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The operation and maintenance (O&M) period is a critical and resource-intensive phase of the life cycle of railway line infrastructure. The O&M of a railway line during this period requires a large amount of investment and labor. Thus, there is an urgent need for railway managers to seek more efficient management tools and methods to improve management efficiency and reduce maintenance costs. Infrastructure–building information model (I-BIM) technology, characterized by its intuitive representation and high information-integration capabilities, has gained considerable traction with infrastructure industry researchers. In the context of existing railway lines, the absence of corresponding I-BIMs or similar technology owing to the immaturity of technical development at the time led to the use of manual modeling processes, which have limitations such as high cost, slow speed, and low efficiency. This paper presents an innovative, high-speed, semiautomated method for generating I-BIMs for existing railway lines and leveraging asset management data without incurring additional data collection costs. This approach leverages key modules such as line trajectory computation, element model generation, the linking of O&M semantic information, and the visualization of asset health indexes, which can enable the swift and semiautomated creation of an O&M-oriented I-BIM for railway lines. This process elevates traditional two-dimensional database tables into more intuitive, operation-oriented, and semantically rich models. This results in the provision of more efficient support for maintenance management decisions related to railway lines. The proposed method addresses the limitations of manual modeling processes and can pave the way for enhanced O&M efficiency in the railway infrastructure sector. Practical Applications: The absence of BIMs during the design and construction phase of existing railway lines, coupled with the high costs and error rates associated with manual modeling, constitute substantial barriers to the implementation of BIMs in operation and management. By leveraging the proposed semiautomated modeling approach, which relies on management data, site managers and researchers can rapidly establish basic I-BIMs. Although the asset ledgers and station equipment plans used in this approach originate from National Railway Administration, similar data sets should serve as fundamental inputs for railway line operation and maintenance worldwide. By deploying this method, field managers can enhance traditional two-dimensional (2D) asset ledgers into a three-dimensional (3D) I-BIM, thereby offering a more intuitive understanding of the assets within their jurisdiction. Owing to the integration of geographic information system maps into the model, personnel can directly query asset-related geographic information, potentially reducing the frequency and cost of off-site surveys. For researchers, using this method to establish a real-world model rapidly offers convenient access for further BIM-based applications, such as the integration of real-time data from on-site sensors to formulate digital twins. [ABSTRACT FROM AUTHOR]

An extremely hazardous heavy metal called cadmium (Cd) is frequently released into the soil, causing a considerable reduction in plant productivity and safety. In an effort to reduce the toxicity of Cd, silicon dioxide nanoparticles were chosen because of their capability to react with metallic substances and decrease their adsorption. This study examines the processes that underlie the stress caused by Cd and how SiO2NPs may be able to lessen it through modifying antioxidant defense, oxidative stress, and photosynthesis. A 100 μM concentration of Cd stress was applied to the hydroponically grown wild rice line, and 50 μM of silicon dioxide nanoparticles (SiO2NPs) was given. The study depicted that when 50 μM SiO2NPs was applied, there was a significant decrease in Cd uptake in both roots and shoots by 30.2% and 15.8% under 100 μM Cd stress, respectively. The results illustrated that Cd had a detrimental effect on carotenoid and chlorophyll levels and other growth-related traits. Additionally, it increased the levels of ROS in plants, which reduced the antioxidant capability by 18.8% (SOD), 39.2% (POD), 32.6% (CAT), and 25.01% (GR) in wild rice. Nevertheless, the addition of silicon dioxide nanoparticles reduced oxidative damage and the overall amount of Cd uptake, which lessened the toxicity caused by Cd. Reduced formation of reactive oxygen species (ROS), including MDA and H2O2, and an increased defense system of antioxidants in the plants provided evidence for this. Moreover, SiO2NPs enhanced the Cd resistance, upregulated the genes related to antioxidants and silicon, and reduced metal transporters' expression levels. [ABSTRACT FROM AUTHOR]

Purpose: Low-grade gliomas (LGG) are common brain tumors with high mortality rates. Cancer cell invasion is a significant factor in tumor metastasis. Novel biomarkers are urgently needed to predict LGG prognosis effectively. Methods: The data for LGG were obtained from the Bioinformatics database. A consensus clustering analysis was performed to identify molecular subtypes linked with invasion in LGG. Differential expression analysis was performed to identify differentially expressed genes (DEGs) between the identified clusters. Enrichment analyses were then conducted to explore the function for DEGs. Prognostic signatures were placed, and their predictive power was assessed. Furthermore, the invasion-related prognostic signature was validated using the CGGA dataset. Subsequently, clinical specimens were procured in order to validate the expression levels of the distinct genes examined in this research, and to further explore the impact of these genes on the glioma cell line LN229 and HS-683. Results: Two invasion-related molecular subtypes of LGG were identified, and we sifted 163 DEGs between them. The enrichment analyses indicated that DEGs are mainly related to pattern specification process. Subsequently, 10 signature genes (IGF2BP2, SRY, CHI3L1, IGF2BP3, MEOX2, ABCC3, HOXC4, OTP, METTL7B, and EMILIN3) were sifted out to construct a risk model. Besides, the survival (OS) in the high-risk group was lower. The performance of the risk model was verified. Furthermore, a highly reliable nomogram was generated. Cellular experiments revealed the ability to promote cell viability, value-addedness, migratory ability, invasive ability, and colony-forming ability of the glioma cell line LN229 and HS-683. The qRT-PCR analysis of clinical glioma samples showed that these 10 genes were expressed at higher levels in high-grade gliomas than in low-grade gliomas, suggesting that these genes are associated with poor prognosis of gliomas. Conclusion: Our study sifted out ten invasion-related biomarkers of LGG, providing a reference for treatments and prognostic prediction in LGG. [ABSTRACT FROM AUTHOR]

Rock creep is the result of the combined effects of many environmental conditions, such as temperature and moisture, and internal hardening and damage. In this study, we introduce a creep parameter that accounts for the joint effect of hardening and damage by using a dashpot in the Nishihara model. A modified creep model is established by connecting this dashpot to the modified Nishihara model. The modeling results agree well with the experimental creep data. The model resolves the shortcomings of the conventional spider model in describing the accelerated creep properties. The creep instantaneous model can describe the creep curve and the hardening–damage characteristics of the creep process. [ABSTRACT FROM AUTHOR]

Network modeling characterizes the underlying principles of structural properties and is of vital significance for simulating dynamical processes in real world. However, bridging structure and dynamics is always challenging due to the multiple complexities in real systems. Here, through introducing the individual's activity rate and the possibility of group interaction, we propose a probabilistic activity-driven (PAD) model that could generate temporal higher-order networks with both power-law and high-clustering characteristics, which successfully links the two most critical structural features and a basic dynamical pattern in extensive complex systems. Surprisingly, the power-law exponents and the clustering coefficients of the aggregated PAD network could be tuned in a wide range by altering a set of model parameters. We further provide an approximation algorithm to select the proper parameters that can generate networks with given structural properties, the effectiveness of which is verified by fitting various real-world networks. Finally, we construct the co-evolution framework of the PAD model and higher-order contagion dynamics and derive the critical conditions for phase transition and bistable phenomenon using theoretical and numerical methods. Results show that tendency of participating in higher-order interactions can promote the emergence of bistability but delay the outbreak under heterogeneous activity rates. Our model provides a basic tool to reproduce complex structural properties and to study the widespread higher-order dynamics, which has great potential for applications across fields. [ABSTRACT FROM AUTHOR]

Federated learning is a promising learning paradigm that allows collaborative training of models across multiple data owners without sharing their raw datasets. To enhance privacy in federated learning, multi-party computation can be leveraged for secure communication and computation during model training. This survey provides a comprehensive review on how to integrate mainstream multi-party computation techniques into diverse federated learning setups for guaranteed privacy, as well as the corresponding optimization techniques to improve model accuracy and training efficiency. We also pinpoint future directions to deploy federated learning to a wider range of applications. [ABSTRACT FROM AUTHOR]

In order to study the mode I crack propagation mechanism of coal gangue concrete with different contents, the digital image correlation (DIC) method was used to carry out the three-point bending fracture tests on coal gangue concrete with different contents. The results show that the process of the mode I crack propagation of coal gangue concrete with different contents can be divided into three stages as follows: the elastic stage before crack initiation, extended viscoelastic stage, and extended fracture stage. The amount of coal gangue has a significant impact on the crack propagation path. The more the amount of coal gangue, the more the crack penetrates through the coal gangue coarse aggregate, the smaller the bending degree of the failure path, and the faster the crack propagation to the penetration speed. The crack initiation load, ultimate load, external force work, gravity work, and fracture energy all decrease with the increase of the coal gangue content. The data obtained by the DIC method and displacement extensometer are in good agreement, which proves that the DIC method is feasible. Based on the DIC method, before reaching the horizontal displacement on both sides of the crack tip, the horizontal displacement of the horizontal pixel is very small and there is a jump increase after the ultimate load. There are obvious inflection points on the left and right, and the horizontal displacement remains unchanged after the inflection point. After the horizontal displacement field of crack propagation reaches the limit load, there is an obvious limit; the limit gradually extends upward, and the corresponding crack tip strain field is also gradually enhanced. The more the coal gangue is added, the smaller the corresponding horizontal displacement and strain field is at the same limit load moment. The shape of the crack generation area of coal gangue concrete takes the crack tip as the axis of symmetry and is "gourd shaped." The more the content of the crack, the larger the crack generation area. [ABSTRACT FROM AUTHOR]

Menaquinone-7 (MK-7), a subtype of vitamin K2 (VK2), assumes crucial roles in coagulation function, calcium homeostasis, and respiratory chain transmission. The production of MK-7 via microbial fermentation boasts mild technological conditions and high biocompatibility. Nevertheless, the redox activity of MK-7 imposes constraints on its excessive accumulation in microorganisms. To address this predicament, an adaptive laboratory evolution (ALE) protocol was implemented in Bacillus subtilis BS011, utilizing vitamin K3 (VK3) as a structural analog of MK-7. The resulting strain, BS012, exhibited heightened tolerance to high VK3 concentrations and demonstrated substantial enhancements in biofilm formation and total antioxidant capacity (T-AOC) when compared to BS011. Furthermore, MK-7 production in BS012 exceeded that of BS011 by 76% and 22% under static and shaking cultivation conditions, respectively. The molecular basis underlying the superior performance of BS012 was elucidated through genome and transcriptome analyses, encompassing observations of alterations in cell morphology, variations in central carbon and nitrogen metabolism, spore formation, and antioxidant systems. In summation, ALE technology can notably enhance the tolerance of B. subtilis to VK and increase MK-7 production, thus offering a theoretical framework for the microbial fermentation production of other VK2 subtypes. Additionally, the evolved strain BS012 can be developed for integration into probiotic formulations within the food industry to maintain intestinal flora homeostasis, mitigate osteoporosis risk, and reduce the incidence of cardiovascular disease. Key points: • Bacillus subtilis was evolved for improved vitamin K tolerance and menaquinone-7 (MK-7) production • Evolved strains formed wrinkled biofilms and elongated almost twofold in length • Evolved strains induced sporulation to improve tolerance when carbon was limited [ABSTRACT FROM AUTHOR]

Menaquinone-7 (MK-7), a subtype of vitamin K2 (VK2), assumes crucial roles in coagulation function, calcium homeostasis, and respiratory chain transmission. The production of MK-7 via microbial fermentation boasts mild technological conditions and high biocompatibility. Nevertheless, the redox activity of MK-7 imposes constraints on its excessive accumulation in microorganisms. To address this predicament, an adaptive laboratory evolution (ALE) protocol was implemented in Bacillus subtilis BS011, utilizing vitamin K3 (VK3) as a structural analog of MK-7. The resulting strain, BS012, exhibited heightened tolerance to high VK3 concentrations and demonstrated substantial enhancements in biofilm formation and total antioxidant capacity (T-AOC) when compared to BS011. Furthermore, MK-7 production in BS012 exceeded that of BS011 by 76% and 22% under static and shaking cultivation conditions, respectively. The molecular basis underlying the superior performance of BS012 was elucidated through genome and transcriptome analyses, encompassing observations of alterations in cell morphology, variations in central carbon and nitrogen metabolism, spore formation, and antioxidant systems. In summation, ALE technology can notably enhance the tolerance of B. subtilis to VK and increase MK-7 production, thus offering a theoretical framework for the microbial fermentation production of other VK2 subtypes. Additionally, the evolved strain BS012 can be developed for integration into probiotic formulations within the food industry to maintain intestinal flora homeostasis, mitigate osteoporosis risk, and reduce the incidence of cardiovascular disease. Key points: • Bacillus subtilis was evolved for improved vitamin K tolerance and menaquinone-7 (MK-7) production • Evolved strains formed wrinkled biofilms and elongated almost twofold in length • Evolved strains induced sporulation to improve tolerance when carbon was limited [ABSTRACT FROM AUTHOR]

Interpolating non-uniform rational B-spline (NURBS) curves often leads to undesirable feedrate fluctuations due to the non-analytic relationship between the spline parameter and arc length. In this paper, we introduce a feedback method that effectively reduces feedrate fluctuations while maintaining simplicity in the interpolation process. Our approach begins by defining the chord length-parameter ratio (CPR), which we then predict for the current interpolation point using Newton's divided difference interpolation polynomial and historical CPR data. Subsequently, we calculate the compensation length based on tangent and chord directions, and we correct the initial parameter using the second-order Runge–Kutta method. Importantly, our method involves only two calculations of the first derivative of the NURBS curve, making it computationally efficient compared to most approximation methods. To validate our proposed method, we conduct numerical simulations and compare its performance against several approximation methods and a recent feedback method. The results demonstrate that our approach excels in terms of both efficiency and accuracy, making it a promising solution for improving NURBS curve interpolation. [ABSTRACT FROM AUTHOR]

While brain function is supported and constrained by the underlying structure, the connectome-based link estimated by current approaches is either relatively moderate or accompanied by high model complexity, with the essential principles underlying structure-function coupling remaining elusive. Here, by proposing a mapping method based on network eigendecomposition, we present a concise and strong correspondence between structure and function. We show that the explanation of functional connectivity can be significantly improved by incorporating interactions between different structural eigenmodes. We also demonstrate the pronounced advantage of the present mapping in capturing individual-specific information with simple implementation. Applying our methodology to the human lifespan, we find that functional diversity decreases with age, with functional interactions increasingly dominated by the leading functional mode. We also find that structure-function liberality weakens with age, which is driven by the decreases in functional components that are less constrained by anatomy, while the magnitude of structure-aligned components is preserved. Overall, our work enhances the understanding of structure-function coupling from a collective, connectome-oriented perspective and promotes a more refined identification of functional portions relevant to human aging, holding great potential for mechanistic insights into individual differences associated with cognition, development, and neurological disorders. An eigenmode-based structural and functional connectivity mapping approach applied to diffusion and functional MRI data reveals decreased structure-function liberality with age across the human lifespan. [ABSTRACT FROM AUTHOR]

Arbuscular mycorrhizal fungi (AMF) are obligate plant symbionts of most land plants. In these organisms, thousands of nuclei that are either genetically similar (homokaryotic) or derived from two distinct parents (dikaryotic) co-exist in a large syncytium. Here, we investigated the impact of these two nuclear organizations on the mycorrhizal response of potatoes (Solanum tuberosum) by inoculating four potato cultivars with eight Rhizophagus irregularis strains individually (four homokaryotic and four dikaryotic). By evaluating plant and fungal fitness-related traits four months post inoculation, we found that AMF genetic organization significantly affects the mycorrhizal response of host plants. Specifically, homokaryotic strains lead to higher total, shoot, and tuber biomass and a higher number of tubers, compared to dikaryotic strains. However, fungal fitness-related traits showed no clear differences between homokaryotic and dikaryotic strains. Nucleotype content analysis of single spores confirmed that the nucleotype ratio of AMF heterokaryon spores can shift depending on host identity. Together, these findings continue to highlight significant ecological differences derived from the two distinct genetic organizations in AMF. [ABSTRACT FROM AUTHOR]

While the link between brain structure and function remains an ongoing challenge, the prevailing hypothesis is that the structure-function relationship may itself be gradually decoupling from unimodal to transmodal cortex. However, this hypothesis is constrained by the underlying models which may neglect requisite information. Here we relate structural and functional connectivity derived from diffusion and functional MRI through orthogonal eigenmodes governing frequency-specific diffusion patterns. We find that low-frequency eigenmodes contribute little to functional interactions in transmodal cortex, resulting in divergent structure-function relationships. Conversely, high-frequency eigenmodes predominantly support neuronal coactivation patterns in these areas, inducing structure-function convergence along a unimodal-transmodal hierarchy. High-frequency information, although weak and scattered, could enhance the structure-function tethering, especially in transmodal association cortices. Our findings suggest that the structure-function decoupling may not be an intrinsic property of brain organization, but can be narrowed through multiplexed and regionally specialized spatiotemporal propagation regimes. Brain structure and function have been observed to be increasingly untethered in transmodal cortex. Here, the authors show that structure-function coupling in these areas can be enhanced by diffusion patterns governed by high-frequency eigenmodes. [ABSTRACT FROM AUTHOR]

Environmental changes play a critical role in determining the evolution of social dilemmas in many natural or social systems. Generally, the environmental changes include two prominent aspects: the global time-dependent fluctuations and the local strategy-dependent feedbacks. However, the impacts of these two types of environmental changes have only been studied separately, a complete picture of the environmental effects exerted by the combination of these two aspects remains unclear. Here we develop a theoretical framework that integrates group strategic behaviors with their general dynamic environments, where the global environmental fluctuations are associated with a nonlinear factor in public goods game and the local environmental feedbacks are described by the 'eco-evolutionary game'. We show how the coupled dynamics of local game-environment evolution differ in static and dynamic global environments. In particular, we find the emergence of cyclic evolution of group cooperation and local environment, which forms an interior irregular loop in the phase plane, depending on the relative changing speed of both global and local environments compared to the strategic change. Further, we observe that this cyclic evolution disappears and transforms into an interior stable equilibrium when the global environment is frequency-dependent. Our results provide important insights into how diverse evolutionary outcomes could emerge from the nonlinear interactions between strategies and the changing environments. Author summary: The intricate interplay between strategic behavior and environment is ubiquitous in complex systems of different scales. Previous works mainly focus on one aspect of the environmental changes: either global environment fluctuations that unidirectionally decide the welfare of the evolutionary dynamics, or local environment feedbacks that coevolve with the strategic behavior. Here we develop a theoretical framework that integrates them both in order to obtain a more complete picture of how group cooperation evolves in a general dynamic environment. We show that global environmental fluctuations can fundamentally alter the dynamical predictions of local game-environment evolution. The most interesting finding is the emergence of cyclic evolution of group cooperation and local environment, which forms an interior irregular loop in the phase plane, depending on the relative changing speed of both global and local environments compared to the strategic change. Such irregular loop, however, is substituted by an interior stable fixed point when considering a more complicated situation where the global environment is also frequency-dependent. Our results show how rich dynamical outcomes arise from the interactions between strategic behaviors and their natural or social environments, which has important practical value for solving social dilemmas in an ever-changing world. [ABSTRACT FROM AUTHOR]

The relationship between strain and elastic energy is simplified by introducing a stress state parameter based on the generalised Hooke's law. It is assumed that the micro-element strengths satisfy the Weibull distribution and a new model for the non-linear evolution of energy is developed by introducing the concept of rock micro-element strengths. A sensitivity analysis of the model parameters is carried out on this basis. The results show that the model agrees well with the experimental data. The model is close to the deformation and damage laws of the rock and is able to reflect the relationship between the elastic energy and strain of the rock. By comparing with other model curves, the model of this paper is more suitable for the experimental curve. They show that the improved model could better describe the stress–strain relationship of rock. Finally, according to the analysis of the influence of the distribution parameter on the variation pattern of the elastic energy of the rock, the magnitude of the distribution parameter can directly reflect the peak energy of the rock. [ABSTRACT FROM AUTHOR]

Stimulation to local areas remarkably affects brain activity patterns, which can be exploited to investigate neural bases of cognitive function and modify pathological brain statuses. There has been growing interest in exploring the fundamental action mechanisms of local stimulation. Nevertheless, how noise amplitude, an essential element in neural dynamics, influences stimulation-induced brain states remains unknown. Here, we systematically examine the effects of local stimulation by using a large-scale biophysical model under different combinations of noise amplitudes and stimulation sites. We demonstrate that noise amplitude nonlinearly and heterogeneously tunes the stimulation effects from both regional and network perspectives. Furthermore, by incorporating the role of the anatomical network, we show that the peak frequencies of unstimulated areas at different stimulation sites averaged across noise amplitudes are highly positively related to structural connectivity. Crucially, the association between the overall changes in functional connectivity as well as the alterations in the constraints imposed by structural connectivity with the structural degree of stimulation sites is nonmonotonically influenced by the noise amplitude, with the association increasing in specific noise amplitude ranges. Moreover, the impacts of local stimulation of cognitive systems depend on the complex interplay between the noise amplitude and average structural degree. Overall, this work provides theoretical insights into how noise amplitude and network structure jointly modulate brain dynamics during stimulation and introduces possibilities for better predicting and controlling stimulation outcomes. Author summary: Despite the extensive application of local stimulation in cognition research and disease treatments, how regional perturbations alter brain-wide dynamics has not yet been fully understood. Given that noninvasive stimulation is associated with changes in the signal-noise relationship, we assume that noise amplitude is one of the plausible factors modulating the stimulation effects. Using a whole-brain biophysical model under different stimulation sites and noise amplitudes, we explore the influence of noise amplitude on stimulation effects and, more importantly, the interplay between noise amplitude and network structure. From a regional perspective, noise amplitude reduces the peak frequencies in unstimulated areas during stimulation. Moreover, we find a high similarity between the noise-averaged peak frequency matrix and the structural network. From a network perspective, we show that the changes in functional connectivity are decreased by noise amplitude, while the alterations in structural constraints display nonmonotonic trends. Intriguingly, increasing the noise amplitude in specific ranges can improve the association between network-level effects and structural degree, promoting better predicting and controlling therapeutic performance. Finally, the behaviors of cognitive systems quantified by network-level effects are jointly modulated by the noise amplitude and average structural degree. [ABSTRACT FROM AUTHOR]

Vitamin K2 plays an important role in electron transport, blood coagulation, and calcium homeostasis, and researchers have been trying to use microbes to produce it. Although our previous studies have shown that gradient radiation, breeding, and culture acclimation can improve vitamin K2 production in Elizabethkingia meningoseptica, the mechanism is still unclear. This study is the first which performs genome sequencing of E. meningoseptica sp. F2 as a basis for subsequent experiments and further comparative analyses with other strains. Comparative metabolic pathway analysis of E. meningoseptica sp. F2, E. coli, Bacillus subtilis, and other vitamin K2 product strains revealed that the mevalonate pathway of E. meningoseptica sp. F2 is different in bacteria at the system level. The expressions of menA, menD, menH, and menI in the menaquinone pathway and idi, hmgR, and ggpps in the mevalonate pathway were higher than those in the original strain. A total of 67 differentially expressed proteins involved in the oxidative phosphorylation metabolic pathway and citric acid cycle (TCA cycle) were identified. Our results reveal that combined gradient radiation breeding and culture acclimation can promote vitamin K2 accumulation probably by regulating the vitamin K2 pathway, oxidative phosphorylation metabolism pathway, and the citrate cycle (TCA cycle). [ABSTRACT FROM AUTHOR]

Different stress creep tests are conducted on the sandstone in this study to better describe the creep properties of rocks under different stress states. A model that describes the rock creep process is established. The various stages of creep can be described by combining the creep properties of the creep elements of the model. A new method for determining creep parameters is proposed by using the special point on the creep curve and the definition of creep deformation. The relationship between the creep parameters, stress, and time is analyzed. An improved creep model that considers the effects of stress state and time on the creep parameters is developed. This model is verified using experimental data and calculation results. Results shows that the improved creep model better describes the creep properties of rocks and provides a new method for determining future model parameters. The shear modulus of elastic model controls the instantaneous deformation. The shear modulus of viscoelastic model governs the limit of viscoelastic deformation. The shear viscoelastic coefficient of viscoelastic model increases with the increase in stress. The coefficient of viscoplastic model controls the viscoplastic creep rate. The coefficient of a nonlinear Newtonian dashpot mainly controls the accelerated creep deformation of rock. The calculation results of the proposed model agree well with the experimental data under the action of different stress levels. This model accurately reflects the creep characteristics of the primary and steady-state creep stages, and overcomes the shortcomings of the traditional Nishihara model in describing accelerated creep. [ABSTRACT FROM AUTHOR]

Lung cancer, amongst the fast growing malignant tumors, has become the leading cause of cancer death, which deserves attention. From a prevention and treatment perspective, advances in screening, diagnosis, and treatment have driven a reduction in non-small-cell lung cancer (NSCLC) incidence and improved patient outcomes. It is of benefit that the identification of key genetic markers contributes to the understanding of disease initiation and progression. In this work, information theoretical measures are proposed to determine the collaboration between genes and specific NSCLC samples. Top mutual information observes genes of high sample classification accuracy, such as STX11, S1PR1, TACC1, LRKK2, and SRPK1. In particular, diversity exists in different gender, histology, and smoking situations. Furthermore, leading synergy detects a high-accuracy combination of two ordinary individual genes, bringing a significant gain in accuracy. We note a strong synergistic effect of genes between COL1A2 and DCN, DCN and MMP2, and PDS5B and B3GNT8. Apart from that, RHOG is revealed to have quite a few functions in coordination with other genes. The results provide evidence for gene-targeted therapy as well as combined diagnosis in the context of NSCLC. Our approach can also be extended to find synergistic biomarkers associated with different diseases. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) and blockchain, the hottest frontier technologies in recent years, are expected to lead the next technological revolution. Blockchain promises to solve the current challenges encountered by the IoT. However, most of the proposed blockchain-based IoT architectures, which are based on discrete logarithm or large integer factorization problems, are susceptible to quantum attacks. Several quantum-resistant blockchain schemes have recently been proposed. However, the efficiency of their construction or the equipment required is not satisfactory. In this paper, to construct a more efficient postquantum blockchain infrastructure, we propose blockchain architecture for the IoT over the NTRU lattice and provide a cryptographic security proof of the scheme. Attributed to the more efficient underlying lattice structure, our scheme has excellent performance when compared to the existing quantum-resistant blockchain scheme, and we reduce the transaction size from hundreds of megabytes to several kilobytes. To further improve the blockchain's performance, we present the general framework of segregated witnesses and aggregate signatures over the NTRU lattice. Our scheme promises a blockchain solution for resource-constrained environments. [ABSTRACT FROM AUTHOR]

Nowadays, graph representation learning methods, in particular graph neural network methods, have attracted great attention and performed well in many downstream tasks. However, most graph neural network methods have a single perspective since they start from the edges (or adjacency matrix) of graphs, ignoring the mesoscopic structure (high-order local structure). In this paper, we introduce HS-GCN (High-order Node Similarity Graph Convolutional Network), which can mine the potential structural features of graphs from different perspectives by combining multiple high-order node similarity methods. We analyze HS-GCN theoretically and show that it is a generalization of the convolution-based graph neural network methods from different normalization perspectives. A series of experiments have shown that by combining high-order node similarities, our method can capture and utilize the high-order structural information of the graph more effectively, resulting in better results. [ABSTRACT FROM AUTHOR]

High biomass and nutrient acquisition are desirable for oat (Avena sativa L.) as a cover crop. However, our understanding of oat genotypes suitable for cover crops and associated traits is limited. The objectives of this experiment on growing oat as a cover crop, after winter wheat (Triticum aestivum L.) harvest, were to determine biomass production, nutrient uptake of a set of oat genotypes, and to identify phenotypic traits that can be used as indicators to select cultivars suitable for cover crops. The results showed that the top biomass-producing genotypes took up larger amounts of soil nutrients, up to 142 kg N ha−1 and 17 kg P ha−1 in 2016, and 43.5 kg N ha−1 and 8.3 kg P ha−1 in 2017. The biomass production was significantly related to plant height and leaf area index (LAI) in both years, and to the normalized difference vegetation index (NDVI) in 2017. Both NDVI and LAI were closely related to the total amounts of N and P uptake. The poor association between biomass and NDVI in 2016 was due to vigorous growth of volunteer wheat and weeds as well as severe rust (Puccinia coronata f. sp. avenae Eriks.) infestation. Our results suggest that it is important to choose oat varieties as cover crops. Leaf area index can be used as a nondestructive indicator for final biomass and nutrient acquisition, while both NDVI and LAI are important traits for choosing oats as soil conservation cover crops. [ABSTRACT FROM AUTHOR]

The biosynthesis of citric acid (CA) using Aspergillus niger as a carrier is influenced by mycelium morphology, which is determined by the expression level of morphology-related genes. As a key component of the fungal cell wall, chitin content has an important effect on morphogenesis, and to investigate the effects of this on fermentation performance, we used RNA interference to knockdown chitin synthase C (CHSC) and chitin synthase activator (CHS3) to obtain the single-gene mutant strains A. niger chs3 and chsC and the double mutant A. niger chs3C. We found that the CA fermentation performance of the two single mutants was significantly better than that of the double mutant. The mutant A. niger chs3-4 exhibited CA production potential compared to that of the parent strain in scale-up fermentation; we determined certain characteristics of CA high-yielding strain fermentation pellets. In addition, when chsC alone was silenced, there was very little change in chs3 mRNA levels, whereas those of chsC were significantly reduced when only chs3 was silenced. As this may be because of a synergistic effect between chsC and chs3, and we speculated that the latent activation target of CHS3 is CHSC, our results confirmed this hypothesis. This study is the first application of a separation and combination silence strategy of chitin synthase and chitin synthase activator in the morphology of A. niger CA fermentation. Furthermore, it provides new insights into the method for the morphological study of A. niger fermentation and the interaction of homologous genes. Key points: • The function of chitin synthase C (chsC) and chitin synthase activator (chs3) is tightly interrelated. • Mycelial morphology was optimized by knockdown of CHS3, resulting in the overproduction of citric acid. • The separation and combination silence strategies are promising tools for the interaction of homologous housekeeping genes. [ABSTRACT FROM AUTHOR]

To detect residual pre-proinsulin (PPI) in recombinant human insulin production, an analytical method based on double-antibody sandwich ELISA was developed in this study. The BALB/c mice were immunized with PPI, and the hybridomas secreting anti-PPI monoclonal antibodies were obtained using the conventional cell fusion technique and ELISA screening. We purified the antibody using a Protein G gel column and identified its purity by SDS-PAGE. The sandwich ELISA was used to explore the pairing effect, and the specificity of the paired antibody was determined. We selected a paired antibody with relatively good specificity to establish sandwich ELISA, constructed a quantitative curve, and evaluated the accuracy and sensitivity of the method. Six anti-PPI monoclonal antibodies were obtained, named P1, P2, P3, P4, P5 and P6, of which P5 had the highest titer value. The sandwich ELISA method was established with P5 for plating and P2 as detection antibodies. The linear range of the quantitative curve of PPI by sandwich ELISA was 0.645 to 82.5 pg/mL, the recovery was 95% and the detection limit was 3.06 pg/mL. In this study, we prepared six anti-PPI monoclonal antibodies and established the sandwich ELISA method to detect PPI in process control and product release control for recombinant human insulin production. [ABSTRACT FROM AUTHOR]

Bacillus subtilis is one of the few strains that can secrete synthetic menaquinone-7 (MK-7) to the outside of the cell, and its purpose and mechanism have not been clearly studied. As an amphiphilic protein naturally synthesized by Bacillus subtilis, the BslA protein may be involved in the inversion of extracellular vitamin K2 solubility. The protein structure in UniProt was used to search for the possible binding sites of MK-7, and the analysis of the higher ranking results of the genetic algorithm showed that the ASP166 residue was likely to be the binding site. They could form a stable hydrogen bond connection through ASP166, and approximately 7 proteins formed the conformation of a fixed naphthoquinone ring. We isolated and obtained the BslA protein by Ni-NTA affinity chromatography. Then, MK-7 was modified by BslA in vitro. A series of experiments, such as SEM, XPS, and WCA, showed that MK-7 and BslA proteins can realize self-assembly and transform from fat-soluble to water-soluble complexes. When the bslA protein in Bacillus subtilis natto was overexpressed, its MK-7 synthesis ability was further improved, especially the extracellular MK-7 content, which increased by 16%. This finding suggests that the BslA protein in Bacillus subtilis is likely to be involved in the extracellular secretion of MK-7 as a receptor. [ABSTRACT FROM AUTHOR]

Identifying the most influential spreaders in online social networks plays a prominent role in affecting information dissemination and public opinions. Researchers propose many effective identification methods, such as k-shell. However, these methods are usually validated by simulating propagation models, such as epidemic-like models, which rarely consider the Push-Republish mechanism with attenuation characteristic, the unique and widely-existing spreading mechanism in online social media. To address this issue, we first adopt the Push-Republish (PR) model as the underlying spreading process to check the performance of identification methods. Then, we find that the performance of classical identification methods significantly decreases in the PR model compared to epidemic-like models, especially when identifying the top 10% of superspreaders. Furthermore, inspired by the local tree-like structure caused by the PR model, we propose a new identification method, namely the Local-Forest (LF) method, and conduct extensive experiments in four real large networks to evaluate it. Results highlight that the Local-Forest method has the best performance in accurately identifying superspreaders compared with the classical methods. [ABSTRACT FROM AUTHOR]

Lattice-based cryptography, as an active branch of post-quantum cryptography (PQC), has drawn great attention from side-channel analysis researchers in recent years. Despite the various side-channel targets examined in previous studies, detail on revealing the secret-dependent information efficiently is less studied. In this paper, we propose adaptive EM side-channel attacks with carefully constructed ciphertexts on Kyber, which is a finalist of NIST PQC standardization project. We demonstrate that specially chosen ciphertexts allow an adversary to modulate the leakage of a target device and enable full key extraction with a small number of traces through simple power analysis. Compared to prior research, our techniques require fewer traces and avoid building complex templates. We practically evaluate our methods using both a reference implementation and the ARM-specific implementation in pqm4 library. For the reference implementation, we target the leakage of the output of the inverse NTT computation and recover the full key with only four traces. For the pqm4 implementation, we develop a message-recovery attack that leads to extraction of the full secret key with between eight and 960 traces, depending on the compiler optimization level. We discuss the relevance of our findings to other lattice-based schemes and explore potential countermeasures. [ABSTRACT FROM AUTHOR]

While inequalities in science are common, most efforts to understand them treat scientists as isolated individuals, ignoring the network effects of collaboration. Here, we develop models that untangle the network effects of productivity defined as paper counts, and prominence referring to high-impact publications, of individual scientists from their collaboration networks. We find that gendered differences in the productivity and prominence of mid-career researchers can be largely explained by differences in their coauthorship networks. Hence, collaboration networks act as a form of social capital, and we find evidence of their transferability from senior to junior collaborators, with benefits that decay as researchers age. Collaboration network effects can also explain a large proportion of the productivity and prominence advantages held by researchers at prestigious institutions. These results highlight a substantial role of social networks in driving inequalities in science, and suggest that collaboration networks represent an important form of unequally distributed social capital that shapes who makes what scientific discoveries. While inequalities in science are common, most efforts to understand them treat scientists as isolated individuals, ignoring the network effects of collaboration. Here, the authors develop models that untangle the network effects of productivity and prominence of individual scientists from their collaboration networks. [ABSTRACT FROM AUTHOR]

In computer numerical control systems, linear segments generated by computer-aided manufacturing software are the most widely used toolpath format. Since the linear toolpath is discontinuous at the junction of two adjacent segments, the fluctuations on velocity, acceleration and jerk are inevitable. Local corner smoothing is widely used to address this problem. However, most existing methods use symmetrical splines to smooth the corners. When any one of the linear segments at the corner is short, the inserted spline will be micro to avoid overlap. This will increase the curvature extreme of the spline and reduce the feedrate on it. In this article, the corners are smoothed by a C 4 continuous asymmetric Pythagorean-hodograph (PH) spline. The curvature extreme of the proposed spline is investigated first, and K = 2.5 is determined as the threshold to constrain the asymmetry of the spline. Then, a two-step strategy is used to generate a blended toolpath composed of asymmetric PH splines and linear segments. In the first step, the PH splines at the corners are generated under the condition that the transition lengths do not exceed half of the length of the linear segments. In the second step, the splines at the corners are re-planned to reduce the curvature extremes, if the transition error does not reach the given threshold and there are extra linear trajectories on both sides of the spline trajectory. Finally, the bilinear interpolation method is applied to determine the critical points of the smoothed toolpath, and a jerk-continuous feedrate scheduling scheme is presented to interpolate the smoothed toolpath. Simulations show that, under the condition of not affecting the machining quality, the proposed method can improve the machining efficiency by 7.27 to 75.11 % compared to G 3 and G 4 methods. [ABSTRACT FROM AUTHOR]

Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2 datasets of static images and 1 dataset of video data. HTNet achieves an area under the receiver operating curve (AUC) of 0.905 (95% CI: 0.894 to 0.915), 0.888 (0.836–0.939) and 0.895 (0.862–0.927). HTNet exceeds radiologists' performance on accuracy (83.2% versus 79.8%; binomial test, p < 0.001) and sensitivity (82.6% versus 68.1%; p < 0.001). By integrating serologic markers with imaging data, the performance of HTNet was significantly and marginally improved on the video (AUC, 0.949 versus 0.888; DeLong's test, p = 0.004) and static-image (AUC, 0.914 versus 0.901; p = 0.08) testing sets, respectively. HTNet may be helpful as a tool for the management of HT. Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. Here the authors develop a deep learning model for diagnosis of HT on a large multi-site dataset including image and video data. [ABSTRACT FROM AUTHOR]

Nutritional food supplements and pharmaceutical products produced with vitamin K2 as raw materials a very promising market in the global scope. The main production method of vitamin K2 is microbial fermentation, but approximately 50% of vitamin K2 synthesized by the main production strain Bacillus subtilis natto exists in extracellular form, which is not easy to separate and extract. In order to solve this problem, in this study, we synthesized a novel cellulose flocculant, MCC-g-LMA, by grafting reaction using microcrystalline cellulose (MCC) and lauryl methacrylate (LMA) as monomers, and ammonium persulfate as an initiator to flocculate VK2 from the fermentation supernatant. The flocculant was characterized by Fourier transform infrared spectroscopy (FTIR), elemental analysis, and scanning electron microscopy (SEM), and the grafting reaction was successful. When the flocculant dosage was 48.0 mg/L and pH was 5.0, the flocculation rate of the MCC-g-LMA on the fermentation supernatant reached 85.3%, and the enrichment rate of VK2 reached 90.0%. Furthermore, we explored the flocculation mechanism of VK2 by the MCC-g-LMA and speculated that the flocculation mechanism mainly included adsorption bridging, hydrophobic association and net trapping and sweep effect. In this study, the extraction method for trace high-value biological products in the fermentation supernatant was improved, which provided a method and theoretical basis for the efficient separation and purification of VK2 and other terpenoids. [ABSTRACT FROM AUTHOR]

Public goods games are widely used to model social dilemmas involving multiple agents. Though defection is the only rational choice for an individual in a public goods game, cooperative behavior is observed in a variety of social dilemmas, which is the subject of our research. Punishing defectors has been shown to be an effective mechanism for promoting cooperation, but it relies on the third-party umpire being fair. In this article, an umpire intervention model with corruption is proposed to explore the impact of corruption on punishment mechanisms. In our model, players and umpires operate in a multilayer network. The players play public goods games, which are overseen by umpires. Fair umpires punish defectors, whereas corrupt umpires take bribes from defectors rather than meting out a punishment. We separately explore the effects of the fraction of fair umpires ρ f , the spatial distribution, and the fine cost α and bribe cost β. Our Monte Carlo simulation shows that the above factors have a significant impact on cooperation. Intervention by an umpire always improves social efficiency, even for an entirely corrupt system. Moreover, relatively developed systems can resist corruption. Staggered and centralized distributions always have opposite effects on cooperative behavior, and these effects depend on ρ f and r. We also find that whether cooperators fully occupy the player layer depends only on whether β reaches a certain threshold. [ABSTRACT FROM AUTHOR]

Background: Menaquinone-7 (MK-7), which is associated with complex and tightly regulated pathways and redox imbalances, is produced at low titres in Bacillus subtilis. Synthetic biology provides a rational engineering principle for the transcriptional optimisation of key enzymes and the artificial creation of cofactor regeneration systems without regulatory interference. This holds great promise for alleviating pathway bottlenecks and improving the efficiency of carbon and energy utilisation. Results: We used a bottom-up synthetic biology approach for the synthetic redesign of central carbon and to improve the adaptability between material and energy metabolism in MK-7 synthesis pathways. First, the rate-limiting enzymes, 1-deoxyxylulose-5-phosphate synthase (DXS), isopentenyl-diphosphate delta-isomerase (Fni), 1-deoxyxylulose-5-phosphate reductase (DXR), isochorismate synthase (MenF), and 3-deoxy-7-phosphoheptulonate synthase (AroA) in the MK-7 pathway were sequentially overexpressed. Promoter engineering and fusion tags were used to overexpress the key enzyme MenA, and the titre of MK-7 was 39.01 mg/L. Finally, after stoichiometric calculation and optimisation of the cofactor regeneration pathway, we constructed two NADPH regeneration systems, enhanced the endogenous cofactor regeneration pathway, and introduced a heterologous NADH kinase (Pos5P) to increase the availability of NADPH for MK-7 biosynthesis. The strain expressing pos5P was more efficient in converting NADH to NADPH and had excellent MK-7 synthesis ability. Following three Design-Build-Test-Learn cycles, the titre of MK-7 after flask fermentation reached 53.07 mg/L, which was 4.52 times that of B. subtilis 168. Additionally, the artificially constructed cofactor regeneration system reduced the amount of NADH-dependent by-product lactate in the fermentation broth by 9.15%. This resulted in decreased energy loss and improved carbon conversion. Conclusions: In summary, a "high-efficiency, low-carbon, cofactor-recycling" MK-7 synthetic strain was constructed, and the strategy used in this study can be generally applied for constructing high-efficiency synthesis platforms for other terpenoids, laying the foundation for the large-scale production of high-value MK-7 as well as terpenoids. [ABSTRACT FROM AUTHOR]

Brain health is an important research direction of neuroscience. In addition to the effects of diseases, we cannot ignore the negative effect of aging on brain health. There have been many studies on brain aging, but only a few have used dynamic models to analyze differences in micro brain characteristics in healthy people. In this article, we use the relaxed mean-field model (rMFM) to study the effects of normal aging. Two main parameters of this model are the recurrent connection strength and subcortical input strength. The sensitivity of the rMFM to the initial values of the parameters has not been fully discussed in previous research. We examine this issue through repeated numerical experiments and obtain a reasonable initial parameter range for this model. Differences in recurrent connection strength and subcortical input strength due to aging have also not been studied previously. We use statistical methods to find the regions of interest (ROIs) exhibiting significant differences between young and old groups. Further, we carry out a difference analysis on the process of change of these ROIs on a more detailed timescale. We find that even with the same final results, the trends of change in these ROIs are different. This shows that to develop possible methods to prevent or delay brain damage due to aging, more attention needs to be paid to the trends of change of different ROIs, not just the final results. [ABSTRACT FROM AUTHOR]

Vitamin K2, a natural fat-soluble vitamin, is a potent neuroprotective molecule, owing to its antioxidant effect, but its mechanism has not been fully elucidated. Therefore, we stimulated SH-SY5Y cells with 6-hydroxydopamine (6-OHDA) in a proper dose-dependent manner, followed by a treatment of vitamin K2. In the presence of 6-OHDA, cell viability was reduced, the mitochondrial membrane potential was decreased, and the accumulation of reactive oxygen species (ROS) was increased. Moreover, the treatment of 6-OHDA promoted mitochondria-mediated apoptosis and abnormal mitochondrial fission and fusion. However, vitamin K2 significantly suppressed 6-OHDA-induced changes. Vitamin K2 played a significant part in apoptosis by upregulating and downregulating Bcl-2 and Bax protein expressions, respectively, which inhibited mitochondrial depolarization, and ROS accumulation to maintain mitochondrial structure and functional stabilities. Additionally, vitamin K2 significantly inhibited the 6-OHDA-induced downregulation of the MFN1/2 level and upregulation of the DRP1 level, respectively, and this enabled cells to maintain the dynamic balance of mitochondrial fusion and fission. Furthermore, vitamin K2 treatments downregulated the expression level of p62 and upregulated the expression level of LC3A in 6-OHDA-treated cells via the PINK1/Parkin signaling pathway, thereby promoting mitophagy. Moreover, it induced mitochondrial biogenesis in 6-OHDA damaged cells by promoting the expression of PGC-1α, NRF1, and TFAM. These indicated that vitamin K2 can release mitochondrial damage, and that this effect is related to the participation of vitamin K2 in the regulation of the mitochondrial quality-control loop, through the maintenance of the mitochondrial quality-control system, and repair mitochondrial dysfunction, thereby alleviating neuronal cell death mediated by mitochondrial damage. [ABSTRACT FROM AUTHOR]

Background: The study and application of microbial consortia are topics of interest in the fields of metabolic engineering and synthetic biology. In this study, we report the design and optimisation of Elizabethkingia meningoseptica and Escherichia coli co-culture, which bypass certain limitations found during the molecular modification of E. meningoseptica, such as resistance to many antibiotics and fewer available molecular tools. Results: The octaprenyl pyrophosphate synthase from E. meningoseptica sp. F2 (EmOPPS) was expressed, purified, and identified in the present study. Then, owing to the low vitamin K2 production by E. coli or E. meningoseptica sp. F2 monoculture, we introduced the E. meningoseptica and E. coli co-culture strategy to improve vitamin K2 biosynthesis. We achieved production titres of 32 mg/L by introducing vitamin K2 synthesis-related genes from E. meningoseptica sp. F2 into E. coli, which were approximately three-fold more than the titre achieved with E. meningoseptica sp. F2 monoculture. This study establishes a foundation for further engineering of MK-n (n = 4, 5, 6, 7, 8) in a co-cultivation system of E. meningoseptica and E. coli. Finally, we analysed the surface morphology, esterase activity, and membrane permeability of these microbial consortia using scanning electron microscopy, confocal laser scanning microscopy, and flow cytometry, respectively. The results showed that the co-cultured bacteria were closely linked and that lipase activity and membrane permeability improved, which may be conducive to the exchange of substances between bacteria. Conclusions: Our results demonstrated that co-culture engineering can be a useful method in the broad field of metabolic engineering of strains with restricted molecular modifications. [ABSTRACT FROM AUTHOR]

In high-speed CNC (compute numerical control) machining, the feedrate scheduling has played an important role to ensure machining quality and machining efficiency. In this paper, a novel feedrate scheduling method is proposed for generating smooth feedrate profile conveniently with the consideration of both chord error and kinematic error. First, a relationship between feedrate value and chord error is applied to determine the feedrate curve. Then, breaking points, which can split whole curve into several blocks, can be found out using proposed two step screening method. For every block, the feedrate profile based on Sigmoid function is generated. With the consideration of kinematic limitation and machining efficiency, a time-optimal feedrate adjustment algorithm is proposed to further adjust feedrate value at breaking points. After achieving feedrate profile for each block, all blocks' feedrate profile will be connected smoothly. The resulting feedrate profile is more concise compared with the polynomial profile and more efficient compared with the trigonometric profile. Finally, simulations with two free-form NURBS curves are conducted and comparison with the sine-curve method is carried out to verify the feasibility and applicability of the proposed method. In order to further validate the feasibility of proposed method, machining simulation experiments are also conducted using Unigraphics NX. [ABSTRACT FROM AUTHOR]

Purpose: Adaptive slicing is a key step in three-dimensional (3D) printing as it is closely related to the building time and the surface quality. This study aims to develop a novel adaptive slicing method based on ameliorative area ratio and accurate cusp height for 3D printing using stereolithography (STL) models. Design/methodology/approach: The proposed method consists of two stages. In the first stage, the STL model is sliced with constant layer thickness, where an improved algorithm for generating active triangular patches, the list is developed to preprocess the model faster. In the second stage, the model is first divided into several blocks according to the number of contours, then an axis-aligned bounding box-based contour matching algorithm and a polygons intersection algorithm are given to compare the geometric information between several successive layers, which will determine whether these layers can be merged to one. Findings: Several benchmarks are applied to verify this new method. Developed method has also been compared with the uniform slicing method and two existing adaptive slicing methods to demonstrate its effectiveness in slicing. Originality/value: Compared with other methods, the method leads to fewer layers whilst keeping the geometric error within a given threshold. It demonstrates that the proposed slicing method can reach a trade-off between the building time and the surface quality. [ABSTRACT FROM AUTHOR]

Cross-modal retrieval has become a topic of popularity, since multi-data is heterogeneous and the similarities between different forms of information are worthy of attention. Traditional single-modal methods reconstruct the original information and lack of considering the semantic similarity between different data. In this work, a cross-modal semantic autoencoder with embedding consensus (CSAEC) is proposed, mapping the original data to a low-dimensional shared space to retain semantic information. Considering the similarity between the modalities, an automatic encoder is utilized to associate the feature projection to the semantic code vector. In addition, regularization and sparse constraints are applied to low-dimensional matrices to balance reconstruction errors. The high dimensional data is transformed into semantic code vector. Different models are constrained by parameters to achieve denoising. The experiments on four multi-modal data sets show that the query results are improved and effective cross-modal retrieval is achieved. Further, CSAEC can also be applied to fields related to computer and network such as deep and subspace learning. The model breaks through the obstacles in traditional methods, using deep learning methods innovatively to convert multi-modal data into abstract expression, which can get better accuracy and achieve better results in recognition. [ABSTRACT FROM AUTHOR]

Lattice-based non-interactive zero-knowledge proof has been widely used in one-way communication and can be effectively applied to resist quantum attacks. However, lattice-based non-interactive zero-knowledge proof schemes have long faced and paid more attention to some efficiency issues, such as proof size and verification time. In this paper, we propose the non-interactive zero-knowledge proof schemes from RLWE-based key exchange by making use of the Hash function and public-key encryption. We then show how to apply the proposed schemes to achieve the fixed proof size and rapid public verification. Compared with previous approaches, our schemes can realize better effectiveness in proof size and verification time. In addition, the proposed schemes are secure from completeness, soundness, and zero-knowledge. [ABSTRACT FROM AUTHOR]

Structures of genetic regulatory networks are not fixed. These structural perturbations can cause changes to the reachability of systems' state spaces. As system structures are related to genotypes and state spaces are related to phenotypes, it is important to study the relationship between structures and state spaces. However, there is still no method can quantitively describe the reachability differences of two state spaces caused by structural perturbations. Therefore, Difference in Reachability between State Spaces (DReSS) is proposed. DReSS index family can quantitively describe differences of reachability, attractor sets between two state spaces and can help find the key structure in a system, which may influence system's state space significantly. First, basic properties of DReSS including non-negativity, symmetry and subadditivity are proved. Then, typical examples are shown to explain the meaning of DReSS and the differences between DReSS and traditional graph distance. Finally, differences of DReSS distribution between real biological regulatory networks and random networks are compared. Results show most structural perturbations in biological networks tend to affect reachability inside and between attractor basins rather than to affect attractor set itself when compared with random networks, which illustrates that most genotype differences tend to influence the proportion of different phenotypes and only a few ones can create new phenotypes. DReSS can provide researchers with a new insight to study the relation between genotypes and phenotypes. [ABSTRACT FROM AUTHOR]

By comparing the survival rate and positive mutation rate of the primary mutagenic strain and progeny mutagenic strain under different radiation doses, the results showed that the tolerance of the mutagenic strain to radiation dose increased with the increase of the mutagenic generations. We adopted an improved gradient radiation breeding strategy to improve the breeding efficiency. The strains were treated with radiation in four stages. The first stage was low energy N+ ion implantation (ion energy 15 keV, dose 80 × 2.6 × 1013 cm−2). In the second stage, the energy and dose of N+ ion reached to 20 keV, 90 × 2.6 × 1013 cm−2. In the third stage, 60Co-γ radiation (dose of 1.56 kGy) was used. In the fourth stage, the radiation dose of 60Co-γ increased to 1.82 kGy. After each stage of radiation, the MK (Menaquinone) precursor 1, 4-dihydroxy-2-naphthalate (DHNA) was used as the stress factor to domesticate the mutant strains. By gradually increasing the concentration of DHNA in the culture medium, the substrate tolerance of Flavobacterium sp. was effectively improved. By measuring SOD (superoxide dismutase) activity and malondialdehyde, it showed that the cell damage caused by radiation mutagenesis to the offspring mutant was less than that of the primary mutant. Changes in membrane permeability and membrane potential of the mutant strains were reflected in changes in fluorescence intensity of luciferin diacetate and rhodamine 123, which could explain the enhanced substrate tolerance of strain F-2. After gradient radiation breeding and culture acclimation, the biomass of mutant Strain F-2 was 6.59 g/L, and the MK yield was 9.59 mg/L. [ABSTRACT FROM AUTHOR]

Since the beginning of the 21st century, the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means. It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph. Based on adopting the graph pattern of general knowledge representation, the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge, and integrates geoscience knowledge elements, such as map, text, and number, to establish an all-domain geoscience knowledge representation model. A federated, crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here, which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists. We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis, which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph. A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis, but also advance the construction of the high-precision geological time scale driven by big data, the compilation of intelligent maps driven by rules and data, and the geoscience knowledge evolution and reasoning analysis, among others. It will further expand the new directions of geoscience research driven by both data and knowledge, break new ground where geoscience, information science, and data science converge, realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research. [ABSTRACT FROM AUTHOR]

Menaquinone-7 is involved in bone metabolism and can be used to prevent and treat osteoporosis. However, as a fat-soluble vitamin, menaquinone-7 has poor water solubility. As a surfactant, hydrophobins can change the affinity/hydrophobicity of the covered interface. In this study, menaquinone-7 was modified by hydrophobins, and the different addition ratios were explored. Moreover, Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), and water contact angle (WCA) measurements indicated that hydrophobins effectively bind to menaquinone-7 and greatly increase the hydrophilicity of the surface of menaquinone-7. Studies on the metabolism of MC3T3-E1 cells showed that compared with native menaquinone-7, HGFI-modified menaquinone-7 can significantly promote osteoblast differentiation but inhibit osteoclast differentiation. Besides, the Mito-Tracker Green experiments show that HGFI-modified menaquinone-7 can significantly promote the activity of mitochondria in cells. These findings indicate that hydrophobins can be used as an effective biomaterial to modify menaquinone-7, promote the formation of osteoblasts, and better to bone balance. [ABSTRACT FROM AUTHOR]

Prisoner's dilemma game is the most commonly used model of spatial evolutionary game which is considered as a paradigm to portray competition among selfish individuals. In recent years, Win-Stay-Lose-Learn, a strategy updating rule base on aspiration, has been proved to be an effective model to promote cooperation in spatial prisoner's dilemma game, which leads aspiration to receive lots of attention. In this paper, according to Expected Value Theory and Achievement Motivation Theory, we propose a dynamic aspiration model based on Win-Stay-Lose-Learn rule in which individual's aspiration is inspired by its payoff. It is found that dynamic aspiration has a significant impact on the evolution process, and different initial aspirations lead to different results, which are called Stable Coexistence under Low Aspiration, Dependent Coexistence under Moderate aspiration and Defection Explosion under High Aspiration respectively. Furthermore, a deep analysis is performed on the local structures which cause defectors' re-expansion, the concept of END- and EXP-periods are used to justify the mechanism of network reciprocity in view of time-evolution, typical feature nodes for defectors' re-expansion called Infectors, Infected nodes and High-risk cooperators respectively are found. Compared to fixed aspiration model, dynamic aspiration introduces a more satisfactory explanation on population evolution laws and can promote deeper comprehension for the principle of prisoner's dilemma. [ABSTRACT FROM AUTHOR]

8Effects of different treatments of menaquinone-7 on mitochondrial activity in MC3T3-E1 cells. 6Formation of extracellular mineralized nodules, detected by AR-S solution staining in MC3T3-E1 cells cultured with menaquinone-7, HGFI-modified menaquinone-7, and HGFI at different concentrations (0.1, 1.0, or 10 mg/L, respectively) for 7 days. a Cell image stained with AR-S solution. b The content of mineralized nodules detected by spectrophotometer. The cells were treated with menaquinone-7, HGFI-modified menaquinone-7, and HGFI at different concentration (0.1, 1.0, or 10 mg/L, respectively), a Fluorescence micrograph of cells after adding Mito-Tracker Green. b High-content screening analysis of mitochondrial fluorescence intensity in cells. [Extracted from the article]

A correction is presented to the article "Vitamin K2 Modulates Mitochondrial Dysfunction Induced by 6-Hydroxydopamine in SH-SY5Y Cells via Mitochondrial Quality-Control Loop."