In this paper, we discuss optical properties of the topologically charged rotating black hole. We study the horizon, the photon region, the shadow of the black hole and other observables. The results show that in addition to the black hole spin parameter $a$, the other two parameters, five-dimensional mass parameter $\beta$ and electric charge $q$, are also found to affect the horzion, the photon region and the black hole shadow. In a certain range, with the increase of the three parameters, the horizon distance, shape of the photon region and the black hole shadow will all shrink. Moreover, with the increase of these three parameters, the distortion parameter $\delta_{s}$ gradually increases, while the peak of the black hole energy emission rate decreases.

The porous structure is an important three-dimensional morphological feature of the peripheral nerve guidance conduit (NGC), which permits infiltration of cells, nutrients, and molecular signals, and the discharge of metabolic waste. Porous structures with precisely customised pore sizes, porosities, and connectivities were used to construct fully permeable, semi-permeable, and asymmetric peripheral NGCs to replace traditional nerve autografts in treatment of long-segment peripheral nerve injury. In this review, the features of porous structures and classification of NGCs based on these characteristics are discussed. Common methods for constructing 3D porous NGCs in current research are described, as well as the pore characteristics and the parameters used to tune the pores. The effects of the porous structure on the physical properties of NGCs including biodegradation, mechanical performance, and permeability were analysed. Pore structure affects the biological behaviour of Schwann cells, macrophages, fibroblasts, and vascular endothelial cells during peripheral nerve regeneration. Construction of ideal porous structures is a significant advancement in the regeneration of peripheral nerve tissue engineering materials. The purpose of this review is to generalise, summarise, and analyse the preparation methods for porous NGCs and their biological functions in promoting peripheral nerve regeneration to guide development of medical nerve repair materials.

In this paper, the current technologies of the regenerative shock absorber systems have been categorized and evaluated. Three drive modes of the regenerative shock absorber systems, namely the direct drive mode, the indirect drive mode and hybrid drive mode are reviewed for their readiness to be implemented. The damping performances of the three different modes are listed and compared. Electrical circuit and control algorithms have also been evaluated to maximize the power output and to deliver the premium ride comfort and handling performance. Different types of parameterized road excitations have been applied to vehicle suspension systems to investigate the performance of the regenerative shock absorbers including that of the nonlinear regenerative shock absorber. The research gaps for comparison of the different drive modes and the nonlinearity analysis of the regenerative shock absorbers are identified and, the corresponding research questions have been proposed for future work.

Ocean circulation serve as the primary channels for transporting material and energy flows throughout the entire ocean system, which plays a crucial role in shaping Earth’s climate, weather patterns, and marine ecosystems. The ocean movements have far-reaching impacts on both the environment and human life. An effective method for semantically modeling the ocean circulation is urgently required to be established. To achieve a unified description of ocean circulation at the semantic level, this paper introduces the theory and methodology of ocean ontology, which is developed through an analysis of domain knowledge in ocean circulation. We focus on analyzing the concepts, temporal relationships, and spatial relationships of ocean circulation. By defining classes, properties, relationships, instances, and constraint conditions within the logical structure of an ontology, it is feasible to formalize the expression of conceptual elements and their relationships. Additionally, semantic inference rules are established to finalize the construction of the ocean circulation ontology. The effectiveness of ontology construction has been verified through practical examples. Furthermore, a specialized knowledge base framework has been developed upon the ontology description of ocean circulation. Some examples of knowledge base queries have been articulated and verified. The results demonstrate that this ontology can effectively represent the relevant knowledge in the domain of ocean circulation and provide a meaningful strategy for investigating semantic integration and knowledge sharing in this field.

Enhancing residents' purchasing intention of prepared dishes is crucial for the sustainable development of the prepared dishes industry. Understanding how residents' cognition influences their purchasing intentions can provide valuable insights for developing and refining industry policies. Based on the theory of distributed cognition, this study utilizes questionnaire data from urban residents in Beijing and Shanghai, and employs Structural Equation Modeling to explore the influence of cognition on the continuous purchasing intention of Chinese urban residents towards prepared dishes. The study results reveal that: (1) individual and geographical power significantly positively impact on residents' continuous purchasing intentions of prepared dishes, while cultural power perception does not have a significant effect. (2) Risk perception partially mediates the effect of personal and geographical power on continuous purchasing intention and fully mediates the effect of cultural power on continuous purchasing intention. Recommendations include: (1) The government should enhance standardization and supervision to create a favorable consumption environment; (2) Enterprises should provide more objective and transparent information to improve residents' knowledge of prepared dishes and establish a good reputation.

Centralized/Cloud Radio Access Networks (C-RAN) are deployed in converged fixed-mobile networks to exploit the flexibility coming from joint application of Network Function Virtualization (NFV) and Software Defined Networking (SDN). In this context, optical links connecting C-RAN nodes, possibly based on the Ethernet standards, may carry traffic with different requirements in terms of latency and throughput. This paper considers the problem of traffic aggregation on C-RAN optical Ethernet links with latency control for fronthaul traffic and throughput capability for backhaul traffic. Integrated hybrid nework technique is applied to show how time transparency can be enforced for Ethernet encapsulated Common Public Radio Interface (CPRI) traffic while allowing statistical multiplexing of backhaul traffic. Simulation results show the effectiveness of segmentation of backhaul traffic to allow exploitation of the available bandwidth even with high capacity CPRI options.

Intelligent ship technology is currently an international research hotspot, and model predictive control is widely used in the path-tracking control of intelligent vehicles. To construct an intelligent ship anti-disturbance path-tracking control method, firstly, an environmental disturbance model was constructed with the actual meteorological data of the target sea area. Secondly, the Fossen ship equation of motion is linearized and discretized as the ship motion model. Thirdly, the expression of the prediction equation is derived from the ship motion model. Fourthly, the cost function is constructed by using the polar diameter and polar angle values of the ship. Fifth, the power function in the cost function is replaced with an exponential function to obtain an improved cost function. Sixthly, according to the Lyapunov theory and the MPC terminal constraint theory, the stability of the improved cost function is verified. Seventh, different test paths are set up, the environmental disturbance model is taken as the external disturbance, the ship motion model, the prediction equation, and the improved cost function are used to design the anti-disturbance path-tracking control algorithm according to the model prediction control idea for simulation experiments. Finally, different MATLAB simulation results show that the improved cost function can resist disturbance of the external wave, current, and wind, and effectively track the target path. Therefore, this study provides a reference for improving the navigation safety of ship path-tracking.

Ocean wave energy conversion as one of the renewable clean energy sources is attracting the research interests of many people. This review introduces different types of power take-off technology of wave energy converters. The main focus is the linear direct drive power take-off devices as they have the advantages for ocean wave energy conversion. The designs and optimizations of power take-off systems of ocean wave energy converters have been studied from reviewing the recently published literature. Also, the simple hydrodynamics of wave energy converters have been reviewed for design optimization of the wave energy converters at specific wave sites. The novel mechanical designs of the power take-off systems have been compared and investigated in order to increase the energy harvesting efficiency.

The Urban heat island (UHI) effect has evolved into one of the key environmental problems affecting urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and UGI spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional data set reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using stepwise regression model and partial least square regression (PLSR) model, the complex response relationship between UGI pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the partial least square regression PLSR model is due to the stepwise regression model. The PLSR model points out that moderately increasing the average building height, CA, PLAND, LSI and LPI play a positive role in inhibiting/slowing down the growth of LST (land surface temperature), and the cooling effect of index weights decreases in order. However, the interaction effects of CA×Cohesion×AI×LPI and PLAND×CA×Cohesion×AI×LPI exert relatively small weight on the cooling effect, and according to the results, suggestions such as UGI structure and urban construction layout optimization can effectively alleviate the urban heat island effect are proposed.

The Capon algorithm can be applied to reprocess SAR images, resulting in super-resolution super-resolution reconstructed scenes with lower sidelobe levels. Base on this idea, we have proposed a processing chain of Super-Resolution Persistent Scatterer Interferometry (SR-PSI), to increase PS density. In this paper, we review the main aspect of SR-PSI. We also propose a revised robust Capon algorithm. The result of real-life Sentinel-1 (S-1) data is shown.

Choosing new energy vehicles for travel, especially electric vehicles, is an important component of building a low-carbon urban transportation system. However, the charging need of electric vehicle users is still constrained by the unreasonable layout and insufficient supply of public charging piles in the city. Private charging pile sharing as an alternative policy tool can play a very good role in solving this problem. But it needs decision-makers in urban transportation to take corresponding measures to promote. This paper constructs an evolutionary game model to study the decision behavior of participants in private piles sharing platform. Through numerical simulation analysis, it is found that under most parameter conditions, the government tends to establish a shared charging pile platform based on public interests. Private charging pile owners are influenced by the relationship between the cost of supply modification and revenue, and they tend to join the shared platform when they expect to recover the modification cost. The research conclusions of this paper will provide support for exploring how participants make decisions to maximize overall benefits in the development of low-carbon urban transportation.

Rare study on quantitative relationship between energetic impact of debris flows on the intensity and duration of growth disturbances of tree rings was carried out, partly due to lack of feasible approaches and detailed field evidence. In this study, we firstly determine the age of a recent debris flow derived from historic landslide deposits at Qingyang mountain (QYM) on the northeastern Tibet plateau by dendrogeomorphic technique. We acquired the quantitative data of annual widths of tree rings in history and confirmed the influence of debris flow rather than other factors (e.g. climatic event and inset outbreaking) in disturbing the growth of tree rings in a specific year. Using the approach, we determined the age of the debris flow at QYM occurred in 1982, which was speculated to be triggered by high monthly precipitation of July in 1982. Subsequently, based on the boundaries of historic debris flow identified on remote sensing images before and after 1982 and depth-integrated continuum model, we reconstructed the process of 1982-debris flow and obtained the kinematic energy of debris flow impacting on the sampled trees. Based on the study, we observed that two growth disturbance patterns of tree rings influenced by the reconstructed 1982-debris flow were revealed including growth suppression and asymmetric growth. A raw logarithm relationship between duration (i.e. lasting time for the disturbed tree rings to recover the initial width) and intensity of growth disturbances (i.e. growth suppression ratio of disturbed tree rings) was obtained. We concluded that there is a negative exponential relationship between simulated kinematic energy of debris flow impacting on the disturbed trees and time to recover the initial width of corresponding tree rings.

Objectives: Although pitch reception poses a great challenge for individuals with cochlear implants (CIs), formal auditory training (e.g., high variability phonetic training, HVPT) has been shown to provide direct benefits in pitch-related perceptual performances such as lexical tone recognition for CI users. As lexical tones in spoken language are expressed with a multitude of distinct spectral, temporal, and intensity cues, it is important to determine the sources of training benefits for CI users. The purpose of the present study was to conduct a rigorous fine-scale evaluation with the categorical perception (CP) paradigm to control the acoustic parameters and test the efficacy and sustainability of HVPT for Mandarin-speaking pediatric CI recipients. The main hypothesis was that HVPT-induced perceptual learning would greatly enhance CI users’ ability to extract the primary pitch contours from spoken words for lexical tone identification and discrimination. Furthermore, individual differences in immediate and long-term gains from training would likely be attributable to baseline performance and duration of CI use. Design: Twenty-eight prelingually deaf Mandarin-speaking kindergarteners with CIs were tested. Half of them received five sessions of HVPT within a period of three weeks. The other half served as control who did not receive the formal training. Two classical CP tasks on a tonal continuum from Mandarin Tone 1 (high-flat in pitch) to Tone 2 (mid-rising in pitch) with fixed acoustic features of duration and intensity were administered before (pretest), immediately after (posttest), and 10 weeks post training termination (follow-up test). Participants were instructed to either label a speech stimulus along the continuum (i.e., identification task) or determine whether a pair of stimuli separated by zero or two steps from the continuum was the same or different (i.e., discrimination task). Identification function measures (i.e., boundary position and boundary width) and discrimination function scores (i.e., between-category score, within-category score, and peakedness score) were assessed for each child participant across the three test sessions.Results: Linear mixed-effects (LME) models showed significant training-induced enhancement in lexical tone categorization with significantly narrower boundary width and better between-category discrimination in the immediate posttest over pretest for the trainees. Furthermore, training-induced gains were reliably retained in the follow-up test 10 weeks after training. By contrast, no significant changes were found in the control group across sessions. Regression analysis confirmed that baseline performance (i.e., boundary width in the pretest session) and duration of CI use were significant predictors for the magnitude of training-induced benefits. Conclusions: The stringent CP tests with synthesized stimuli that excluded acoustic cues other than the pitch contour and were never used in training showed strong evidence for the efficacy of HVPT in yielding immediate and sustained improvement in lexical tone categorization for Mandarin-speaking children with CIs. The training results and individual differences have remarkable implications for developing personalized computer-based short-term HVPT protocols that may have sustainable long-term benefits for aural rehabilitation in this clinical population.

Forest resources are renewable,rational exploitation and utilization of forest resources are not only conducive to sustainable development of population, but also can obtain higher economic benefits. Based on actual timber harvesting problems,a combined harvesting model of timber and non-timber with nonlinear harvesting term was established.Firstly, using the qualitative theory of ordinary differential equations, the dynamic behavior of the model is studied, and the existence and stability of the equilibrium point of the model are proved .Secondly, the optimal control solution is obtained by using the optimal control theory.Finally, the optimal harvesting strategy of timber and non-timber products is given based on the numerical simulation results, which provides a certain theoretical basis for the sustainable development of forestry ecological economy.

Ovarian cancer poses a significant therapeutic challenge owing to the lack of specific targets for treatment. New treatment strategies are needed to improve patient outcomes and reduce the toxicity of existing therapies. This study aimed to investigate the synergistic effects of recombi-nant human apurinic/apyrimidinic endonuclease 1/redox factor 1 (rhAPE1/Ref-1) and aspirin on PEO14 and CAOV-3 ovarian cancer cells and human umbilical vein endothelial cells (HUVECs). Specifically, this study examined the mechanisms underlying the effect of rhAPE1/Ref-1 and as-pirin on cell death and the associated pathways. Cell viability was assessed using the MTT assay, and flow cytometry analysis and caspase-3/7 activity assays were conducted to determine apop-tosis. Western blotting was performed to evaluate the cleavage of poly(ADP-ribose) polymerase (PARP). Exposure to aspirin (3 mM) for 24 h did not affect cell viability in PEO14. Co-incubation of aspirin with rhAPE1/Ref-1 in PEO14 cells led to rhAPE1/Ref-1 acetylation and intracellular hyperacetylation. Co-treatment with aspirin (3 mM) and rhAPE1/Ref-1 induced a rhAPE1/Ref-1 concentration-dependent increase in cell death, particularly in PEO14 cells, as well as apoptosis, caspase-3/7 activation, and PARP cleavage. Furthermore, this combination treatment significantly increased paclitaxel-induced PEO14 cell death. Therefore, co-administration with rhAPE1/Ref-1 and aspirin is a potential strategy for ovarian cancer treatment.

The regenerated magnesia-calcium brick samples that had added 0, 1.5, 3.0 wt.% aluminium oxide (Al2O3) were prepared by using spent magnesia-calcium bricks, fused magnesia and Al2O3 powder additive as the main raw materials. The phases, microstructures, room temperature and hot flexural strength, resistance to cement clinker corrosion and strength of coating adherence were investigated respectively. It indicated that the addition of Al2O3 increased mainly resulting in the content of tetracalcium aluminoferrite (C4AF) and tricalcium aluminate (C3A) increased in the regenerate samples. The bulk density, the room temperature flexural strength and the strength of coating adherence all increased, while the hot flexural strength and corrosion resistance both deteriorated along with the increase of Al2O3 addition. It was because that on the one hand the low melting point phases of C4AF and C3A improved the sinterability of the regenerated samples during the burning stage, on the other hand they melted or existed in liquid phase during the experimental temperature (1573 K and 1823 K) which degraded hot flexural strength and corrosion resistance, and enhanced the strength of coating adherence as the wettability of the liquid phase. The content of Al2O3 in the regenerated magnesia-calcium brick should not be higher than 1.1 wt.%, considering its room and high-temperature performances for cement rotary kiln.

This article systematically studied the A-optimal designs of a high-order mixture central polynomial model, which is an advancement of the research results for the A-optimal design of the most recent third-order mixture central polynomial model and a more accurate response surface model. This article is based on the simplex center design, obtaining measurement values at various design points, and verifying them through the A-optimal equivalence theorem. We also compare the A-efficiency of designs through examples, which can be applied to the A-optimal precise design of the fourth-order mixture model.

Numerous researchers acknowledge that occupational pension protects employees. However, the total occupational pension is shared by employees and employers in China, which is a cost. This study aimed to explore the occupational pension on corporate social responsibility (CSR) and organizational resilience. We drew upon insights from cost-stickiness and resource-based theories to develop a model that illuminates how occupational pension affected firms’ stance toward CSR in the context of the COVID-19 pandemic and how this, in turn, has result organizational resilience. This study categorized CSR into strategic and responsive activities based on cost stickiness. We selected a total of 34,145 observations of Chinese listed companies over the period 2010-2023 as a sample to investigate whether occupational pension changes CSR strategies. The results showed that the cost pressure to contribute to occupational pension drove firms to reduce their responsive CSR and boost their strategic CSR. Moreover, strategic CSR improved organizational resilience, but responsive CSR did not. This relationship between occupational pension and CSR was significantly and negatively moderated by the minimum wage and population aging. Whereas, the relationship between CSR and organizational resilience was significantly and positively moderated by digital transformation and marketing capabilities. This study has implications for decision-making regarding high-quality firm development.

Recently, the triple-network convergence system (TNCS) has emerged from the deep integration of the power grid, transportation network, and information network. Fault recovery research in the TNCS is important since this system's complexity and interactivity can expand the faults scale and increase faults impact. Currently, fault recovery focuses primarily on single power grids and cyber-physical systems, but there are certain shortcomings, such as ignoring uncertainties including generator start-up failures and the occurrence of new faults during recovery, energy supply-demand imbalances leading to system security issues and communication delay caused by network attacks. In this study, we propose a recovery method based on the improved TD3 algorithm, factoring in shortcomings of the existing research. Specifically, we establish a TNCS model to analyze interaction mechanisms and design a state matrix to represent the uncertainty changes in the TNCS, a negative reward to reflect the impact of unit start-up failures, a special reward to reflect the impact of communication delay and an improved Actor network update mechanism. Experimental results show that our method obtains the optimal recovery decisions, maximizes restoration benefit in power grid failure scenarios and demonstrates a strong resilience against communication delay caused by DoS attacks.

Endophytic bacteria, especially those participate in nitrogen fixation, play critical roles in supplying essential nutrients for legume plant growth. Compared to the numerous bacterial microbiome reports targeting legume roots and nodules, little is known about embryonic bacteria that facilitate plant nutrient utilization after seed germination. Here, we collected and investigated endophytic bacterial microbiomes in edible pea (Pisum sativum) embryos using five representative cultivars and a pea sprout control. Twenty-six nitrogen-fixing bacteria (NFBs) were isolated from pea embryos, with three strains found in fresh pea (FGP) and snow pea (SP) exhibiting the strongest nitrogenase activity. Some NFB isolates are also potassium-solubilizing bacteria (KSBs) or phosphorus-solubilizing bacteria (PSBs) utilizing inorganic and/or organic phosphorus. All 26 NFBs showed variable levels of indole-3-acetic acid (IAA) secretion. The nutrient-solubilizing NFBs identified in our research are valuable resources for biofertilizer development. At the microbiome level, high-throughput 16S ribosomal RNA (rRNA) sequencing of 40 bacterial collections from pea embryos revealed similar community structures and species abundances and diversities in most samples. Our embryo-derived endophytic bacterial pool provides a microbiome platform for seed dormancy and germination research of edible peas.

Purpose: This study builds upon an established effective training method to investigate the advantages of high variability phonetic identification training for enhancing lexical tone perception and production in Mandarin-speaking pediatric cochlear implant (CI) recipients, who typically face ongoing challenges in these areas. Method: Thirty two Mandarin-speaking children with CIs were quasi-randomly assigned into the training group (TG) and the control group (CG). The sixteen TG participants received five sessions of high variability phonetic training (HVPT) within a period of three weeks. The CG participants did not receive the training. Perception and production of Mandarin tones were administered before (pretest) and immediately after (posttest) the completion of HVPT via lexical tone recognition task and picture naming task. Both groups participated in the identical pretest and posttest with the same time frame between the two test sessions. Results: TG showed significant improvement from pretest to posttest in identifying Mandarin tones for both trained and untrained speech stimuli. Moreover, perceptual learning of HVPT facilitated trainees’ lexical tone production as rated by a cohort of 10 Mandarin-speaking adults with normal hearing. In contrast, CG did not exhibit significant changes in either perception or production. Conclusion: The results represent initial evidence of HVPT-induced transfer of perceptual learning to lexical tone production in CI users, which supports the application of this speech training protocol to aural rehabilitation practice.

Compressed Sensing (CS) MRI has shown great potential in enhancing time efficiency. Deep learning techniques, specifically Generative Adversarial Networks (GANs), have emerged as potent tools for speedy CS-MRI reconstruction. Yet, as the complexity of deep learning recon-struction models increases, this can lead to prolonged reconstruction time and challenges in achieving convergence. In this study we present a novel GAN-based model that delivers superior performance without escalating model complexity. Our generator module, built on the U-net architecture, incorporates dilated residual (DR) networks, thus expanding the network's receptive field without increasing parameters or computational load. At every step of the downsampling path, this revamped generator module includes a DR network, with the dilation rates adjusted according to the depth of the network layer. Moreover, we have introduced a channel attention mechanism (CAM) to distinguish between channels and reduce background noise, thereby fo-cusing on key information. This mechanism adeptly combines global maximum and average pooling approaches to refine channel attention. We conducted comprehensive experiments with the designed model using public domain MRI datasets of the human brain. Ablation studies af-firmed the efficacy of the modified modules within the network. Compared to other relevant models, our proposed model exhibits exceptional performance, achieving not only excellent sta-bility but also outperforming other networks in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The model presents a promising pathway for enhancing the efficiency and quality of CS-MRI reconstruction.

How language mediates emotional perception and experience is poorly understood. The present event-related potential (ERP) study examined the explicit and implicit processing of emotional speech to differentiate the relative influences of communication channel, emotion category and task type in the prosodic salience effect. Thirty participants (15 women) were presented with spoken words denoting happiness, sadness and neutrality in either the prosodic or semantic channel. They were asked to judge the emotional content (explicit task) and speakers’ gender (implicit task) of the stimuli. Results indicated that emotional prosody (relative to semantics) triggered larger N100 and P200 amplitudes with greater delta, theta and alpha inter-trial phase coherence (ITPC) values in the corresponding early time windows, and continued to produce larger LPC amplitudes and faster responses during late stages of higher-order cognitive processing. The relative salience of prosodic and semantics was modulated by emotion and task, though such modulatory effects varied across different processing stages. The prosodic salience effect was reduced for sadness processing and in the implicit task during early auditory processing and decision-making but reduced for happiness processing in the explicit task during conscious emotion processing. Additionally, across-trial synchronization of delta, theta and alpha bands predicted the ERP components with higher ITPC values significantly associated with stronger N100, P200 and LPC enhancement. These findings reveal the neurocognitive dynamics of emotional speech processing with prosodic salience tied to stage-dependent emotion- and task-specific effects, which can reveal insights to research reconciling language and emotion processing from cross-linguistic/cultural and clinical perspectives.

Phthalate esters (PAEs) are a ubiquitous kind of environmental endocrine-disrupting chemicals, causing environmental and health issues. EstJ6 is an effective phthalate-degrading hydrolase, and its mutant with a combination of three non-conservative distal mutations has an improved activity against PAEs with unknown molecular mechanisms. Herein, we attempt to fill the significant gap between distal mutations and the activity of this enzyme using computational approaches. We find mutations result in a redistribution of enzyme’s preexisting conformational states and dynamics changes of key functional regions, especially the lid over the active site. The outward motion of the lid upon mutations should make it easier for substrates or products to enter or exit. Additionally, the stronger substrate binding affinity and conformational rearrangements of catalytic reaction-associated residues in mutant, accompanied by the strengthened communication within the protein, might contribute to the elevated catalytic efficiency. Finally, an attempt has been done to improve the thermostability of EstJ6 upon introducing a distal disulfide bond between residues A23 and A29, and the simulation results are as expected. Together, our work explored the allosteric effects caused by distal mutations, which could provide insights into the rational design of esterases for industrial applications in the future.

This study investigated the fatigue properties and interfacial strengthening mechanisms of Al6061-to-Cu dissimilar welded joints via electromagnetic pulse welding (EMPW). The load-bearing capacity of the joints at discharge voltages of 14 kV and 16 kV was superior to that of 12 kV. Meanwhile, the fatigue life of 14 kV joints was one order of magnitude higher than that of 12 kV. The SEM observation on the fatigue fracture surface shows that the typical “tire-mark” fatigue striation just appeared on the 14 kV joint, indicating higher ductility for handling more extended plastic deformation. The high EBSD acquisition was achieved except for the transition zone due to the formation of ultra-fine nanocrystalline Al2Cu phase and amorphous phase, along with many dislocations. Dense low-angle grain boundaries (LAGBs) and refined grains are formed along the bonding interface. This indicates that severe plastic deformation induced dislocations to form the substructure in such an instant (40-60 μs) during the high-velocity collision. The interfacial strength is not only due to the continuous interfacial diffusion layer with a “wave-like” or “inverted hook-like” pattern but also benefits from refined grains along the interface and in the transition zone, as well as the hybrid amorphous-nanocrystalline microstructure, which strengthens the joint through increasing ductility induced by refined grains and regulating amorphous or nanocrystalline phases to affect the balance between strength and ductility of the Al/Cu joint.

In the context of carbon emissions peak, environmental issues highlight the importance of the green economy, how does economic agglomeration release growth potential and enable the coordinated development of the economy and environment? There are few works of literature to analyze it within the framework of spatial economy. This paper constructs a theoretical model to clarify the influence mechanism of economic agglomeration on green total factor productivity (GTFP), and then uses a dynamic SDM model to test the theoretical hypothesis. This contribution has three main findings. First, there is a "U-shaped" curve relationship between economic agglomeration and GTFP, and the formation mechanism is that economic agglomeration has a threshold effect on the agglomeration externalities such as infrastructure sharing, knowledge spillover, and labor market upgrading. Second, the mismatch of industrial structure is an important reason that the economic agglomeration in this region has not produced an obvious spatial spillover effect on other regions; Relaxing restrictions on the concentration of economic activity to regional centers would contribute to the improvement of GTFP. Third, GTFP has the classic "snowball effect" in the time dimension, but has the obvious "warning effect" in the space and time dimension. Based on this, this paper believes that at the present stage, it is necessary to adapt to the layout of economic geography, promote the rational allocation of human resources in the territorial space, promote the coordination between economic agglomeration and the development goal of green economy, and at the same time, it is necessary to cultivate the cooperative linkage mechanism of green economy development and transformation among cities.

Face swapping is an intriguing and intricate task in the field of computer vision. Currently, most mainstream face swapping methods employ face recognition models to extract identity features and inject them into the generation process. Nonetheless, such methods often struggle to effectively transfer identity information, result in generated results failing to achieve a high identity similarity with the source face. Furthermore, if we can accurately disentangle identity information, we can achieve controllable face swapping, thereby providing more choices to users. In pursuit of this goal, we propose a new face swapping framework (ControlFace) based on the disentanglement of identity information. We disentangle the structure and texture of the source face, encoding and characterizing them in the form of feature embeddings separately. According to the semantic level of each feature representation, we inject them into the corresponding feature mapper and fuse them adequately in the latent space of StyleGAN. Owing to such disentanglement of structure and texture, we are able to controllablely transfer parts of the identity features. Extensive experiments and comparisons with state-of-the-art face swapping methods demonstrate the superiority of our face swapping framework in terms of transferring identity information, producing high-quality face images and controllable face swapping.

Self-sustained learning (SSL) is considered a crucial factor in promoting students’ long-term learning and development in a sustainable society. To deepen the understanding of SSL, especially in the context of learning English as a second language, the current study examined the influence of intercultural communicative skills, language mindset, and positive L2 self on SSL in English learning among 1,238 college students in China. The results showed that students not only had a strong language mindset, positive L2 self, and intercultural communicative skills but also scored higher in long-term self-sustained English learning. Findings from the Structural Equation Modeling indicated that both language mindset and intercultural communicative skills positively predicted positive L2 self and self-sustained English learning. Furthermore, language mindset and intercultural communicative skills had an indirect impact on self-sustained English learning through positive L2 self. These findings suggest that to promote English learners’ SSL, instructors should help facilitate students’ intercultural communicative skills and foster a growth language mindset, as well as positive language learning beliefs.

In recent years, due to the low energy utilization of the whole life-cycle of buildings and the di-minished indoor and outdoor comfort of buildings and the impact on the surrounding environ-ment caused by the carbon emissions of the building life-cycle, the establishment of a whole life- cycle carbon emission model for buildings to improve their energy utilization at all stages of their life-cycle has received unprecedented attention. In China, the construction industry has become a major carbon emitter, and traditional houses, as a green development building type, are an effec-tive way to achieve carbon neutrality in buildings, but the existing green building evaluation system lacks quantitative indicators of carbon emissions in the building life-cycle. The exclusive evaluation indexes for regional and characteristic buildings, such as traditional houses, are ne-glected; This study explored the formula for calculating the life-cycle carbon emissions model of traditional residential houses under a carbon emission intervention and used real measurements of the physical environment and comparative analysis of the limitations of existing local stand-ards; The results showed that the carbon emission calculation formulas for each stage of the life-cycle of traditional residential houses must be established by combining the selection of local building materials, and the materials for sustainable energy and carbon sinks of green systems. Based on the results of indoor and outdoor heat and humidity environmental tests of residential houses and an analysis of the limitations of existing evaluation indexes due to locality, four im-portant factors affecting locality green buildings in terms of energy utilization, site ecology and landscape, land saving and material saving were extracted; on this basis, the whole life-cycle carbon emission model of traditional residential houses is constructed by combining the existing green building evaluation standards with the carbon emission indexes of the life-cycle of tradi-tional residential houses.

Based on research data from the renovation of old residential areas in Chengdu, China, this study provides empirical evidence regarding the causal relationship between urban renewal and the transformation of residents' pro-environmental behaviors. The research findings demonstrate a significant enhancement in residents' engagement in pro-environmental behaviors due to the renovation of old residential areas. Robustness tests based on replacement samples and two-stage difference-in-difference models also confirm the reliability of the conclusions. The preliminary mechanism test indicates that the mechanism of the impact of renovation of old residential areas on the transformation of residents' pro-environmental behaviors can be attributed to two main factors. Firstly, the improvement of environmental infrastructure provides residents with better conditions for participating in pro-environmental activities. Secondly, there is an elevation in residents' environmental protection awareness, prompting a more voluntary engagement in pro-environmental behavior. This study suggests that decision-makers should fully recognize that urban renewal activities nationwide are not only a process of improving urban hardware and functionality, but also a realistic and vivid "environmental education" course for the whole nation. Taking urban renewal as an opportunity to enhance citizens' awareness of environmental protection will effectively promote the transformation of pro-environmental behaviors among residents.

This paper introduces a method for tunnel point cloud and BIM model integration and cross-section monitoring, providing information to analyse tunnel cross-sections and surrounding rock deformation, and support for tunnel maintenance and reconstruction. Three types of data are processed for the integration: laser scanning point cloud, BIM tunnel model and terrain model from oblique photogrammetry. An adaptive BIM modelling scheme is proposed for tunnels with alien structures. Precise spatial registration of the data sets is conducted by applying singular value decomposition (SVD) algorithm to calculate transformation parameters from the point cloud model to the BIM model. Since the tunnel central line has high-order derivability, a cross-section calculation method based on tangent vector is proposed to obtain the cross-sectional profile of tunnels at any mileage. The proposed method has been verified by applying it to a tunnel reconstruction project. The experiment results show that the tunnel point cloud and the BIM model were highly coincident after the integration. The developed program can effectively get the cross-section of the tunnel at any mileage, and correctly express the spatial relationship between the BIM tunnel, the point cloud of tunnel and the external mountainous terrain.

The real-time Railway Traffic Management Problem (rtRTMP) is discussed in the field of railway transportation. In this paper, rtRTMP is considered for planning shunting routes based on the use of routing methods on a spatial-temporal graph. An approach and algorithm of Spatial-Temporal Graph formation for rail yard transportation network is proposed. The idea is to construct an undirected loop-free Double Vertex Graph for determining optimal shunting routes consisting of several half-runs for several trains shunting under draw-out tracks capacity constraints. Experimental results on the rail yard simulation model are presented.

Although deep learning has received extensive attention and achieved excellent performances in various of scenarios, it suffers from adversarial examples to some extent. Especially, physical attack poses more threats than digital attack. However, existing researches pay less attention to physical attack of object detection in remote sensing images (RSIs). In this work, we systematically analyze the universal adversarial patch attack for multi-scale objects in the remote sensing field. There are two challenges for adversarial attack in RSIs. On one hand, the number of objects in remote sensing images is more than that of natural images. Therefore, it is difficult for adversarial patch to show adversarial effect on all objects when attacking a detector of RSIs. On the other hand, the wide range of height of photography platform causes that the size of objects diverse a lot, which brings challenges for generating universal adversarial perturbation for multi-scale objects. To this end, we propose an adversarial attack method on object detection for remote sensing data. One of the key ideas of the proposed method is the novel optimization of adversarial patch. We aim to attack as many objects as possible by formulating a joint optimization problem. Besides, we raise a scale factor to generate a universal adversarial patch that adapts to multi-scale objects, which ensures the adversarial patch is valid for multi-scale objects in the real world. Extensive experiments demonstrate the superiority of our method against state-of-the-art methods on YOLO-v3 and YOLO-v5. In addition, we also validate the effectiveness of our method in real-world applications.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

Estimating Visual Quality of Street Space (VQoSS) is pivotal for urban design, environmental sustainability, civic engagement, etc. Recent advancements, notably in deep learning, have enabled large-scale analysis. However, traditional deep learning approaches are hampered by extensive data annotation requirements and limited adaptability across diverse VQoSS tasks. Multimodal Large Language Models (MLLMs) have recently demonstrated proficiency in various computer vision tasks, positioning them as promising tools for automated VQoSS assessment. In this paper, we pioneer the application of MLLMs to VQoSS change estimation, with our empirical findings affirming their effectiveness. In addition, we introduce Street Quality GPT (SQ-GPT), a model that distills knowledge from the current most powerful but inaccessible (not free) GPT-4, requiring no human efforts. SQ-GPT approaches GPT-4’s performance and is viable for large-scale VQoSS change estimation. In a case study of Nanjin, we showcase the practicality of SQ-GPT and knowledge distillation pipeline. Our work promises to be a valuable asset for future urban studies research.

Neptunea cumingii is an economically important marine shellfish found in the Yellow Sea and Bohai Sea areas of China. However, due to environmental factors, such as global warming, Neptunea cumingii resources are in decline along the coast of China. In this study, samples of Neptunea cumingii were collected in Zhangzidao and Yantai during spring, summer， autumn, and winter to clarify the gene expression patterns and regulatory mechanisms in the gills in different seasons. Transcriptome analysis was conducted using Neptunea cumingii gill tissues and genes with significantly different expression levels were extracted for functional verification. The most genes with differences in expression（DEGs） were found in comparisons of the winter and summer samples. Gene enrichment analysis based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes terms showed that these DEGs were mainly involved in immune and metabolic pathways, and they had significant effects on oxidative stress, body metabolism, and protein synthesis in Neptunea cumingii. Further screening of DEGs identified 34 genes related to temperature regulation comprising 13 genes with roles in innate immunity in shellfish, 12 genes related to oxidative stress, and nine genes related to protein synthesis and energy metabolism. Eleven DEGs were randomly selected for qPCR verification and the results were consistent with the transcriptome analysis results. In summary, the transcriptome results differed significantly between seasons in the gill tissues of Neptunea cumingii. The expression levels of immune regulatory genes could be promoted in Neptunea cumingii during the high temperature season, whereas the expression of these genes may be inhibited in the low temperature season. The results obtained in this study provide insights into the molecular defense mechanisms that might allow Neptunea cumingii to adapt to climate change.

A low-profile broadband dual-polarized antenna is investigated for base station applications. It consists of two orthogonal dipoles, fork-shaped feeding lines, an artificial magnetic conductor (AMC), and parasitic strips. By utilizing the dispersion Brillouin diagram, the AMC is designed as the antenna reflector. It has a wide in-phase reflection bandwidth of 54.7% (1.54-2.70 GHz) and a surface wave bound range of 0-2.65 GHz. This design effectively reduces the antenna profile by over 50% compared to traditional antennas without an AMC. For demonstration, a prototype is fabricated for 2G/3G/LTE base station applications. Good agreement between simulations and measurements is observed. The measured -10-dB impedance bandwidth of our antenna is 55.4% (1.58 –2.79 GHz), with a stable gain of 9.5 dBi and high isolation of more than 30 dB across the impedance passband. As a result, this antenna is an excellent candidate for miniaturized base station antenna applications.

Wool quality and yield are important economic traits of livestock. In this study, the skin tissues of the upper scapula of Super Merino sheep (SM) and Small-Tailed Han sheep (STH) during the growing period were studied. Differentially expressed (DE) long non-coding RNAs (lncRNAs) and messenger RNAs (mRNA) were identified via histopathological observation and high-throughput RNA sequencing. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze differentially expressed genes. Reverse transcription quantitative Polymerase Chain Reaction (RT-qPCR) was used to verify nine selected DE lncRNAs and five DE mRNAs. Significant differences were found in the expression levels of LOC114113396 (KRTAP15-1), CRABP1, KRT10, KRTAP1-3, KRTAP4.3, KRT2, FGF1, IGF-1, and KIT in SM and STH skin tissues. These results indicate that these mRNAs may play an important role in the growth and development of hair follicles and the regulation of hair fiber traits. Differentially expressed lncRNA target genes and mRNAs were mainly enriched in biological processes and pathways related to skin development and fiber traits, which is consistent with previous studies. LncRNA MSTRG.9225.1, MSTRG.124320.1, MSTRG.96951.1, MSTRG.91685.1, MSTRG.122229.1, MSTRG.89255.1, MSTRG.98769.1, and MSTRG.84658.1 may indirectly participate in the growth and development of sheep hair follicles and the regulation of hair fiber diameter by regulating the expression of their respective target genes. These candidate lncRNAs and mRNAs may provide a basis for the study of sheep hair follicle growth and development and hair fiber traits.

In this paper, we consider a make-to-order supply chain which satisfies demand that is dependent on both price and quoted lead -time. The manufacturer chooses the lead -time and the order quantity, and the retailer sets the revenue shares. The interactions between the manufacturer and the retailer are modelled as a Nash Game, and the existence and uniqueness of pure strategy equilibrium are demonstrated. A mechanism that enables the supply chain to coordinate the decisions of the members is developed. Lastly, we also analyze how the supply chain system parameters impact the optimal supply chain decisions and the supply chain performance.

In view of the complexity of the pile foundation underpinning structure system and the stringent requirements of the construction process, this paper briefly describes the necessity of introducing epoxy resin reinforcing adhesive of planting rebar in the design of pile foundation underpinning beam structure to im-prove the mechanical properties of the underpinning beam new and old concrete joint surfaces and proposes a new type of pile foundation underpinning beam system construction method by “chiseling + prestressed reinforcement + epoxy resin reinforcing adhesive”. This paper uses an actual pile foundation underpinning project of an urban overpass as a prototype, designs and creates a model structure with a similarity ratio of 1/6, and performs repeated pro-gressive static loading tests to study the load carrying capacity, displacement change, and other properties of the underpinning structure, as well as analyses and distorts the overall working performance and failure mode of them. On this basis, the prototype structure's finite element analysis model was built, and the finite element analysis results were compared with the test results to get the mechanical properties and deformation characters of the actual pile foundation under-pinning structure system corresponding to the actual underpinning beam load. This paper's study can lay the theoretical and experimental foundation for the smooth development of similar projects.

The study of the area model of Pinus tabulaeformis forest provides an important reference for improving the management of Pinus tabulaeformis and revealing the growth law of Pinus tabulaeformis. According to the classification method proposed by Munro, stand growth and harvest prediction models are divided into three categories: full stand model, single wood model and diameter distribution model. Based on the fixed sample data of Shangluo Pinus tabulaeformis, the spatial instead of time method is used to process the data, and the weight coefficient of each model in the combined prediction model is calculated by using the optimal weighting method. The single wood model, the whole forest model and the diameter distribution model are combined by the combined prediction method to integrate the fault area prediction of Pinus tabulaeformis forest. The results show that the combined prediction method is more accurate than the single model (single wood model, whole forest model and diameter distribution model). At the same time, the method can improve the compatibility of the forest break area prediction model, ensure the consistency of the forest break area prediction, and provide a new direction for the research of forest resource monitoring and investigation.

Background: Developing patient-centric baseline standards that enable the detection of clinically significant outlier gene products on a genome-scale remains an unaddressed challenge required for advancing personalized medicine beyond the small pools of subjects implied by “precision medicine”. This manuscript proposes a novel approach for reference standard development to evaluate the accuracy of single-subject analyses of metabolomes, proteomes, or transcriptomes. Since distributional assumptions of statistical testing may inadequately model genome dynamics of gene products, the so-called significant results of previous studies may artefactually conflate with real signals. Model confirmation biases escalate when studies use the same analytical methods in the discovery sets and reference standards, as corroboration of results leads to an evaluation of reproducibility confounded with replicated biases rather than a measure of accuracy. We hypothesized that developing method-agnostic reference standards using effect-size and expression-level filtering of results, obtained from multiple discovery methods that are distinct from the one evaluated, would maximize the evaluation of clinical-transcriptomic signals and minimize statistical artefactual biases. We developed and released an R package “referenceNof1” to facilitate the construction of robust reference standards. Results: Since RNA-Seq data analysis methods often rely on binomial and negative binomial assumptions to non-parametric analyses, the differences create statistical noise and make the reference standards method dependent. In our experimental design, the accuracy of 30 distinct combinations of fold changes (FC) and expression levels (EL) were determined for five types of RNA analyses in two different datasets. This design was applied to two distinct datasets: breast cancer cell lines and a yeast study with isogenic biological replicates in two experimental conditions. In addition, the reference standard (RS) comprised all RNA analytical methods with the exception of the method testing accuracy. To mitigate for biased optimization of the RS parameters towards a specific analytical method, similarity between observed results of distinct analytical methods were calculated across all methods (Jaccard Concordance Index). The greatest differences were observed across diametric extremes. For example, filtering out differentially expressed genes (DEGs) using a fold change < 1.2 leads to a 50% increase in concordance between techniques when compared to results with FC > 1.2. Combining this FC cutoff with genes with mean expressions > 30 counts leads to a 65% increase in concordance in comparison to genes with expression levels < 30 counts and with FC < 1.2. Conclusions: We have demonstrated that comparing accuracies of different single-subject analysis methods for clinical optimization requires a new evaluation framework. Reliable and robust reference standards, independent of the evaluated method, can be obtained under a limited number of parameter combinations: fold change (FC) ranges thresholds, expression level cutoffs, and exclusion of the tested method from the RS development process. When applying anticonservative reference standard frameworks (e.g., using the same method for RS development and for prediction), a majority of the concordant signal between prediction and Gold Standard (GS) cannot be confirmed by other methods, which we conclude as biased results. Statistical tests to determine DEGs from a single-subject study generate many biased results that require subsequent filtering for increasing their reliability. Conventional single-subject studies pertain to one or a few measures in one patient over time [1]and need a substantial conceptual framework extension in order to address the tens of thousands of measures in genome-wide analyses of gene products. The proposed referenceNof1 framework addresses some of the inherent challenges in improving transcriptome scale single-subject analyses by providing a robust approach to constructing reference standards. Github: https://github.com/SamirRachidZaim/referenceNof1

Reverse water gas shift reaction (RWGS) is an important process which plays a vital role in many CO2 utilization related reactions. Noble metals are the most active catalysts in RWGS, but the high price and low reserve strangled their applications. In the present work, we reported a non-transition-metal MgAl2O4 catalyst which showed outstanding activity and stability at high temperatures in the RWGS reaction and improved performance after doping of single atomic Nin+. The catalyst can obtain 46% of CO2 conversion in durability test of 75 h at 800 °C under high weight hourly space velocities (225 000 ml g-1 h-1). The adsorption sites, possible reaction route, and effects of Nin+ single atoms on the (111) surface of MgAl2O4 for RWGS were investigated by in situ DRIFTS and DFT calculations. The results indicated that the rate determining reaction step of RWGS on MgAl2O4 and Ni (SA)/MgAl2O4 were both the reaction of OH* + H* → H2O* + *, but the energy barrier was significantly reduced after introducing single atomic Nin+. Nin+ atoms can increase the hydroxyl coverage on the surface of catalyst and Al3+ sites near the Nin+ ion are considered as the predominant active sites for RWGS reactions.

Three dimension (3D) Multi-input-multi-output (MIMO) scheme, which exploits another dimension of the spatial resource, is one of the enabling technologies for the next generation mobile communication. As the elevation angle in 3D-MIMO channel model might varies against the height of the base station transmit antenna, it has to be taken into account carefully. In this paper, the impact of antenna height on the channel characteristics of 3D MIMO channel is investigated by using the intelligent ray launching algorithm (IRLA). Three typical street scenarios, i.e., the straight street, the fork road and the cross road, are selected as benchmarks. On the basis of simulations, joint and marginal probability density functions (PDFs) of both the elevation angle of departure (EAoD) and the elevation angle of arrival (EAoA) are obtained. The elevation angle spread (AS) and the delay spread (DS) under various antenna heights are also discussed. Simulation results indicate that the PDFs of EAoD and EAoA vary characteristics under different street scenarios. Moreover, the minimum value of the DS can be achieved when the antenna height is half of the building height.

Cymbidium faberi Rolfe is one of the traditional Chinese orchids with important ornamental value, and the cultivation of Cymbidium faberi Rolfe mutant strains with different appearances is essential to increase its economic value, but at present, the acquisition of Cymbidium faberi Rolfe mutant strains basically relies on natural mutation.The objectives of this research were to mutagenize Cymbidium faberi Rolfe protocorm-like bodies (PLBs) and shoots in vitro using sodium azide (NaN3), and to screen and evaluate mutants in mutagenized Cymbidium faberi Rolfe seedlings using morphological characteristics.Cymbidium faberi Rolfe PLBs and shoots were used as mutagenic materials, and co-cultivated in induced shoots growth medium with the addition of 0.0 (control), 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 mg/L and 0.0 (control), 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, and 10.0 mg/L NaN3 to induce the mutations, and the mortality rates of the PLBs and shoots were increased with the increase of the NaN3 concentration.At 14 d of co-cultivation, PLBs and shoots were most efficiently mutagenized with 1.5 mg/L and 4.0 mg/L NaN3, respectively.After the explants were cultured for 3 months, changes in leaf and flower morphology were observed in some mutants: shorter and thicker leaves, shorter node length, reduced height, and mid-translucent leaves compared with controls; and some Cymbidium faberi Rolfe bloomed prematurely, with single flowers with large, thick petal sepals and small inflorescences, and colours include light green throughout, and a few with purple stamens.This suggests that NaN3 can effectively mutagenise Cymbidium faberi Rolfe PLBs and shoots to satisfy people's demand for Cymbidium faberi Rolfe's ornamental properties while increasing its economic value.

This paper proposes an active-reactive power collaborative scheduling model with cluster division for the flexible distributed energy resources (DERs) of smart building system to resolve the high complexity of centralized optimal scheduling of massive dispersed DERs in the distribution network. Specifically, the optimization objective of each cluster is to minimize the operational cost, the power loss cost, and penalty cost for the flexibility deficiency, and the second-order cone-based branch flow method is utilized to convert the power flow equations into the linearized cone constraints, reducing the nonlinearity and heavy computation burden of the scheduling model. Customized virtual battery models for the building-integrated flexible DERs are developed to aggregate the power characteristics of flexible resources while quantifying their regulation capacities with time-shifting power and energy boundaries. Moreover, a cluster division algorithm considering the module degree index based on the electrical distance and flexible balance contribution index is formulated for cluster division to achieve the information exchange and energy interaction in the distribution network with high proportion of building-integrated flexible DERs. Comparative studies have demonstrated the superior performance of the proposed methodology on the economic merits and voltage regulation.

Novel 1,2,3-triazole compounds 3–4 were synthesised via the regioselective addition and cyclization reaction of 1,1-enediamines (EDAMs) 1 with p-methylbenzenesulfonyl azide (TsN₃) 2 in 1,4-dioxane at refluxing for 5 hours. As a result, 1,2,3-triazoles 3–4 can be easily and efficiently obtained via catalyst-free click chemistry. The reactions have some advantages such as metal-free catalyst, excellent yield, inexpensive raw materials, and convenient final treatment.

Land cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spatial resolution on land cover classification. Since it is difficult to obtain multiple spatial resolution remote sensing images of the same area at the same time, the main current method to study the scale effect of land cover classification is to use the same image resampled to different resolutions, however errors in the resampling process lead to uncertainty in the accuracy of land cover classification. To study the land cover classification scale effect of different spatial resolutions of multi-source remote sensing data, we selected 1 m and 4 m of GF-2, 6 m of SPOT-6, 10 m of Sentinel-2 and 30 m of Landsat-8 multi-sensor data, and explored the scale effect of image spatial resolution on land cover classification from two aspects of mixed image element decomposition and spatial heterogeneity. For the study area, we compared the classification obtained from GF-2, SPOT-6, Sentinel-2, and Landsat-8 images at different spatial resolutions based on GBDT and RF. The results show that (1) GF-2 and SPOT-6 had the best classification results, and the optimal scale based on this classification accuracy was 4–6 m; (2) the optimal scale based on linear decomposition depended on the study area; (3) the optimal scale of land cover was related to spatial heterogeneity, i.e., the more fragmented and complex was the space, the smaller the scale needed; and (4) the resampled images were not sensitive to scale and increase the uncertainty of the classification. These findings have implications for land cover classification and optimal scale selection, scale effects and landscape ecology uncertainty studies.

Mouse embryonic stem cells (mESCs) possess remarkable characteristics of unlimited self-renewal and pluripotency, which render them highly valuable for both fundamental research and clinical applications. A comprehensive understanding of the molecular mechanisms underlying mESC function is of utmost importance. The Human Silence Hub (HUSH) complex, comprising FAM208A, MPP8, and periphilin, constitutes an epigenetic silencing complex involved in suppressing retroviruses and transposons during early embryonic development. However, its precise role in regulating mESC pluripotency and differentiation remains elusive. In this study, we generated homogenous miniIAA7 tagged Mpp8 mouse ES cell lines. Upon induction of MPP8 protein degradation, we observed impaired proliferation and reduced colony formation ability of mESCs. Furthermore, this study unveils the involvement of MPP8 in regulating the activity of the LIF/STAT3 signaling pathway and Nanog expression in mESCs. Finally, we provide compelling evidence that degradation of the MPP8 protein impairs the differentiation of mESC.

Complete digraphs are referred to in the combinatorics literature as tournaments. We consider a family of semi-simplicial complexes, that we refer to as ``tournaplexes'', whose simplices are tournaments. In particular, given a digraph G, we associate with it a ``flag tournaplex'' which is a tournaplex containing the directed flag complex of G, but also the geometric realisation of cliques that are not directed. We define several types of filtrations on tournaplexes, and exploiting persistent homology, we observe that flag tournaplexes provide finer means of distinguishing graph dynamics than the directed flag complex. We then demonstrate the power of these ideas by applying them to graph data arising from the Blue Brain Project's digital reconstruction of a rat's neocortex.

Detecting, especially locating local degradations at an incipient stage, is very important for mission-critical high voltage rotating machines. One particular challenge of the existing testing techniques is that the characteristic of a local incipient defect is not prominent due to various factors such as averaging with the healthy remainder, attenuation in signal propagation, interference, and varied operating conditions. This paper proposes and investigates the frequency domain reflectometry (FDR) technique based on scattering parameter measurement. The FDR result presents the object length, wave impedance, and reflections due to impedance discontinuity along the measured windings. Experiments were performed on two commercial coils with artificially made defects. These defects include turn-to-turn short, surface creepage, loose coils, and local overheating, which are commonly seen in practice. Two practical water pumps in the field were also selected for investigation. The study outcome shows that the FDR can identify and locate both structure and insulation degradations of both shielded and unshielded objects with good sensitivity. This makes the FDR a comprehensive tool for fault diagnosis and aging assessment.

We performed a retrospective, observational study for 51 eyes of 51 treatment-naive patients with polypoidal choroidal vasculopathy (PCV), whose lesion ranged within the 6x6mm scope of optical coherence tomography angiography (OCTA). Patients were divided into two groups based on the pattern of branching vascular network (BVN) on OCTA: ill-defined group and well-defined group. BVN morphology was not related to baseline best-corrected visual acuity (BCVA). But the BCVA in the ill-defined BVN group (-0.18 [interquartile range: -0.40 to 0.00]) was significantly improved after anti-vascular endothelial growth factor (VEGF) injections, compared with that (0.00 [interquartile range: -0.18 to 0.00]) in the well-defined group (z=2.143, p=0.032). Multiple logistic regression analysis showed that male sex, smaller number of injections, and presence of polypoidal lesions on OCTA images at baseline predicted a poor prognosis of polypoidal lesions on OCTA images after anti-VEGF therapy (all p&lt;0.05). Finally, BCVA at baseline and the number of injections were protective factors for BCVA after anti-VEGF therapy (all p&lt;0.05). In contrast, history of hypertension and macular edema at baseline were risk factors for BCVA after anti-VEGF injections (all p&lt;0.05). Our results revealed the visual and morphological prognosis of patients with active subfoveal circumscribed PCV after anti-VEGF therapy.

The papaya mealybug Paracoccus marginatus is an invasive, polyphagous pest and poses a quarantine threat to tropical and subtropical countries. Infested commodity internationally should be undergoing phytosanitary treatment, while irradiation is recommended to replace methyl bromide fumigation. Dose-response tests were conducted on the 2-, 4-, and 6-d-old eggs and gravid females of P. marginatus using the X-ray radiation doses of 15–105 Gy with an interval of 15 Gy, respectively. Radiotolerance was compared using fiducial overlapping and lethal dose ratio (LDR) test, resulting in insignificant difference except for LDR test at LD90 (leading 90% mortality at 95% confidence level (CL)); the estimated dose for 99.9968% mortality at 95% CL was 176.5–185.2 Gy, which was validated in the confirmatory tests using gamma irradiation because gammy and X-rays have equal biological effect on pests. Therefore, a total of estimating 60,386 gravid females of papaya mealybug irradiated with 146.8–185.0 Gy resulted in no F1 nymphs developing. Eggs can therefore be used as an alternative to gravid females for dose-response tests; the recommended minimum dose for phytosanitary treatment of P. marginatus on infested commodity is 185 Gy, with treatment efficacy ≥ 99.9950% at 95% CL.

Intense thermoacoustic oscillations may lead to severe deterioration due to the induced intolerable damage to combustors. A better understanding of unstable behaviors is important to prevent or suppress these oscillations. Active thermoacoustic coupling in practical combustors is caused primarily by two approaches: inherent turbulent fluctuations and the flame response to acoustic waves. Turbulent fluctuations are generally characterized by random noise. This paper experimentally expands on previous analytic studies regarding the influence of colored disturbances on the thermoacoustic response near the supercritical bifurcation point. Therein, a laboratory-scale Rijke-type thermoacoustic system is established, and both supercritical and subcritical bifurcations are observed. Then, Ornstein–Uhlenbeck (OU)-type external colored noise is introduced near the supercritical bifurcation point, and the effects of the corresponding correlation time τc and noise intensity D are studied. The experimental results show that these variables of the colored noise significantly influence the dynamics of thermoacoustic oscillations in terms of the most probable amplitude, autocorrelation, and correlation time. A resonance-like behavior is observed as the noise intensity or the autocorrelation time of the colored noise is continuously varied, which means that the coherent resonance occurs in the thermoacoustic system. Finally, when the system is configured closer to the stability boundary, the extent of the coherence motion is intensified in the stochastic system response. Meanwhile, the Signal to Noise Ratios (SNRs) of the colored-noise-induced response are found to become more distinguished, the optimal colored noise intensity decreases, and the optimal autocorrelation time increases. This provides valuable guidance to predict the onset of thermoacoustic instabilities.

A challenge in building large-scale superconducting quantum processors is the precise control and manipulation of the qubit state. However, the crosstalk between the microwave control lines impedes the parallel execution of high-fidelity digital and analog quantum operations. Here, we propose and demonstrate a universal compensation protocol for calibrating the microwave signal crosstalk. We also introduce amplified error sequences to optimize the accuracy. Furthermore, we show a definitive improvement in parallel gate operations with crosstalk cancellation, demonstrating the technique's effectiveness. This work paves the way for superconducting hardware that features automated calibration of microwave crosstalk, leading to enhanced fidelities in multiqubit circuits.

In this paper, an ultracompact combined sensor for displacement and angle synchronous measurement is proposed based on self-imaging effect of optical microgratings. Using a two-grating structure, linear and angular displacement can be measured by detecting the change of phase and amplitude of the optical transmission respectively within one single structure in meantime. The optical transmitted properties of the two-grating structure are investigated in both theory and simulation. Simulated results indicate that, the optical transmission changes in a sinusoidal relationship to the input linear displacement. Meanwhile, the amplitude of the curve decreases with an input pitch angle, indicating the ability for synchronous measurement within one single compact structure. The synchronous measurement of the linear displacement and the angle is also demonstrated experimentally. The results show a resolution down to 4nm for linear displacement measurement, and a sensitivity of 0.26mV/arcsec within a range of ±1° for angle measurement. Benefitting from a simple common-path structure without using optical components including reflectors and polarizers, the sensor shows an ultrahigh compactness for multiple-degrees-of-freedom measuring, indicating the great potential for this sensor in the fields such as integrated mechanical positioning and semiconductor fabrication.

Supplemental light is widely applied in greenhouses for promotions of the product and flavors of strawberries in global markets. Present selections of colored lights are, however, quite empirical or qualitative, from the aspect of photometry or colorimetry. The accurate control of chromatic parameters of supplemental light and their chromatic influences on fruit quality has been under-studied. In this study, color parameters including correlated color temperatures (CCTs) and illuminance of supplement lights are precisely controlled using a digitally color-coding method. We systematically investigate the chromatic effect of supplemental light on five parameters of strawberries: plant height, single weight, fruit hardness, soluble solids, and titratable acids. Results show that the supplement light generally lowers down the single weight and the fruit hardness, increases the plant height, the contents of soluble solids and titratable acids. The chromatic dependences for the five parameters are different and might be strengthened, weakened, or shifted by light illuminance. We demonstrate the beneficial roles of supplemental light in accelerating the maturation and enhancing the flavor of strawberries in greenhouses cultivation. The results pro-vide valuable guidance for the effective cultivation of strawberries. Moreover, the controlling method for accurate colors is ready for the implementation of supplemental lights in other fruits or plants.

The security of several full homomorphic encryption (FHE) schemes depends on the hardness of the approximate common divisor (ACD) problem. The analysis of attack and defense against the system is one of the frontiers of cryptography research. In this paper, the performance of existing algorithms, including orthogonal lattice, simultaneous diophantine approximation, multivariate polynomial and sample pre-processing are reviewed and analyzed for solving the ACD problem. Orthogonal lattice (OL) algorithms are divided into two categories (OL-$\land$ and OL-$\vee$) for the first time. And an improved algorithm of OL-$\vee$ is presented to solve the GACD problem. This new algorithm works well in polynomial time if the parameter satisfies certain conditions. Compared with Ding and Tao's OL algorithm, the lattice reduction algorithm is used only once, and when the error vector $\mathbf{r}$ is recovered in Ding et al.'s OL algorithm, the possible difference between the restored and the true value of $p$ is given. It is helpful to expand the scope of OL attacks.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

In this paper we investigate in different scenarios the feasibility of using massive multiple-input multiple-output (mMIMO) with Reconfigurable Intelligent Surfaces (RISs) to boost the throughput and coverage performances with high energy efficiency, considering sub-6 GHz, mmWave and THz bands. With that objective, a centralized radio access network (C-RAN) suitable for beyond fifth generation (B5G) systems is considered, where we integrate the base stations (BSs) with multiple RISs and devices or user equipment. RISs with a large number of quasi-passive reflecting elements constitute a low-cost approach capable of shaping the radio wave propagation and improve wireless connectivity. We consider a scenario where multiple RISs are combined with mMIMO in the uplink in order to provide connectivity to Smart City (thousands of active low power devices) wirelessly, in the 3.6GHz and 28GHz bands. We also address a scenario where RISs are adopted with mMIMO in the downlink so as to offer connectivity to a Stadium with Pitch, (thousands of active user equipment) in the 28GHz band. Finally, we have also studied the connectivity at 100GHz of a Factory where several RIS panels replacing most of the BSs equipped with mMIMO assure improved throughput and coverage. We concluded that RISs are capable of improving the performance in any of these analyzed scenarios at the different frequency bands, justifying that they are a key enabling technology for 6G.

Abstract:This study aimed to explore the effects of supplementary feeding on milk yield, blood biochemical indexes, milk components, and fecal microflora diversity of Yili horses under grazing condition.18 grazing Yili mare horses with physiological condition consistent were randomly assigned to three groups with six mare horses each. The control group normal grazing, whereas the test group I and II were provided with supplemented with 1 kg/d of concentrate and 1 kg/d of concentrate + 0.4 kg/d coated fatty acids, respectively. After 3 days of pre-feeding, begin the experiment.Horse milk was collected every 7 days, and 10% of the milk yield of each horse was mixed in 100 mL milk sample bottles and stored in -20℃ refrigerator.Which blood samples were collected from the jugular vein before morning feeding (0 h) and at 1,2,3,4,6,9 and 12 h after morning feeding on day 40, and the plasma were centrifuged at 4000 rpm for 15 min and conservation at-20℃. Excrement was collected within 8 h on days 45 and 46 of the test, mixed with 5g of fresh fecal samples in a 5 mL frozen storage tubes and stored in liquid nitrogen. Compared with the control group, the lactation volume of Yili horses in test groups I and II was significantly higher throughout the trial period (P <0.05), and the late test group II was significantly higher than test group I (P <0.05). The yield of milk fat, lactose, and milk protein in test group II was significantly higher than that in test group I and control group (P <0.05); the urea nitrogen content in test group I was significantly lower than the control group (P <0.01). The lauric acid, tetradecanoic acid, cis-11,14,17-eicosotrienic acid, total saturated fatty acid, and total saturated fatty acid/total unsaturated fatty acid in test group II were significantly higher than those in the control group and test group I (P <0.05); The plasma glucose concentration of mares in test group II was significantly higher than that of control group and test group I at 1, 2 and 9 h after feeding (P <0.05), and significantly higher at 4 h after feeding (P <0.05); At 3 h and 6 h after feeding, test group II mares had significantly higher plasma free fatty acids and triglycerides concentrations than the control and test group I (P <0.05), at 4 h after feeding, the plasma triglyceride concentrations were significantly higher than the control and test I groups (P <0.05). Plasma low density lipoprotein and very low density lipoprotein concentrations were significantly higher in mares at 3 h and 9 h after feeding than in control and group I (P <0.05). The total number of OTUs was 3483, and the number of OTUs was 4984,5487, and 5158 in the control and test I and II, respectively. At the phylum level, the total abundance of Bacteroidetes and Firmicutes was more than 75%, and the test group Verrucomicrobia was significantly higher than the control group (P <0.05), and the test group II was significantly higher than the test group I (P <0.05). The Treponema_saccharophilum was significant difference in the feces of the control group (P <0.05); WCHB 1_41, kiritimatiellae, and Verrucomicrobia were significant difference of the test group II (P <0.05) and the fecal flora was mainly related to lipid synthesis, metabolism, and energy metabolism (P <0.05). Supplemental feeding can improve lactation volume of grazing Yili horses, improve the absorption and utilization of fatty acids, and improve the composition and diversity of horse milk and fecal flora to a certain extent.

Pyrethroid pesticides (PYRs) as the third most widely used pesticides, following organophosphorus and carbamate pesticides, which are of significant importance in the analysis and detection of vegetables. However, the current pretreatment technology for PYRs confronts challenges of difficult separation and low enrichment efficiency, resulting in a cumbersome and time-consuming pretreatment process with poor selectivity. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed to simultaneously purify and enrich five PYRs in vegetables, with the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. The COF-SiO2@Fe3O4 was prepared by a simple solvothermal conditions method, using Fe3O4 as magnetic core, benzidine and 3,3,5,5-tetraaldehyde biphenyl as two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on extraction efficiency was investigated to optimize the MSPE conditions, including adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography-mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg-1 (1.00–100 μg·kg-1 for bifenthrin and 2.5–100 μg·kg-1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg-1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg-1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promising prospects for the determination of PYRs in real samples.

a sensorless control scheme based on novel power converging law sliding mode observer is suggested to realize the sensorless control for the permanent magnet synchronous motor (PMSM). Firstly, by introducing a new power converging law, the problem of slow converging speed/large chattering value dilemma in the conventional converging law is solved; Secondly, in view of the shortcomings of the conventional position and speed estimation algorithm, the high-frequency buffeting in the sliding mode observer will be expanded, a phase-locked loop (PLL) velocity and position estimation strategy is adopted to replace it. Finally, through Matlab/Simulink modeling and motor speed regulation platform experimental results, the sensorless position and speed estimation technology proposed in this paper can respond to the starting speed command of 1000 r/min within 0.05 s, and the starting process has no overshoot. When disturbed by 10Nm loading, the speed fluctuation value can be controlled within 1%.

As the problem of light pollution becomes more serious, more and more scholars pay attention to this issue and carry out related research. In the perspective of cities, the measurements of light pollution mainly focus on the brightness of the sky or artificial lighting on the ground. However, there is lack of research on the whole urban space. With the two-dimensional brightness analyses, this paper processes the changes of the light environment of the whole urban space into image quantization. It gets the 3D and 2D light environment changes of luminance distribution, color temperature distribution and chromaticity in the three space layers, the ground layer, the urban canopy layer and the sky layer, from dusk with natural light to night with artificial lighting completely. It is found that the brightness difference between the light environments among the three city levels gradually reduces with the measuring time, and the final values maintain at 0.11~0.25 cd/m². In the ground layer, the light environment is mainly affected by the lighting facilities, and vegetation can prevent the light from scattering up. The light environment of the urban canopy layer is the brightest in the whole city space and has the largest influence on the sky layer. The color concentrates in the range of yellow and red. The color temperature near the ground distributes in 3000K~15000K, and near the sky distributes in 2300K~2700K which is warmer than the natural night sky. The sky brightness of Dalian city is about 951 times than the natural night sky.

Land Surface Temperature (LST) is a basic parameter in energy exchange between the land and atmosphere and is frequently used in many sciences such as climatology, hydrology, agriculture, ecology, etc. LST time series data have usually deficient, missing and unacceptable data caused by the presence of clouds in images, presence of dust in atmosphere and sensor failure. In this study, Singular Spectrum Analysis (SSA) algorithm was used to resolve the problem of missing and outlier data caused by cloud cover. The region studied in the present research included an image frame of MODIS with horizontal number 22 and vertical number 05 (h22v05). This image involved a large part of Iran and Turkmenistan and Caspian Sea. In this study, MODIS LST sensor (MOD11A1) was used during 2015 with 1×1 Km spatial resolution and day/night LST data (daily temporal resolution). The results of the data quality showed that cloud cover caused 36.37% of missing data in the studied time series with 730 day/night LST images. Further, the results of SSA algorithm in reconstruction of LST images indicated the Root Mean Square Error (RMSE) of 2.95 K between the original and reconstructed data in LST time series in the study region. In general, the findings showed that SSA algorithm using spatio-temporal interpolation in LST time series can be effectively used to resolve the problem of missing data caused by cloud cover.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

An algorithm is presented for a micro-model of a mining dump truck movement, which allows determining the optimal speed and acceleration of a vehicle, considering the change of the road grade. The structure of the simulation macro-model of an excavator-and-dump truck complex has been developed. The procedure for integrating a micro-model of a dump truck movement into a simulation model is shown. As a result of a series of experiments with a macro-model, the influence of open pit roads grade on the performance and efficiency of excavator-and-dump truck complexes was established. The necessity of considering in simulation excavator-and-dump truck complexes the speed regulation of dump trucks depending on the change in road grade is shown.

The purpose of this study was to compare the long-term clinical outcomes and quality of life measures for two fixation methods in the setting of displaced femoral neck fractures. The two groups included fixation with multiple cancellous screws (group 1) and telescopic femoral neck screws and small locking plate device (Targon FN) (group 2). Patients underwent reduction and internal fixation with either multiple cancellous screws or Targon FN device from March 2000 to January 2012. Failure endpoints included nonunion, osteonecrosis of the femoral head, and revision surgery. Patient reported outcome measures included chronic pain, ability to ambulate, and the use of ambulation assistive devices. Statistical analysis demonstrated a statistically significant lower rate of non-union and overall complication in the Targon FN group (p value < 0.001 and p value = 0.005 respectively). Logistic regression analysis showed that operative fixation with the Targon FN device decreased the odds ratio for overall complication by a factor of 0.34 (P = 0.02). There were no statistically significant differences between groups 1 and 2 in patient reported outcomes (chronic pain (p-0.21), ability to ambulate (p- 0.07), and the use of ambulation assistive device (p-0.07)). When compared to traditional cancellous screw fixation of femoral neck fractures, the Targon FN device has significantly lower complications rates and equivalent patient reported outcomes.

Type III interferon (IFN-λs) exhibit potent antiviral activity and immunomodulatory effects in specific cells. Nucleotide fragements of bovine ifn-λ (boifn-λ) gene was synthetized after codon optimization. The boifn-λ gene was then amplified by splicing by overlap extension PCR (SOE PCR), resulting in serendipitous acquisition of the mutated boIFN-λ3V18M. Recombinant plasmids pPICZαA-boIFN-λ3/λ3V18M were constructed and the corresponding proteins were expressed in Pichia pastoris with high-level extracellular soluble form. Dominant expression strains of boIFN-λ3/λ3V18M were selected by Western blot and ELISA, cultured on a large scale, and the recombinant proteins purified by ammonium sulphate precipitation and ion exchange chromatography, yielding 1.5g/L and 0.3 g/L, with 85% and 92% purity, respectively. The antiviral activities of boIFN-λ3/λ3V18M exceeded 106 U/mg, were neutralized with IFN-λ3 polyclonal antibodies, were susceptible to trypsin, and retained stability within defined pH and temperature ranges. Furthermore, boIFN-λ3/λ3V18M exerted antiproliferative effects on MDBK cells without cytotoxicity at 104 U/mL. Overall, boIFN-λ3 and boIFN-λ3V18M did not differ substantially in biological activity, except for reduced glycosylation of the latter. Development of boIFN-λ3 and comparative evaluation with the mutant provide theoretical insights into antiviral mechanisms of boIFN-λs and provide material for therapeutic development.

Concrete is more stable than filler as a false roof in a downward approach type infill quarry, but the mechanical model of a concrete false roof is not clear. As a result, there has been limited application. Therefore, it is necessary to establish the mechanical model of a concrete artificial false roof to enhance the stability of the downward approach infill quarry. This paper combines theoretical analysis, model derivation, finite element analysis and field application methods. Firstly, the basic assumptions of thin plate theory and elasticity mechanics are used as the premise to establish the differential equations of the deflection curve of the concrete thin plate false roof. Then, the three types of bending moment generation of the concrete thin plate false roof are explored. Secondly, the relationship between the location of dangerous surface and dangerous point in hard-supported weak-slab structure and soft-supported weak-slab structure is analyzed, and the type of uniform load and calculation model of concrete thin-slab false roof are improved. Finally, according to the established mechanical model of thin slab false roof, finite element analysis and field application were carried out. The results show that there are three types of deflection curve differential equations in the concrete thin slab false roof perpendicular to the strike, and three extreme points exist in the middle section of the thin slab and on both sides of the surrounding rock. The hazardous surface of the hard-supported weak-slab structure is present at the intersection of the encircling rock and the thin-slab fake ceiling, with the perilous point situated on the top of this surface. The hazardous surface of the soft-supported weak-slab structure can be found in the centre section of the thin-slab fake ceiling, with the perilous point being located at the bottom of this surface. Moreover, the damage mode for both structures is that of maximum tensile stress damage. Upon conducting a finite element analysis, the results indicate that the concrete's maximum tensile stress is significantly high.

In this work, nylon 6/ P(N-phenylmaleimide-alt-styrene) blends were prepared by melt blending, and the mechanical, heat-resistant, crystallographic and dynamical mechanical properties of nylon 6/ P(N-phenylmaleimide-alt-styrene) blends with different contents were investigated and analyzed. The results showed that the mechanical properties decreased with increasing PNS, while the heat deflection temperature (HDT), relative crystallinity (Xn), and storage modulus (G’) increased with increasing PNS. The results of differential Scanning Calorimetry (DSC) proved the PNS played the positive role of nucleating PA6. And the results of dynamic mechanical analysis (DMA) proved the PNS could improve the rigidity of PA6/PNS blends. From the SEM, these PNS domains were between 0.2 and 4 μm in diameter. The experimental results indicated that the addition of PNS improved the rigidity of PA6/PNS blends, and then improved the heat-resistant property.

Asian dust (AD) events and total suspended particle (TSP) was observed at Kanazawa University Wajima Air Monitoring Station (KUWAMS), a Japanese background site, during the East Asian winter monsoon periods (from November to May of the following year) from 2010 to 2021. Nine kinds of polycyclic aromatic hydrocarbons (PAHs) were determined in each TSP sample. In this study, a total of 54 AD events were observed. According to the different pathways of long-range transportation, AD events were divided into AD-high (transported at higher altitude, around 4000 m) and AD-low (transported at lower altitude, around 2500 m). The TSP concentrations in-creased sharply in the AD and was higher in AD-high (39.8 ± 19.5 μg/m³) than that in AD-low (23.5 ± 10.5 μg/m³). While AD didn’t have significant effect on ΣPAHs characteristic variation, as ΣPAHs concentration in non-AD periods, AD-high, AD-low were 543 ± 374, 404 ± 221, 436 ± 265 pg/m³, respectively. PAHs compositions were also consistent. As a result, TSP concentration was affected by the input air mass transported at higher altitude from the desert region while PAHs concentration was under the impact of air mass at lower altitude which carried the PAHs emitted from fossil fuels and biomass combustion in northeastern China. Moreover, the health risks of PAHs were calculated by inhalation lifetime cancer risk which ranged from 10−6 to 10−5 ng/m3, in-dicating a potential carcinogenic risk at KUWAMS during the East Asian winter monsoon period.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

Background: Hepatocellular carcinoma (HCC) is one of most common cancers with a high mortality rate. HBV/HCV infection is an important risk factor to trigger HCC. Therefore, developing serum biomarkers for early diagnosis is crucial to prolong survival in HCC patients. Methods: An antibody array technology was utilized to detect serum from 20 HBV-related HCC patients, 20 chronic hepatitis B patients and 20 normal population, whose results were further validated by ELISA. Results: Both antibody array and ELISA showed that ten growth factors (SCF R, GDF-15, HGF, FGF-4, IGFBP-1, PIGF, GH, GDNF, BDNF and IGF-1) were significantly differential in HCC patients when compared to the non-HCC population. Among these growth factors, the levels of SCF R, GDF-15, HGF, GH and IGF-1 showed significant correlation with hepatitis B and its severity, indicating that these growth factors may promote HCC progression by an HBV-specific mechanism. A therapy targeting these growth factors in hepatitis B patients may help to prevent the development of HCC. FGF4 and GH were found, for the first time, to be upregulated in HCC, suggesting that these two growth factors may serve as novel serum biomarkers for the early diagnosis of HCC. Conclusion: The combined detection of all the differential growth factors may improve the diagnostic accuracy of HCC.

Non-destructive, accurate, and timely approach for crop yield prediction at field scale is vital for precision agriculture. This study aimed to investigate the appropriate wavelengths and their combinations to explore the new SIs derived from UAV hyperspectral images in predicting yield during the growing season of spring maize. The best wavelengths and new SIs, including the difference spectral index, ratio spectral index, and normalized difference spectral index forms, were obtained by the contour maps constructed by the coefficient of determination (R2) from the linear regression models between the yield and all possible SIs screening out from the 450-950 nm wavelengths. The results showed that the most sensitive wavelengths were 640-714 nm at WJQ, 450-650 nm and 750-950 nm at SKS, and 450-700 nm and 750-950 nm at FJJ. The new SIs established here were different across the three experimental fields, and their performance on maize yield prediction were generally better than that of the published SIs. In addition, the new SIs presented different response to various N fertilization levels. This study demonstrated the potential of exploring new spectral characteristics from remote sensing technology for predicting field-scale crop yield in spring maize cropping systems before harvest.

Currently, in some domestic and foreign mines, the backfill drilling pipeline experience a rupture phenomenon even when the wear degree is low. This results in a delay in production due to the filling becoming 'sick'. This paper presents, for the first time, the damage mechanism from a mechanical perspective and re-derives the anti-extrusion strength model of the backfill drilling pipeline. We investigate the influence of law on the anti-extrusion strength of pipelines from the perspective of stratum and cement ring. We then verify the theoretical and simulation results through engineering examples. The results demonstrate that the Mises stress criterion is a suitable modification principle for the anti-extrusion strength model of the backfill drilling pipeline. The anti-extrusion strength of the pipeline is related to the elastic modulus and Poisson's ratio of the stratum, and the thickness of the cement ring. It is negatively affected by the depth of the stratum. For hard strata, a cement ring with a smaller elastic modulus is suitable, while for soft stratum, a cement ring with a larger elastic modulus is recommended. When the missing angle of the cement ring is less than 60°, the stress concentration factor increases up to 2.2. The stress unloading capacity of the cement ring ranges from 32.7% to 37.8%, and optimal performance of the cement ring is achieved when it has high strength and low rigidity. The backfill filling pipeline of a copper mine abroad was destroyed due to external extrusion force exceeding its anti-extrusion strength value. The modified pipeline anti-extrusion strength model is 18.2% higher than the casing API strength value. This finding can inform the design of the backfill filling pipeline for China's kilometer-deep wells in the future.

To facilitate the computation of the uniaxial compressive strength value of the cemented paste backfill under the condition of high sand-cement ratio, and to analyze the size effect of the cemented paste backfill with high sand-cement ratio under varied aspect ratios, the cemented paste backfill specimens with sand-cement ratios of 8:1-24:1 and aspect ratios of 0.5, 1, and 2 were prepared. Through response surface experiments and finite element analysis, the influence of three aspect ratios on the cemented paste backfill strength was explored, and the failure characteristics and size effect mechanisms of cemented paste backfill with various aspect ratios were analyzed. The model of strength conversion between cemented paste backfill with different aspect ratios was established. The results show that the compressive strength of the cemented paste backfill decreases with the increase of the aspect ratio under the same mass concentration and sand-cement ratio. When the aspect ratio is 0.5 and 1, the splitting failure is the main factor; when the aspect ratio is 2, the shearing failure is the main factor. The three-dimensional stress caused by the end effect of the cemented paste backfill is the main reason for the high strength when the aspect ratio is 0.5. Due to the one-dimensional stress zone generated in the middle of the cemented paste backfill with an aspect ratio of 2 in the laboratory, its strength value is closer to the actual uniaxial compressive strength value of the cemented paste backfill. The strength values of the cemented paste backfill with aspect ratios of 0.5 and 1 were higher than the actual uniaxial compressive strength values in the laboratory. The rationality of the theoretical analysis was verified by the ABAQUS analysis results. According to the experimental results, a strength conversion model between different aspect ratios is established, which can provide a reference for the design of the uniaxial compressive strength of the cemented paste backfill.

Using the Super-SBM method, this study calculates the carbon emission efficiency (CEE) of 30 provinces in mainland China from 2011 to 2019. Then, using the systematic GMM model, spatial Durbin model, and mediating effect model, it examines the direct effect, spatial effect, and influence mechanism of the digital economy (DE) on CEE. It was found that (1) the DE significantly promoted regional CEE, but had a negative effect on CEE in provinces with high economic correlation; (2) mechanism studies showed that the DE improved CEE by reducing energy intensity, promoting industrial upgrading and green technology innovation; (3) regional heterogeneity analysis found that the DE significantly improved CEE in eastern provinces, but not in central and western provinces. DE improves CEE in provinces with high level of economic development, but decreases CEE in provinces with low level of economic development.This paper provides some empirical and theoretical references for the development of DE to improve CEE.

The retrieval of tree height percentiles with satellite lidar waveforms over the mountainous ar-eas is greatly challenged due to slanted and rugged topographic relief of underlying ground. A novel algorithm is proposed to extract the height percentiles based on the target response waveform (TRW) that is resolved by using a Richardson–Lucy deconvolution algorithm with an adaptive iterative time. The height metrics of the energy percentiles of 25%, 50%, 75% and 95% for the cumulative TRW distribution are determined by their vertical distances relative to the ground elevation in this study. To validate the proposed algorithm, we select the received waveforms of the Global Ecosystem Dynamics Investigation (GEDI) lidar over the Pahvant Mountains of central Utah, USA. The results reveal that the resolved TRWs resemble closely to the actual target response waveforms from the coincident airborne lidar data, with the mean values of the coefficient of correlation, total bias and root mean square error (RMSE) taking val-ue of 0.92, 0.0813 and 0.0016. In addition, the accuracies of the derived height percentiles from the proposed algorithm have been greatly improved compared with the conventional Gaussian de-composition method and the slope-adaptive waveform metrics method. The RMSE values de-crease by the mean values of 1.96 m and 2.72 m, respectively. It demonstrates that the proposed algorithm has good potential in the extraction of forest structure parameter over rugged moun-tainous areas.

The spatiotemporal variability of vegetation in the Middle East was investigated for the period 2001–2019 using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day/500 m composites of the Normalized Difference Vegetation Index (NDVI; MOD13A1). The results reveal a strong increase in the NDVI coverage in the Middle East during the study period (R = 0.75, p-value = 0.05). In Egypt, the annual coverage exhibits the strongest positive trend (R = 0.99, p-value = 0.05). In Turkey, both the vegetation coverage and density increased from 2001 to 2019, which can be attributed to the construction of some of the biggest dams in the Middle East, such as the Atatürk and Ilisu dams. Significant increases in the annual coverage and maximum and average NDVI in Saudi Arabia are due to farming in the northern part of the country for which groundwater and desalinated seawater are used. The results of this study suggest that the main factors affecting the vegetation coverage in the Middle East are governmental policies. These policies can have a positive effect on the vegetation coverage in some countries such as Egypt, Saudi Arabia, Qatar, Kuwait, Iran, and Turkey.

In this work, magnetic CuFe₂O₄/Ag nanoparticles activated by porous covalent organic frameworks (COF) was fabricated to evaluate the heterogenous reduction of 4-nitrophenol (4-NP). The core-shell CuFe₂O₄/Ag@COF was successfully prepared by polydopamine reduction of silver ions on CuFe₂O₄ nanoparticles, followed by COF layer condensation. With integrating the intrinsic characteristics of the magnetic CuFe₂O₄/Ag core and COF layer, the obtained nanocomposite exhibited features of high specific surface area (464.21 m² g^-1), ordered mesoporous structure, strong environment stability, as well as fast magnetic response. Accordingly, the CuFe₂O₄/Ag@COF catalyst showed good affinity towards 4-NP via π-π stacking interactions and possessed enhanced catalytic activity compared with CuFe₂O₄/Ag and CuFe₂O₄@COF. The pseudo-first-order rate constant of CuFe₂O₄/Ag@COF (0.77 min^-1) is 3 and 5 times higher than CuFe₂O₄/Ag and CuFe₂O₄@COF, respectively. The characteristics of bi-catalytic CuFe₂O₄/Ag and the porous COF shell of CuFe₂O₄/Ag@COF made a contribution to improve the activity of 4-NP reduction. The present work demonstrated a facile strategy to fabricate COF activated nano-catalysts with enhanced performance in the fields of nitrophenolic wastewater treatment.

As one of the important components of underwater propulsion systems, water lubricated bearings are often failure due to mechanical wearing and vibrating, especially under high loads and prolonged friction. In this paper, a dual-network co-crosslinking strategy based on HNBR is proposed, in which the epoxy network connects with the rubber network through Epoxidized Eommia ulmoides gum. The damping, tribological and mechanical properties of the prepared composite are systematically investigated. The results show that this material has excellent friction and vibration damping properties, with a water-lubricated coefficient of friction as low as 0.022 and a wear resistance as high as 3.87 × 10-6mm3/Nm. Preparing HNBR-based composite by dual network co-crosslinked is proved being a feasible solution to improve the reliability and service life of water-lubricated bearings.

Remote sensing imagery is of great significance for policy decisions, especially for disaster assessment and disaster relief. To ensure the privacy and inviolability of personal buildings, the information containing these buildings must be anonymized during the remote sensing mapping process. Traditional processing methods for these targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Deep learning provides a new direction for target hiding. Although the image inpainting method based on deep learning is faster than the manual method, the cost of training calculation is a disadvantage. And the element-wise product operation used in the model increases the risk of vanished or exploded gradients. We propose a Residual Attention Target Hiding (RATH) model for remote sensing target hiding based on deep learning. RATH uses residual attention modules to replace gated convolutions, reducing parameters and mitigating gradient issues. The residual attention module preserves gated convolution performance but provides an adjustable kernel size. RATH retains gated convolutions for dynamic feature selection and balances model depth and width. Furthermore, this paper modifies the contextual attention layer by adjusting the fusion process to enlarge the fusion patch size. Finally, we extend the edge-guided function to preserve the original target information and confound viewers. Ablation studies on an open dataset prove RATH’s efficiency for image inpainting and target hiding. RATH achieves state-of-the-art results with lower complexity. And it has the highest similarity for edge-guided target hiding. RATH enables robust, efficient target hiding for privacy protection in remote sensing imagery while balancing performance and complexity. Experiments show RATH's superiority over existing methods in hiding arbitrary-shaped targets.

Crowd accident surveys have shown that regardless of the initial triggering factors, pedestrian fall behaviour is the most critical factor causing and aggravating crowd accidents in public traffic areas (PTAs). Application of pedestrian fall behaviour detection methods in PTAs is significant. Once deployed, it would prevent many pedestrians from losing life in crowed traffic areas accidents. However, most existing methods is still focused on medical assistance for the elderly. Therefore, this paper conducted bibliometric and content analyses, combining fall detection-related keywords to retrieve from internationally recognized literature databases and benchmark pedestrian behaviour datasets. Based on the analysis of the state-of-the-art (SOTA) achievements in fall detection methods, the fall detection methods were classified into different categories according to the research approach. Among them, it undertakes a comprehensive analysis of five predominant methods, namely computer vision, Internet of Things, smartphone, kinematic, and wearable device-based methods. Furthermore, the benchmark datasets including fall scenarios were introduced and compared. Finally, it provides a detailed discussion of existing fall detection methods, and possible future directions are identified considering application requirements in PTAs. This overview may help researchers understand the SOTA fall detection methods and devise new methodologies by improving and synthesizing the highlighted issues in PTAs.

With the increasing demand for medicinal plants and the increasing shortage of resources, improving the quality and yield of medicinal plants and making more effective use of medicinal plants has become an urgent problem to be solved. In the process of growth and development of medicinal plants, due to the threat of various adversity, there are problems such as nutrient loss and yield decline. Using traditional chemical pesticides to control the stress resistance of plants will cause serious pollution to the environment and even endanger human health. Therefore, it is necessary to find suitable pesticide substitutes from natural ingredients. As an important part of the microecology of medicinal plants, endophytes can promote the growth of medicinal plants, improve the stress resistance of hosts, and promote the accumulation of active components of hosts. Because it has a more positive and direct impact on the host, and can metabolize rich medicinal ingredients, so researchers pay attention to it. This paper reviews the research in recent five years, aiming to provide ideas for improving the quality of medicinal plants, developing more microbial resources, exploring more medicinal natural products, and providing help for the development of the research on medicinal plants and endophytes.

Underwater image processing faces significant challenges due to the absorption and scattering of light as it travels through water. A self-supervised learning network based on the self-attention mechanism is proposed for underwater visual applications in this paper. The goal is to improve the effectiveness and stability of feature extraction from underwater images. By incorporating self-attention mechanism, the sensitivity of the original network architecture to degraded features of blurred underwater images is enhanced. The network proposed in this paper is trained using transfer learning and evaluated on various underwater image datasets. With distributive, quantitative, and qualitative advantages compared with other methods, experimental results have demonstrated that the algorithm presented shows a slighter decline in feature extraction ability for blurred images as the turbidity of water increases.

Water plays a vital role in the healthy growth of pears. Early detection of water stress can play a significant role in the timely management of water deficiency for pear yield. Most current methods are labour-intensive, time-consuming, only provide point measurements, and could be destructive. In this research, a real-time non-destructive method using a push-broom hyperspectral system (400-1000nm) was used to collect hyperspectral image data and detect the water stress of the pear seedling leaves. To build a reliable prediction model, machine learning techniques were used. The Successive Projections Algorithm (SPA) was applied for optimal wavelength selection. In particular, CNN was applied to obtain the features of key wavelengths. Both the CNN features and key wavelengths were put into RR-MLR, BLR and ENN for analysis. The training accuracy of the three modellings all reach the accuracy above 70% after about 100 epochs, while combination of CNN features outperformed the mere main spectra analysis. This research demonstrated that hyperspectral imaging coupled with machine learning techniques could be applied to predict the water content of pear leaves predict non-destructively.

Lemonomycin (1) was first isolated from the fermentation broth of Streptomyces candidus in 1964. The complete chemical structure was not elucidated until 2000 with extensive spectroscopic analysis. Lemonomycin is currently known as the only glycosylated tetrahydroisoquinoline antibiotic. Its potent antibacterial activity against Staphylococcus aureus and Bacillus subtilis and complex architecture make it an ideal target for total synthesis. In this short review, we summarize the research status of lemonomycin for biological activity, biosynthesis and chemical synthesis. The unique deoxy aminosugar-lemonose was proposed to play a crucial role in biological activity, as shown in other antibiotics, such as arimetamycin A, nocathiacin I, glycothiohexide α, and thiazamycins. Given the self-resistance of the original bacterial host, the integration of biosynthesis and chemical synthesis to pursue efficient synthesis and further derivatization is in high demand for the development of novel antibiotics to combat antibiotic-resistant infections.

Cotton fiber development transition from elongation to secondary cell wall biosynthesis is a critical growth shifting phase that affects cotton fiber final length, strength and other properties. Morphological dynamic analysis indicates that an asynchronous fiber developmental pattern between two cotton species. The critical time point for Gh and Gb fiber elongation termination is, respectively, 23 and 27 days post-anthesis (dpa). The temporal changes of protein expression at three representative development periods (15–19, 19–23, 23–27 dpa) were examined in both species with iTRAQ technics. Strikingly, a large proportion of differentially expressed proteins (DEPs) was identified at 19–23 dpa in Gh or at 23–27 dpa in Gb, corresponding to their fiber developmental transition timing from elongation to secondary cell wall biosynthesis. To better understand fibers transitional development, we comparatively analyzed those DEPs in 19–23 dpa of Gh vs. in 23–27 dpa of Gb, and noted that these cotton species indeed share fundamentally similar fiber development features under the biological processes. It also showed that there have limited overlaps in both specific upregulated and downregulated proteins between the two species, suggesting specie-specific protein regulations in development. Proteomic profiling revealed dynamic changes of several key proteins and biological processes that potentially correlate with fiber development transition. During the transition, upregulated proteins mainly involved in carbohydrate/energy metabolism, oxidation-reduction, cytoskeleton, protein turnover, Ca²⁺ signaling etc, whereas important downregulated proteins mostly concentrated in phenylpropanoid and flavonoid secondary metabolism pathways. Several changed proteins in this key stage were also validated by qRT-PCR. Overall, the present study provides accurate pictures of the regulatory networks of functional proteins during the fiber developmental transition.

During shearer operation, piston rod is susceptible to wear from invasion of pollutants, and then ruins sealing ring in hydraulic cylinder. This work attempts to conduct a systematical investigation of Cu-DLC (Cu-doped Diamond-like Carbon) film to improve the seal performance. Failure process of hydraulic cylinder was analyzed, and relevant parameters were determined. Several Cu-DLC films were deposited on the substrate of piston rod in a multi-ion beam assisted system, and their structures and combined tribological performances were investigated. As a result, dust particles attached to the piston rod may enter the cylinder, and damage the sealing ring under the radial force. Cu grains prefer to orientate (111) crystal plane with increase of Cu content, and may induce drop of hardness and internal stress for the film. Friction coefficient of the film ranges from 0.04 to 0.15, and rise of IG/ID ratio from 1.4 to 2.3 in Raman data indicates that bond transition from sp3-C to sp2-C may lower the friction coefficient. Modification mechanism of Cu-DLC film for the seal performance may come from synergistic effects of (i) contact force and friction heat induce the film graphitization, (ii) Cu doping improves toughness of the film and acts as a solid lubricant, and (iii) transfer layer plays a role of self-lubrication.

This study utilises NaOH to treat composite cementitious materials containing aeolian sand and zeolite powders, which were used to replace 50% of the cement in aeolian-sand concrete (ASC). The mechanical properties of treated ASC considerably improved, especially when the NaOH dosage was 4% by mass. After curing this sample (denoted as AAZC-4) for 28 d, its compressive strength improved by 17.2% and its split tensile was increased by 16.3%. Potassium feldspar and montmorillonite in zeolite powder and SiO2 in the sand were decomposed by OH− and combined with other elements to generate various silicate gels and A-type potassium zeolite crystals inside the concrete. Microscopic examination showed that the gels and crystals intertwined to fill the pores, decreasing (increasing) the percentage of large (small) pores, thus optimising the pore structure. This substantially improved the mechanical properties of ASC. Freeze–thaw salt-intrusion tests showed that the extent of mass loss, degree of damage and loss of compressive strength of AAZC-4 were similar to those of ordinary concrete but were reduced by 36.8%, 19% and 52.1%, respectively, compared with those of ASC. Therefore, AAZC-4 has sustainable working performance in the chloride ion permeable environment in cold and arid areas.

The COVID-19 pandemic has significantly impacted human health and daily life. Meteorological factors play a crucial role in virus transmission. Understanding these factors is critical for pandemic control, yet debates continue due to variations in research methods and data. This study uses a global dataset and focuses on administrative units smaller than 10,000 km². The relationship between daily COVID-19 incidence rates and meteorological factors—including temperature, relative humidity (RH), ultraviolet radiation (UVR), and diurnal temperature range (DTR)—was analyzed across 173 units in 62 countries. The results revealed significant nonlinear responses and lag effects between incidence rates and the meteorological factors. Key inflection points were observed at 0°C and 24°C for temperature, 63% for RH, 102 KJ/m² for UVR, and 15°C for DTR. Below 0°C, infection risk increased with rising temperatures; from 0°C to 24°C, risk decreased; and above 24°C, risk escalated rapidly. RH below 63% correlated inversely with infection risk, while above 63%, the correlation was positive. Infection risk decreased with UVR below 102 KJ/m² but increased beyond this threshold. These nonlinear responses are primarily driven by the differential effects of these factors on virus survival, transmission, and human immunity. Conditions around 24°C, 63% RH, 102 KJ/m² UVR, and DTR below 15°C appear optimal for human immunity, correlating with lower infection risk. High temperature and low UVR prompted immediate infection responses, while low temperatures, high UVR, and larger DTR showed delayed effects. These findings provide new, more reliable evidence for understanding the mechanisms driving COVID-19 pandemic dynamics and for preventing the future normalization of the epidemic.

Higher traffic density in Russian cities and less uniform traffic due to congestions are reasons for increased emissions of pollutants contained in exhaust gases of vehicles. The paper presents the modeling results of pollutant dispersion in Magnitogorsk. The analysis of these results shows that now many blocks of flats and social infrastructure of the city are in a zone with an excess of maximum allowable concentration of pollutants. Having summarized the methodological framework formulated by Russian and foreign researchers, the authors systemized the existing methods used to decrease pollutants produced by vehicles. It is proposed to choose an optimal combination of such methods applying a developed mathematical model. By adopting an optimal combination of the methods, it is possible to ensure minimum air pollutant emissions from vehicles, allocating limited financial resources. The mathematical modeling of the solutions on changing traffic density and structure and implementing methods used to decrease pollutants on one of the Magnitogorsk crossroads with the heaviest traffic is used to draw a conclusion about efficiency of the designed model used as a tool for strategic planning of development and transformation of street networks.

The sustainable development and operation of mining enterprises as major sources of economic growth in many countries is determined by both a balance of economic, environmental, and social objectives and the resources required to achieve these objectives. Transportation is one of the main resources at open pits. It accounts for up to 70% of open pit operating expenses. Various parameters of transportation means should be coordinated both with the parameters of the open pit and meet the conditions of its operation. The problem of selecting a dump truck model in the paper is solved using a universal system of selection criteria developed using an original methodology. The two-level system of criteria includes all currently known selection criteria. The peculiarity of the methodology is the use of the multi-criteria FUCOM method for ranking the criteria. In addition, it is proposed to differentiate the criteria evaluations according to the experts' competence levels. Sets of criteria for evaluation by experts of different levels are proposed. The obtained criterion ranks are recommended to be used by managers of mining enterprises to choose a dump truck model. The presented methodology is suitable for the development of new systems of criteria, considering significant changes in operating conditions or the emergence of factors not considered in this study. Evaluation of all models of dump trucks on the market using the developed system of criteria is envisaged by the authors in a future study.

Over the last few decades, many countries, especially Caribbean island ones, have been challenged by the devastating consequences of natural disasters, which pose a significant threat to human health and safety. Timely information related to the distribution of vulnerable population and critical infrastructure are key for an effective disaster relief. OpenStreetMap (OSM) has repeatedly been shown to be highly suitable for disaster mapping and management. However, large portions of the world, including countries exposed to natural disasters, remain unmapped. In this study, we propose a methodology that relies on remotely sensed measurements (e.g. VIIRS, Sentinel-2 and Sentinel-1) and derived classification schemes (e.g. forest and built-up land cover) to predict the completeness of OSM building footprints in three small island states (Haiti, Dominica and St. Lucia). We find that the combinatorial effects of these predictors explain up to 94% of the variation of the completeness of OSM building footprints. Our study extends the existing literature by demonstrating how remotely sensed measurements could be leveraged to evaluate the completeness of OSM database, especially in countries at high risk of natural disasters. Identifying areas that lack coverage of OSM features could help prioritize mapping efforts, especially in areas vulnerable to natural hazards and where current data gaps pose an obstacle to timely and evidence-based disaster risk management actions.

The branch prediction units (BPUs) generally have security vulnerabilities, which can be used by attackers to obtain the execution status, jump directions, and jump address of conditional branches, and the existing protection methods cannot defend against these attacks. Therefore, this article proposes a hardware security protection method for conditional branches of embedded systems. This method calculates the number of updates to the branch target buffer (BTB). When it exceeds the threshold, BTB is locked to prevent attackers from analyzing the execution status of branches based on the time difference of whether BTB is updated. Moreover, the hybrid physical unclonable function (PUF) circuit is designed to provide confidentiality protection for the jump directions, jump addresses, and their indexes, preventing attackers from stealing these critical data. If these mechanism fails and attackers successfully tamper with conditional branches, this paper proposes a control flow integrity (CFI) protection mechanism based on branch labels to timely detect tampering with instruction codes, jump addresses, and jump directions. The proposed method is implemented and tested on FPGA. The experimental results show that this method can achieve fine-grained security protection for conditional branches, with about 5.4% resource overhead and less than 5.5% performance overhead.

China is rich in coal resources, but the complex hydrogeological conditions lead to difficulties in coal mining, such as coal mine collapse, roof and water damage, and other accidents that occur frequently, resulting in many casualties and property losses. The use of coal mine hole detection technology to detect and analyze the internal environment of the coal mine in advance helps to reduce safety hazards and prevent coal mine accidents, for the existing coal mine hole detection technology operation is cumbersome, not easy to control, and insufficient depth of jacking prob-lems, this paper designs a new type of mine hole detection small robot. Firstly, this paper ana-lyzes the function and structural design of the mine hole detection robot, designs the variable diameter function according to the characteristics of narrow and uneven mine holes in coal mines, and analyzes the mechanics of the critical parts through theoretical calculations; secondly, based on the three-dimensional modeling software, established the structural model of the small robot for mine hole detection; after that, designed the robot's hardware circuits and control pro-grams for the presence of water and gas inside the mine hole, highlighting the need to carry out a new type of mine hole detection small robot. After that, we designed the robot's hardware circuit and control program, giving particular emphasis to the safety design of the circuit for the pres-ence of water and gas inside the mine hole of the coal mine. Finally, to verify the feasibility of the design program, the basic parameters and function tests of the mine hole detection small robot are carried out. The experimental results show that the mine hole inspection small robot realized by this design can adapt to the working hole diameter from 65 mm to 100 mm, the maximum working power is only 12 W, and the maximum crawling speed is 3.96 m/min. The maximum crawling slope reaches 90°, which can meet the actual mine hole inspection needs. The research can provide theoretical and design guidance for developing the mine hole detection robot with substantial engineering practical reference value.

Moral observer-licensing happens when people condone others’ morally questionable conducts due to their history of moral behaviors. We investigated in four studies (N = 808) this phenomenon in the context of cyberspace and its contributing factors and boundary conditions. Study 1 determined what participants perceived as typically moral and immoral behaviors in cyberspace. Then in Study 2, participants condemned less a story character’s online immoral behavior when they were informed of the character’s prior online moral behavior than when they were not, which indicates moral observer-licensing in cyberspace. Study 3 confirmed the presence of moral observer-licensing in cyberspace and further demonstrated that a character’s prior moral or immoral behavior online respectively reduces or intensifies the negativity of the character’s subsequent immoral behavior. Finally, Study 4 showed that participants who identified with the victim in a hypothetical scenario showed less forgiveness and more condemnation of a character’s immoral behavior than those who identified with the perpetrator or the bystander. These findings are of theoretical and practical significance for our understanding of cyber ethics.