggests that the dynamics of the quark-gluon plasma can be roughly decoupled from the effect of the electromagnetic field.

In this study, chromatographic and mass spectrometry conditions, sample cleanup and extraction, composition and ratio of salt and purifiers were optimized, which established a high-throughput screening method for 11 plant growth regulators and 79 antibiotic drugs in sprout vegetables by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Samples were extracted by 1% acetonitrile-EDTA-mcllvaine buffer solution, purified by QuEChERS, and separated by ACQUITY UPLC HSS T3 column with gradient elution. Electrospray positive and negative ion mode was used in multi-reaction monitoring mode, and matrix curve external standard method was used to quantify. The limits of quantitation of 90 compounds were in the range of 0.1~15.4 μg/kg. The average recoveries were in the range of 42.2%~138.6% with relative standard deviations lower than 17.2%. In this study, simultaneous, rapid and high-throughput screening and detection of 90 high-risk substances in sprout vegetables were established, which is conducive to a more full understanding of the quality and safety problems of sprout vegetables.

Abstract Background As an economically important crop, tea is strongly nitrogen (N)-dependent. However, the physiological and molecular mechanisms underlying the response of N deficiency in tea are not fully understood. Tea cultivar “Chunlv2” [Camellia sinensis (L.) O. Kuntze] were cultured with a nutrient solution with 0 mM [N-deficiency] or 3 mM (Control) NH4NO3 in 6 L pottery pots containing clean river sands. Results N deficiency significantly decreased N content, dry weight, chlorophyll (Chl) content, L-theanine and the activities of N metabolism-related enzymes, but increased the content of total flavonoids and polyphenols in tea leaves. N deficiency delayed the sprouting time of tea buds. By using the RNA-seq technique and subsequent bioinformatics analysis, 3050 up-regulated and 2688 down-regulated differentially expressed genes (DEGs) were isolated in tea leaves in response to N deficiency. However, only 1025 genes were up-regulated and 744 down-regulated in roots. Gene ontology (GO) term enrichment analysis showed that 205 DEGs in tea leaves were enriched in seven GO terms and 152 DEGs in tea roots were enriched in 11 GO items based on P

Abstract Background Although proximal femoral nail anti-rotation (PFNA) and bipolar hemiarthroplasty (BHA) are selected by most of the orthopaedic surgeons for elderly intertrochanteric fractures (ITFs) patients, there is still no consensus on the superiority of PFNA and BPH for the elderly with unstable comminuted ITFs. The study aims to compare the curative effects of PFNA and cementless BHA on unstable comminuted ITFs in the elderly. Methods From January 2012 to December 2016, we retrospectively reviewed 62 ITFs patients up to the inclusion and exclusion criteria in the study. Depending on the type of surgery, the patients were divided into two groups: Group BHA (n= 30) and Group PFNA (n = 32). The ITFs were classified according to Evans-Jensen. Hospitalization time, operation time, bleeding loss, weight bearing duration, Harris hip scores, 10-m walking speed, gait and postoperative complications were compared between the two groups. Results There was no significant difference between the groups in hospital stay (P > 0.05). The BHA group trended to have a shorter operation time and a larger volume of blood loss (P 0.05). There was no significant difference in postoperative complications between the two groups (P > 0.05). Conclusion The BHA allows an earlier return to weight-bearing activity, but ultimately has the same effective treatments as the PFNA for the elderly with unstable comminuted ITFs.

Hyperspectral compressed imaging is a novel imaging detection technology based on compressed sensing theory that can quickly acquire spectral information of terrestrial objects in a single exposure. It combines reconstruction algorithms to recover hyperspectral data from low-dimensional measurement images. However, hyperspectral images from different scenes often exhibit high-frequency data sparsity and existing deep reconstruction algorithms struggle to establish accurate mapping models, leading to issues with detail loss in the reconstruction results. To address this issue, we propose a hyperspectral reconstruction method based on global gradient information and local low-rank priors. First, to improve the prior model's efficiency in utilizing information of different frequencies, we design a gradient sampling strategy and training framework based on decision trees, leveraging changes in the loss function gradient information to enhance the model's predictive capability for data of varying frequencies. Second, utilizing the local low-rank prior characteristics of the representative coefficient matrix, we develop a sparse sensing denoising module to effectively improve the local smoothness of point predictions. Finally, by establishing a regularization term for the reconstruction process based on the semantic similarity between the denoised results and prior spectral data, we ensure spatial consistency and spectral fidelity in the reconstruction results. Experimental results indicate that the proposed method achieves better detail recovery across different scenes, demonstrates improved generalization performance for reconstructing information of various frequencies, and yields higher reconstruction quality. [ABSTRACT FROM AUTHOR]

This research investigates how fourth-instar larvae of the potato tuber moth, Phthorimaea operculella, respond to plant secondary metabolites (sucrose, glucose, nicotine, and tannic acid) both in terms of gustatory electrophysiology and feeding behavior. The objective is to establish a theoretical foundation for employing plant-derived compounds in potato tuber moth control. We employed single-sensillum recording techniques and dual-choice leaf disk assays to assess the gustatory electrophysiological responses and feeding preferences of these larvae towards the mentioned compounds. Sensory neurons responsive to sucrose, glucose, nicotine, and tannic acid were identified in the larvae’s medial and lateral sensilla styloconica. Neuronal activity was influenced by stimulus type and concentration. Notably, the two types of sensilla styloconica displayed distinct response patterns for sucrose and glucose while they had similar firing patterns towards nicotine and tannic acid. Sucrose and glucose significantly promoted larval feeding, while nicotine and tannic acid had significant inhibitory effects. These findings demonstrate that the medial and lateral sensilla styloconica house sensory neurons sensitive to both feeding stimulants and inhibitors, albeit with differing response profiles and sensitivities. This study suggests that sucrose and glucose are promising candidates for feeding stimulants, while nicotine and tannic acid show potential as effective feeding inhibitors of P. operculella larvae.

Abstract Background Nitrogen (N) fertilizer is commonly considered as one of the most important limiting factors in the agricultural production. As a result, a large amount of N fertilizer is used to improve the yield in modern tea production. Unfortunately, the large amount of N fertilizer input has led to increased plant nitrogen-tolerance and decreased amplitude of yield improvement, which results in significant N loss, energy waste and environment pollution. However, the effects of N-deficiency on the metabolic profiles of tea leaves and roots are not well understood. Results In this study, seedlings of Camellia sinensis (L.) O. Kuntze Chunlv 2 were treated with 3 mM NH4NO3 (Control) or without NH4NO3 (N-deficiency) for 4 months by sandy culture. The results suggested that N-deficiency induced tea leaf chlorosis, impaired biomass accumulation, decreased the leaf chlorophyll content and N absorption when they were compared to the Control samples. The untargeted metabolomics based on GC-TOF/MS approach revealed a discrimination of the metabolic profiles between N-deficient tea leaves and roots. The identification and classification of the altered metabolites indicated that N deficiency upregulated the relative abundances of most phenylpropanoids and organic acids, while downregulated the relative abundances of most amino acids in tea leaves. Differentially, N-deficiency induced the accumulation of most carbohydrates, organic acids and amino acids in tea roots. The potential biomarkers screened in N-deficient leaves compared to Control implied that N deficiency might reduce the tea quality. Unlike the N-deficient leaves, the potential biomarkers in N-deficient roots indicated an improved stress response might occur in tea roots. Conclusions The results demonstrated N deficiency had different effects on the primary and secondary metabolism in tea leaves and roots. The findings of this study will facilitate a comprehensive understanding of the N-deficient tea plants and provide a valuable reference for the optimized N nutrient management and the sustainable development in the tea plantations.

Summary: In this study, six groups of carrots were designed and fermented using Weissella paramensenteroides MbWp142 (WP), Levilactobacillus brevis GDMCC 1.773 (LS), Leuconostoc mesenteroides GDMCC 1.774 (SE), mixed fermentation of three lactic acid bacteria (WP + LS + SE), pasteurisation group (BG) and natural fermentation group (CK). GC–MS results indicated that inoculation of WP + LS + SE increased the types and contents of flavour substances such as alcohols, esters and hydrocarbons. Compared with other experimental groups, the peak nitrite value in the LS group was lower due to the production of organic acids by lactic acid bacteria. Sensory evaluation revealed that the quality and flavour of carrot fermented by LS were superior to those fermented by SE, WP and WP + LS + SE. Therefore, Levilactobacillus brevis used as a starter for fermenting carrot can enhance product quality and reduce nitrite accumulation during fermentation. [ABSTRACT FROM AUTHOR]

Micro‐expressions are spontaneous and unconscious facial movements that reveal individuals' genuine inner emotions. They hold significant potential in various psychological testing fields. As the face is a 3D deformation object, the emergence of facial expression leads to spatial deformation of the face. However, existing databases primarily offer 2D video sequences, limiting descriptions of 3D spatial information related to micro‐expressions. Here, a new micro‐expression database is proposed, which contains 2D image sequences and corresponding 3D point cloud sequences. These samples were classified using both an objective method based on the facial action coding system and a non‐objective emotion classification method that considers video contents and participants' self‐reports. A variety of feature extraction techniques are applied to 2D data, including traditional algorithms and deep learning methods. Additionally, a novel local curvature‐based algorithm is developed to extract 3D spatio‐temporal deformation features from the 3D data. The authors evaluated the classification accuracies of these two features individually and their fusion results under leave‐one‐subject‐out (LOSO) and tenfold cross‐validation. The results demonstrate that fusing 3D features with 2D features results in improved recognition performance compared to using 2D features alone. [ABSTRACT FROM AUTHOR]