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Abstract This study aimed to investigate the adaptive mechanisms of mulberry (Morus alba) to waterlogged conditions, with a specific focus on the development of adventitious roots (ARs), alteration of growth strategies, and adjustment of chlorophyll fluorescence parameters. To achieve this goal, 4-year-old potted mulberry plants were selected for research, and a waterlogging simulation method was implemented. Four treatments were established to investigate the effects of varying water conditions on leaf waterlogging damage, the number of ARs, plant height, chlorophyll fluorescence parameters, and proton motive force (pmf) parameters in mulberry plants. These treatments included the control group (CK), shallow submerged group (SS), half-submerged group (HS) and deep submerged group (DS). Our results showed that (1) The number of ARs in each group increased with increasing waterlogging time. (2) Waterlogging stress inhibited the height growth of mulberry, and the changes in plant height in the HS and DS groups were significantly lower than those in the CK and SS groups. (3) The maximum photochemical quantum yield (Fv/Fm) in the HS and DS groups decreased significantly under waterlogging stress. The nonphotochemical quenching (NPQt) of mulberry leaves in the submergence group increased significantly in the early stage of waterlogging stress, and the NPQt in the submergence group increased continuously with increasing waterlogging time. (4) Thylakoid conductivity to protons (gH +) in the leaves of mulberry decreased significantly under waterlogging stress, whereas the steady-state rate of proton flux (vH +) and total electrochromic shift (ECSt) increased significantly. The morphological, physiological, and ecological responses of mulberry plants to waterlogging stress include the timely generation of ARs at the stem base, the adjustment of plant growth strategies, and the repair of photosynthetic response centers in leaves through heat dissipation and thylakoid acidification mechanisms.

Abstract Epithelial ovarian carcinoma (EOC) is the most fatal among female reproductive system tumors. The immune tumor microenvironment and ubiquitin-proteasome pathway are closely related to the proliferation, invasion, and response to chemotherapy in EOC. However, their specific roles in EOC have not been fully elucidated. Therefore, we aimed to recognize potential prognostic markers and novel therapeutic targets for EOC. We constructed the ubiquitin-related signature risk model comprising HSP90AB1, FBXO9, SIGMAR1, STAT1, SH3KBP1, EPB41L2, DNAJB6, VPS18, PPM1G, AKAP12, FRK, and PYGB, specifically for patients with EOC. The high-risk model presented a worse prognosis, primarily associated with the B-cell receptor signaling pathway, ECM receptor interaction, focal adhesion, and actin cytoskeleton regulations. Analysis of the immune landscape revealed a higher abundance of B cells, M2 macrophages, neutrophil CD4 T cells, cancer-associated fibroblasts, macrophage neutrophils, and fibroblasts in the high-risk group. It also exhibited lower tumor mutation burden, mRNAsi, and EREG-mRNAsi and reduced sensitivity to other chemotherapy drugs, except dasatinib. These findings serve as a valuable indicator for personalized treatment strategies and clinical stratification in managing patients with EOC. Additionally, our study will serve as a foundation for future mechanistic research to explore the association between the ubiquitin-proteasome pathway and EOC.

Abstract The aim of this study was to develop a medical imaging and comprehensive stacked learning-based method for predicting high- and low-risk thymoma. A total of 126 patients with thymomas and 5 patients with thymic carcinoma treated at our institution, including 65 low-risk patients and 66 high-risk patients, were retrospectively recruited. Among them, 78 patients composed the training cohort, while the remaining 53 patients formed the validation cohort. We extracted 1702 features each from the patients’ arterial-, venous-, and plain-phase images. Pairwise subtraction of these features yielded 1702 arterial-venous, arterial-plain, and venous-plain difference features each. The Mann‒Whitney U test and least absolute shrinkage and selection operator (LASSO) and SelectKBest methods were employed to select the best features from the training set. Six models were built with a stacked learning algorithm. By applying stacked ensemble learning, three machine learning algorithms (XGBoost, multilayer perceptron (MLP), and random forest) were combined by XGBoost to produce the the six basic imaging models. Then, the XGBoost algorithm was applied to the six basic imaging models to construct a combined radiomic model. Finally, the radiomic model was combined with clinical information to create a nomogram that could easily be used in clinical practice to predict the thymoma risk category. The areas under the curve (AUCs) of the combined radiomic model in the training and validation cohorts were 0.999 (95% CI 0.988–1.000) and 0.967 (95% CI 0.916–1.000), respectively, while those of the nomogram were 0.999 (95% CI 0.996–1.000) and 0.983 (95% CI 0.990–1.000). This study describes the application of CT-based radiomics in thymoma patients and proposes a nomogram for predicting the risk category for this disease, which could be advantageous for clinical decision-making for affected patients.

Abstract Removing texture while preserving the main structure of an image is a challenging task. To address this, this paper propose an image smoothing method based on global gradient sparsity and local relative gradient constraints optimization. To reduce the interference of complex texture details, adopting a multi-directional difference constrained global gradient sparsity decomposition method, which provides a guidance image with weaker texture detail gradients. Meanwhile, using the luminance channel as a reference, edge-aware operator is constructed based on local gradient constraints. This operator weakens the gradients of repetitive and similar texture details, enabling it to obtain more accurate structural information for guiding global optimization of the image. By projecting multi-directional differences onto the horizontal and vertical directions, a mapping from multi-directional differences to bi-directional gradients is achieved. Additionally, to ensure the consistency of measurement results, a multi-directional gradient normalization method is designed. Through experiments, we demonstrate that our method exhibits significant advantages in preserving image edges compared to current advanced smoothing methods.

Abstract The evaluation of Physical Education Teaching Methods in Colleges and Universities faces two main challenges: an excess of evaluating elements and a lack of assessment framework. Hence, the research proposes the multi-feature fuzzy evaluation model based on artificial intelligence to streamline the evaluation process and provide an efficient framework for accessing teaching methods. The framework integrates natural/human language using fuzzy instructions considering three evaluation perspectives, including the management stage, instructors, and students and employs the enhanced cuckoo search optimization algorithm. After the teaching expert has determined each parameter's ratings, they are fed into the improved cuckoo search algorithm and solved using an unbiased function to assess the assessment's final result. It incorporates the students' mobility mechanism and movement vector deconstruction designed based on functional criteria. A system for evaluating the quality of instruction has been developed utilizing the proposed model with enhanced cuckoo search optimization. The results indicate that the proposed algorithm has achieved the highest scores across multiple assessment categories, average skill performances of 97.01%, learning progress of 87.36%, physical fitness of 93.49%, participation rate of 95.04%, student satisfaction of 95.49%, and physical education of 96.8% teaching efficiency. The usefulness of the proposed framework in enhancing physical education teaching methods has been demonstrated by comparing the results with traditional methods. It contributes to advancing pedagogical practices in the field.

Abstract The family of phosphate transporters (PHTs) mediates the uptake and translocation of Pi inside the plants. However, little is known about transporters in soybean. Therefore, Searched the Genome Database for Soybean, 57 GmPHTs family members were identified in soybean, Phylogenetic analysis suggested that members of the PHTs gene family can be divided into six clades. Collinearity analysis revealed that most of the GmPHT genes shared syntenic relationships with PHTs members in Arabidopsis thaliana and that large segment duplication played a major driving force for GmPHTs evolution in addition to tandem duplication. Further analysis of the promoter revealed that light-responsive elements and abiotic stress-responsive elements were widely distributed within the promoter regions of GmPHT genes. Based on RNA-seq data, GmPHTs showed different expression patterns in roots and leaves of soybean treated with long-term low phosphorus and short-term low phosphorus, in addition, the expression levels of GmPHT genes can be regulated by drought stresses, it was implied that the induced expression of GmPHTs could promote phosphorus uptake and transport in soybean and thus adapt to low phosphorus and drought stress, which is the first step dissection of Pi transport system and probably refers to new roles of PHTs genes in soybean.

Abstract Developing an efficient and quality remote sensing (RS) technology using volume and efficient modelling in different aircraft RS images is challenging. Generative models serve as a natural and convenient simulation method. Because aircraft types belong to the fine class under the rough class, the issue of feature entanglement may occur while modelling multiple aircraft classes. Our solution to this issue was a novel first-generation realistic aircraft type simulation system (ATSS-1) based on the RS images. It realised fine modelling of the seven aircraft types based on a real scene by establishing an adaptive weighted conditional attention generative adversarial network and joint geospatial embedding (GE) network. An adaptive weighted conditional batch normalisation attention block solved the subclass entanglement by reassigning the intra-class-wise characteristic responses. Subsequently, an asymmetric residual self-attention module was developed by establishing a remote region asymmetric relationship for mining the finer potential spatial representation. The mapping relationship between the input RS scene and the potential space of the generated samples was explored through the GE network construction that used the selected prior distribution z, as an intermediate representation. A public RS dataset (OPT-Aircraft_V1.0) and two public datasets (MNIST and Fashion-MNIST) were used for simulation model testing. The results demonstrated the effectiveness of ATSS-1, promoting further development of realistic automatic RS simulation.

Abstract Because of its high flooding tolerance, in recent years, mulberry has become a tree species that is used in plant restoration in impact zones in reservoir areas. Therefore, 3-year-old potted forage mulberry seedlings were used to investigate the mechanism of mulberry adaptation to flooding stress. An indoor simulated flooding method was adopted to study the morphology of mulberry seedling leaves and the changes in leaf chlorophyll fluorescence parameters and fluorescence imaging under different flooding times and depths. The results showed that the leaves of mulberry seedlings treated with shallow submergence remained healthy during the flooding period, while the leaves of mulberry seedlings treated with half submergence and full submergence showed different degrees of waterlogging symptoms in the middle and late flooding periods and formed adventitious roots at the base of the stem. Most of the chlorophyll fluorescence parameters decreased at the beginning of flooding, but the steady-state degree of closure of PS II reaction centres (1-qP_Lss) increased significantly. In the later stage of flooding, the fluorescence parameters showed relatively stable trends. Based on these results, we conclude that mulberry has high flooding tolerance due to a combination of morphological and physiological responses.

Abstract In this paper, we first synthesis three-dimensional jasmine-like Cu@L-aspartic acid(L-ASP) inorganic–organic hybrid nanoflowers to load palladium-platinum nanoparticles (Pd–Pt NPs) as the signal enhancer in order to quantify intracellular speckle-type POZ domain protein. Scanning electron microscope, fourier transform infrared, energy dispersive spectrometer, X-ray photoelectron spectroscopy analysis was used to characterize the newly synthesized materials. The newly formed Cu@L-Asp/Pd-PtNPs can catalyze the decomposition of hydrogen peroxide and exhibit excellent catalytic performance. When different concentration of speckle-type POZ domain protein is captured by speckle-type POZ domain protein antibody linked to the surface of Cu@L-Asp/Pd–Pt NPs, the current signal decreases with the increase concentration of speckle-type POZ domain protein. After optimization, the speckle-type POZ domain protein immunosensor exhibited a good linear response over a concentration range from 0.1–1 ng mL−1 with a low detection limit of 19 fg mL−1. The proposed sensor demonstrates good stability within 28 days, acceptable reproducibility (RSD = 0.52%) and selectivity to the speckle-type POZ domain protein in the presence of possible interfering substances and has potential application for detecting other intracellular macromolecular substances.

Abstract Utilizing acoustic information for search route planning will greatly increase the success rate of searching for underwater targets, which requires rapid computing of numerous underwater acoustic fields. The efficiency of traditional computing methods is too low to meet the requirements of rapid applications. In this paper, a underwater multi-acoustic fields computing model is developed based on ray theory, and multi-level hybrid parallel computing strategies are designed based on the model characteristics, and a dynamic scheduling optimization algorithm at process level is introduced to solve the load imbalance problem. All parallel computing strategies are tested in Tianhe-II High Performance Computer (HPC) system, and the tests show that: 1. compared with the serial version, hybrid parallel computing strategy provides a Speedup of 75.7 under 240 cores; 2. after the introduction of the dynamic scheduling optimization algorithm, the speed of solving the underwater acoustic fields is further increased by 28.99% under the same computing resources, and the Speedup reaches 97.67; 3. the optimal combination of process/thread parameter on the Tianhe-II HPC system is given as 3/8, and the final Speedup reaches 112.13.

Abstract Green consumption is a crucial pathway towards achieving global sustainability goals. Product-oriented green advertisements can effectively stimulate consumers’ latent needs and convert them into eventual purchasing intentions and behaviors, thereby promoting green consumption. Given that neuromarketing methods facilitate the understanding of consumers’ decision-making processes, this study combines prospect theory and need fulfillment theory, employing event-related potentials (ERPs) as measures to explore changes in consumers’ cognitive resources and emotional arousal levels when confronted with green products and advertising information. This enables inference regarding consumers’ acceptance of purchasing and their psychological processes. Behavioral results indicated that message framing influences consumers’ purchases, with consumers consuming more green in response to negatively framed advertisements. EEG results indicated that matching positive framing with utilitarian green products was effective in increasing consumers’ cognitive attention in the early cognitive stage. In the late stage of cognition negative frames stimulated consumers’ mood swings more, and the influence of product type depended on the role of message frames, and the consumption motivation induced by the product, whose influence was overridden by external evaluations such as message frames. These research findings provide an explanation for the impact of frame information on consumers’ purchasing decisions at different stages, assisting marketers in devising diverse promotional strategies based on product characteristics to foster the development and practice of green consumption. This will further embed the concept of green consumption advocated by organizations such as the United Nations Environment Programme (UNEP), World Wildlife Fund (WWF), and Greenpeace into the public consciousness.

Abstract Prostate cancer lineage plasticity is a key driver in the transition to neuroendocrine prostate cancer (NEPC), and the RTK/RAS signaling pathway is a well-established cancer pathway. Nevertheless, the comprehensive link between the RTK/RAS signaling pathway and lineage plasticity has received limited investigation. In particular, the intricate regulatory network governing the interplay between RTK/RAS and lineage plasticity remains largely unexplored. The multi-omics data were clustered with the coefficient of argument and neighbor joining algorithm. Subsequently, the clustered results were analyzed utilizing the GSEA, gene sets related to stemness, multi-lineage state datasets, and canonical cancer pathway gene sets. Finally, a comprehensive exploration of the data based on the ssGSEA, WGCNA, GSEA, VIPER, prostate cancer scRNA-seq data, and the GPSAdb database was conducted. Among the six modules in the clustering results, there are 300 overlapping genes, including 3 previously unreported prostate cancer genes that were validated to be upregulated in prostate cancer through RT-qPCR. Function Module 6 shows a positive correlation with prostate cancer cell stemness, multi-lineage states, and the RTK/RAS signaling pathway. Additionally, the 19 leading-edge genes of the RTK/RAS signaling pathway promote prostate cancer lineage plasticity through a complex network of transcriptional regulation and copy number variations. In the transcriptional regulation network, TP63 and FOXO1 act as suppressors of prostate cancer lineage plasticity, whereas RORC exerts a promoting effect. This study provides a comprehensive perspective on the role of the RTK/RAS pathway in prostate cancer lineage plasticity and offers new clues for the treatment of NEPC.

Abstract The clinical characteristics of Cushing’s syndrome (CS) vary with etiology, and few studies have investigated the risk factors affecting CS recurrence after surgery. This retrospective study involved 202 patients diagnosed with CS between December 2012 and December 2022. The patients were divided into three groups according to etiology: Cushing's disease (CD), adrenocortical adenoma (ACA), and ectopic adrenocorticotropic hormone (ACTH) syndrome (EAS). Of the patients with CS, 41.9% had hypokalemia and 15.0% had hypophosphatemia. The cortisol levels were negatively correlated with blood potassium, blood chlorine, and blood phosphorus. Moreover, 22.4% of patients had an abnormal heart structure, 11.2% had centripetal remodeling, 5.6% had centripetal hypertrophy, and 5.6% had centrifugal hypertrophy. The overall recurrence rate of CS caused by pituitary tumors and adrenal adenoma was 25.7%. The recurrence times were longer in the ACA group versus the CD group, in patients

Abstract A three-layer microscopic model with Fe atoms as the top and bottom layer and SBR polymer composites as the middle layer and SBR polymer composite was established and studied. By adding C atoms as reinforcement, the stability and elastic modulus and frictional coefficient changes of SBR polymer composites before and after adding C atoms were studied. In this study, the molecular dynamics method was used to change of elastic modulus was observed by stretching, compression and shear of the SBR polymer composite; The simulation shows that after adding C atom the elastic modulus of SBR polymer composite increased, the friction coefficient of polymer composite upper and lower decreases and the relative atomsic concentration, temperature, velocity, overall temperature average, kinetic energy, total energy and MSD in the thickness direction are reduced after adding C atoms. The stability of SBR polymer composites is enhanced, and the deformation under shear is weakened. In addition, it is found that the binding energy between SBR polymer composites and Fe atoms is reduced after adding C atoms.The stability of SBR polymer composites is improved during use. This work provides a method for studying the properties of rubber composites by studying the enhancement of the stability of SBR polymer composites from the microscopic point of view.

Abstract Electrical switching operation in a substation which locates in a high-voltage transmission system alters operating modes of main wiring in either the substation or the system. Major alterations may have negative influences on the switchgear of main wiring in a short time. The quantitative study of this problem has to be based on establishing equivalent circuits of main wiring, when there rarely are formulas to calculate the reactance of tubular busbars. In this paper on the basis of the electromagnetic field theory, the magnetic induction and flux linkages outside and inside tubular conductors are obtained from the Ampere Loop Theorem, and then the formulas to calculate approximately the reactance of tubular busbars with a three-phase parallel arrangement are derived. From the process and results of the calculation in an example it may be seen that the formulas are applied simply, conveniently and rapidly, and may be valuably spread in practical electrical engineering.

Abstract Advanced sensor technology provides accurate information for transparent monitoring and real-time control of the power grid. Tunnel magnetoresistance (TMR) elements with high sensitivity and linearity provide a new technical means for current measurement in medium-voltage DC power distribution systems. This paper proposes a dual air-gap closed-loop TMR current sensor and its optimal design method based on the magnetic field’s minimum uniformity coefficient. The dual air-gap structure reduces the measurement error caused by the eccentricity of the wire, and the theory and modelling of the minimum magnetic field uniformity coefficient optimise the key parameters, such as the inner radius of the magnetic core, the distance of the air-gap and the area size of the section side. Finally, a sensor prototype with a rated measurement current of ± 50 A was developed. The experiment results show that the relative error of the proposed TMR current sensor is less than 0.2% under the rated current. The conclusion can be drawn that the proposed sensor with the optimised design effectively improves the measurement accuracy.

Abstract Cinnamon aqueous extract’s active substance base remains unclear and its mechanisms, mainly the therapeutic target of anti-Alzheimer’s disease (AD)-related GABAergic synaptic dysfunction, remain unclear. Here, 30 chemical components were identified in the aqueous extract of cinnamon using LC/MS; secondly, we explored the brain-targeting components of the aqueous extract of cinnamon, and 17 components had a good absorption due to the blood–brain barrier (BBB) limitation; thirdly, further clustering analysis of active ingredient targets by network pharmacology showed that the GABA pathway with GABRG2 as the core target was significantly enriched; then, we used prominent protein–protein interactions (PPI), relying on a protein-metabolite network, and identified the GABRA1, GABRB2 and GABRA5 as the closest targets to GABRG2; finally, the affinity between the target and its cognate active compound was predicted by molecular docking. In general, we screened five components, methyl cinnamate, propyl cinnamate, ( +)-procyanidin B2, procyanidin B1, and myristicin as the brain synapse-targeting active substances of cinnamon using a systematic strategy, and identified GABRA1, GABRB2, GABRA5 and GABRG2 as core therapeutic targets of cinnamon against Alzheimer's disease-related GABAergic synaptic dysfunction. Exploring the mechanism of cinnamon’ activities through multi-components and multiple targets strategies promise to reduce the threat of single- target and symptom-based drug discovery failure.

Abstract Soft, worm-like robots show promise in complex and constrained environments due to their robust, yet simple movement patterns. Although many such robots have been developed, they either rely on tethered power supplies and complex designs or cannot move external loads. To address these issues, we here introduce a novel, maggot-inspired, magnetically driven “mag-bot” that utilizes shape memory alloy-induced, thermoresponsive actuation and surface pattern-induced anisotropic friction to achieve locomotion inspired by fly larvae. This simple, untethered design can carry cargo that weighs up to three times its own weight with only a 17% reduction in speed over unloaded conditions thereby demonstrating, for the first time, how soft, untethered robots may be used to carry loads in controlled environments. Given their small scale and low cost, we expect that these mag-bots may be used in remote, confined spaces for small objects handling or as components in more complex designs.

Abstract Cooperative behaviour can evolve through conditional strategies that direct cooperation towards interaction partners who have themselves been cooperative in the past. Such strategies are common in human cooperation, but they can be vulnerable to manipulation: individuals may try to exaggerate their past cooperation to elicit reciprocal contributions or improve their reputation for future gains. Little is known about the prevalence and the ramifications of misrepresentation in human cooperation, neither in general nor about its cultural facets (self-sacrifice for the group is valued differently across cultures). Here, we present a large-scale interactive decision making experiment (N = 870), performed in China and the USA, in which individuals had repeated cooperative interactions in groups. Our results show that (1) most individuals from both cultures overstate their contributions to the group if given the opportunity, (2) misrepresentation of cooperation is detrimental to cooperation in future interactions, and (3) the possibility to build up a personal reputation amplifies the effects of misrepresentation on cooperation in China, but not in the USA. Our results suggest that misrepresentation of cooperation is likely to be an important factor in (the evolution of) human social behaviour, with, depending on culture, diverging impacts on cooperation outcomes.

Abstract Although national health-related quality of life population norms had been published based on the EuroQol 5-Dimensions 5-levels scale, China is a vast country with diverse cultural and social development in various regions. Therefore, regional population norms may better reflect the health status of residents in a given area. The purpose of the study was to derive the HRQoL population norm for adult general population in southern Jiangsu Province using the EQ-5D-5L scale and explore potential influencing factors. The data were based on a cross-sectional survey conducted in Liyang City from March 2019 to July 2020. EQ-5D-5L utility scores based on Chinese value set and EQ-VAS scores were used to assess HRQoL. The Tobit regression model and generalized linear model were performed to identify the association among potential covariates and HRQoL. The means (95% confidence interval) of the EQ-5D-5L utility scores and EQ-VAS scores were 0.981(0.980–0.983) and 83.6(83.2–83.9), respectively. Younger people (≤ 40 years old) were more likely to experience problems with anxiety or depression. Additionally, women had lower HRQoL scores although multivariate analysis found no statistical difference between the sexes. Lower HRQoL was associated with advanced age, lower socioeconomic status, no spouse, lack of regular physical activities, smoking cessation, and chronic non-communicable diseases. Subjects who declared that they were afflicted by diseases presented significantly lower utility scores, ranging from 0.823 (0.766–0.880) for memory-related diseases to 0.978 (0.967–0.989) for hepatic diseases. Regional population norms of HRQoL are needed in the health economic study owing to the great socioeconomic differences across regions in China. The present study provides HRQoL population norms for adults in southern Jiangsu. These norm values could help policy makers better allocate limited health resources and prioritize service plans.