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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]

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]

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]

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]

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]

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]

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]

Prenyltransferase NovQ is a vital class involved in the biosynthesis of secondary metabolites such as clorobiocin and novobiocin. To investigate the relationship between structure and catalytic properties of NovQ, here, we have analyzed the substrate-binding site, namely PT barrel, and revealed that menadione hydroquinol formed intermolecular interactions with the residue Glu281 near the center of the active pocket. In this study, Glu281 was substituted with 9 diverse amino acids and catalytic properties of mutants were observed in vitro. Among them, E281Q showed 2.05-fold activities towards the aromatic substrate and prenyl donor, while others obtained catalytic efficiency between 8.4 and 88.6% of that of wild-type NovQ. Furthermore, the effects of catalytic conditions and substrate status on the activity of NovQ and its mutants were considered to obtain the optimized prenylated reaction. When the evolutionary NovQ variant E281Q was overexpressed in the host constructed to synthesize dimethylallyl diphosphate through the engineered mevalonate (MVA) pathway, we harvested up to 4.7 mg/L prenylated menadione at C-3 position by exogenously supplying the aromatic substrate. The construction of the microbial platform based on NovQ opens a new orientation to further biosynthesize various vitamin K2 with other ABBA prenyltransferases in E. coli. [ABSTRACT FROM AUTHOR]

BACKGROUND The newly developed sugarcorn is conceived for dual‐purpose use as a potential biofuel feedstock and a high‐energy silage crop. Its agronomic traits are, however, not fully appraised under the umbrella of nitrogen (N) management and with canopy reflectance indicator. A 3‐year field study was conducted to examine the responses of silage biomass, stalk sugar concentration, sugar and juice yields to various N applications; and determine the quantitative relationships between canopy reflectance, expressed as the normalized difference vegetation index (NDVI), and stalk sucrose or other sugar measures in a dual‐purpose sugarcorn (cv. 'CO384xC103'), in comparison with a commercial leafy silage‐specific hybrid (cv. 'Pride A5892G3 EDF'). RESULTS: The moderate N rate, 125 kg ha−1, produced similar stalk sucrose, silage and grain yields, compared to the high rate (250 kg N ha−1), regardless of application methods. The NDVI signatures measured at the V8–V10 stage exhibited significant (P < 0.01) and exponential relationships with stalk sucrose concentrations, sucrose and juice yields at the R3 stage, and with silage yield at approximately 65% whole‐plant moisture, the optimum silage‐harvest window. CONCLUSION: The results indicate that the moderate N rate, 125 kg ha−1, which is recommended for conventional grain corn production in the region, was likely close to the economic optimum N rate for leafy silage‐specific and sugarcorn. Canopy reflectance, measured at the early growth stages, can be used as a potential indicator of sugar and silage production, and this quantitative relationship necessitates further evaluation with more genotypes and under wide environmental conditions. © 2019 Her Majesty the Queen in Right of Canada Journal of The Science of Food and Agriculture © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Balanced plant nutrition is essential to achieve high yields of canola (Brassica napus L.) and get the best economic return from applied fertilizers. A field study was conducted at nine site‐years across eastern Canada to investigate the effects of nitrogen (N), sulfur (S) and boron (B) fertilization on canola nutrient uptake, nutrient balance, and their relationship to canola yields. The factorial experiment consisted of four N rates of 0 (N0), 50 (N50), 100 (N100), and 150 (N150) kg ha−1, two S rates of 0 (S0) and 20 (S20) kg ha−1, and three B treatments of 0 (B0), 2 kg ha−1 at preplant (B2.0P), and 0.5 kg B ha−1 foliar‐applied at early flowering stage (B0.5F). Each site‐year used the same experimental design and assigned treatments in a randomized complete block design with four replications. Fertilizer S application greatly improved seed yields at six out of nine site‐years, and the highest N use efficiency was in the N150+S20 treatment. Sulfur application generally increased seed S concentration, seed S removal, and plant total S uptake, while B fertilization mainly elevated straw B concentration and content, with minimal effect on seed yields. At the early flowering stage, plant tissue S ranged from 2.2 to 6.6 mg S g−1, but the N : S ratio was over or close to the critical value of 12 in the N150+S0 combination at five site‐years. On average across nine site‐years, canola reached a plateau yield of 3580 kg ha−1 when plants contained 197 kg N ha−1, 33 kg S ha−1 and 200 g B ha−1, with a seed B content of 60 g B ha−1. The critical N, S, and B values identified in this work and their potential for a posteriori nutrient diagnosis of canola should be useful to validate fertilizer requirements for canola production in eastern Canada. [ABSTRACT FROM AUTHOR]

To address the issues of sluggish electronic transport and large volume variation of Fe 2 O 3 anode nanomaterials caused by repeated Li + insertion/extraction, herein we engineer an erythrocyte-like Fe 2 O 3 with thin mesoporous carbon into yolk-shell architectures, in which the erythrocyte-like Fe 2 O 3 is well confined inside the thin mesoporous carbon. In this design, the erythrocyte-like Fe 2 O 3 cores with high specific capacity together with the permeable thin carbon shells could not only greatly facilitate the fast diffusion for both ion and electron but also retain a thin and stable solid electrolyte interface (SEI) layer on its surface, resulting in excellent rate capability and cycling stability. Meanwhile, the hollow cavity between carbon shell and Fe 2 O 3 core provides extra free space for Fe 2 O 3 expansion, thus preserving the structural integrity. By virtue of their advantageous structural features, the elegant void-containing mesoporous carbon-encapsulated erythrocyte-like Fe 2 O 3 electrodes exhibit superior performance including large capacity, high rate capability and long cycle stability. More importantly, when coupled with commercial LiCoO 2 cathode, the assembled Li-ion full cell demonstrates a high reversible capacity of 615 mA h g −1 after 100 cycles at 1C with capacity retention of 83.4% as well as outstanding rate capability (675 mA h g −1 at 4C with capacity retention of 83% from 0.2C to 4C), demonstrating significant potential for future practical applications. [ABSTRACT FROM AUTHOR]

In this papa; a total of 723 traditional villages in Hunan wok selected for research. With the aid of spatial analysis of GIS, the number equilibrium and spatial autocorrelation of the traditional villages were analysed quantitatively, watershed distribution characteristics and ethnic distribution characteristics of the traditional villages were analyzed both qualitatively and quantitatively, and the influence factors of distribution of the traditional village were explored in terms of three aspects of agricultural production and population migration, history and culture, and economic activities. [ABSTRACT FROM AUTHOR]

According to advancements in the wireless technologies, study of biometrics-based multi-server authenticated key agreement schemes has acquired a lot of momentum. Recently, Wang et al. presented a three-factor authentication protocol with key agreement and claimed that their scheme was resistant to several prominent attacks. Unfortunately, this paper indicates that their protocol is still vulnerable to the user impersonation attack, privileged insider attack and server spoofing attack. Furthermore, their protocol cannot provide the perfect forward secrecy. As a remedy of these aforementioned problems, we propose a biometrics-based authentication and key agreement scheme for multi-server environments. Compared with various related schemes, our protocol achieves the stronger security and provides more functionality properties. Besides, the proposed protocol shows the satisfactory performances in respect of storage requirement, communication overhead and computational cost. Thus, our protocol is suitable for expert systems and other multi-server architectures. Consequently, the proposed protocol is more appropriate in the distributed networks. [ABSTRACT FROM AUTHOR]

In this paper, we propose a powerful weak learner (Vector Decision Tree (VDT)) and a new Boosted Vector Decision Tree (BVDT) algorithm framework for the task of multi-class classification. Unlike the traditional scalar valued boosting algorithms, the BVDT algorithm directly maps the feature space to the decision space in the multi-class setting, which facilitates convenient implementations of the multi-class classification algorithms using diverse loss functions. By viewing the explicit hard threshold on the leaf node value applied in the LogitBoost as a constraint optimization problem, we further develop two new variants of the BVDT algorithm: the -BVDT and the -BVDT. The performance of the proposed algorithm is evaluated on different datasets and compared with three state-of-the-art boosting algorithms, -Nearest Neighbor (KNN) and Support Vector Machine (SVM). The results show that the performance of the proposed algorithm ranks first in all but one dataset and reduces the test error rate by 4% up to 58% with respect to the state-of-the-art boosting algorithms based on the scalar-valued weak learner. Furthermore, we present a case study on the Abalone dataset by designing a new loss function that combines the negative log-likelihood loss function of classification problem and square loss function of regression problem. [ABSTRACT FROM AUTHOR]

• Established a prediction model of Vitamin K 2 based on near infrared spectroscopy. • Tested the effect of solution supersaturation on crystallization of Vitamin K 2. • Obtained Vitamin K 2 crystals with purity up to 99.7 % for the first time. Polymorphism is frequently encountered in most small molecule drugs and vitamin supplements, and the physical and chemical parameters of crystalline drugs may directly affect the solubility, bioavailability and clinical effects of the substances in the human body. Supersaturation is the key driving force of crystal nucleation and growth. Crystal forms and sizes are different under different supersaturation conditions. To rapid and efficient detection concentration of Vitamin K 2 , we established a solution concentration prediction model using near-infrared (NIR) spectroscopy in this study. The influence of supersaturation on Vitamin K 2 crystal formation was explored. The results showed that for freezing crystallization, the supersaturation would be larger than evaporative crystallization and the size of the crystals would be smaller. The particle size of freezing crystallization is mainly in the range of 5–20 μm while the particle size of evaporative crystallization is mostly distributed in the range of 20–40 μm. This study also found that the crystal form obtained by solvent evaporation method was more regular, mostly in flake shape and smooth surface. These results have guiding significance for biological preparation of high-purity Vitamin K 2 products with regular crystal shape, uniform particle size and good bioavailability. [ABSTRACT FROM AUTHOR]

The importance of urban portal has been improved, but the phenomenon of image convergence has become increasingly prominent The urban design of urban portal area should analyze and refine the regional culture of landscape culture, life culture, architectural culture, historical culture and so on, and combine with the design contents such as functional orientation, spatial pattern, public space, architectural style and landscape environment. [ABSTRACT FROM AUTHOR]

The evolution of networks or dynamic systems is controlled by many parameters in high-dimensional space, and it is crucial to extract the reduced and dominant ones in low-dimensional space. Here we consider the network ensemble, introduce a matrix resolvent scale function and apply it to a spectral approach to get the similarity relations between each pair of networks. The concept of Diffusion Maps is used to get the principal parameters, and we point out that the reduced dimensional principal parameters are captured by the low order eigenvectors of the diffusion matrix of the network ensemble. We validate our results by using two classical network ensembles and one dynamical network sequence via a cooperative Achlioptas growth process where an abrupt transition of the structures has been captured by our method. Our method provides a potential access to the pursuit of invisible control parameters of complex systems. [ABSTRACT FROM AUTHOR]

Highlights: [•] Whole-cell biocatalyst was used to catalyze the transesterification. [•] Study on reaction mode was performed for improving PG yield. [•] This study presented an ecofriendly and efficient way for propyl gallate production. [ABSTRACT FROM AUTHOR]

To date, there is no functional characterization of Em GGPPS (from Elizabethkingia meningoseptica sp.F2) as enzymes catalyzing GGPP. In this research, maltose-binding protein (MBP), disulfide bond A (DbsA), disulfide bond C (DbsC), and two other small protein tags, GB1 (Protein G B1 domain) and ZZ (Protein A IgG ZZ repeat domain), were used as fusion partners to construct an Em GGPPS fusion expression system. The results indicated that the expression of MBP- Em GGPPS was higher than that of the other four fusion proteins in E. coli BL21 (DE3). Additionally, using Em GGPPS as a catalyst for the production of GGPP was verified using a color complementation assay in Escherichia coli. In parallel with it, the enzyme activity experiment in vitro showed that the Em GGPPS protein could produce GGPP, GPP and FPP. Finally, we successfully demonstrated MK-4 production in engineered E. coli by overexpression of Em GGPPS. • Fusion expression of five tags (GB1, ZZ, MBP, DbsA, DbsC) with GGPPS was evaluated in two different E.coli strains. • Em GGPPS has been confirmed produces GPP, FPP and GGPP in vivo and in vitro assays. • The menaquinone-4 (MK-4) were first synthesized in E. coli under anaerobic conditions. [ABSTRACT FROM AUTHOR]

Chitin synthases catalyze the formation of β-(1,4)-glycosidic bonds between N-acetylglucosamine residues to form the unbranched polysaccharide chitin, which is the major component of cell walls in most filamentous fungi. Several studies have shown that chitin synthases are structurally and functionally divergent and play crucial roles in the growth and morphogenesis of the genus Aspergillus although little research on this topic has been done in Penicillium chrysogenum. We used BLAST to find the genes encoding chitin synthases in P. chrysogenum related to chitin synthase genes in Aspergillus nidulans. Three homologous sequences coding for a class III chitin synthase CHS4 and two hypothetical proteins in P. chrysogenum were found. The gene which product showed the highest identity and encoded the class III chitin synthase CHS4 was studied in detail. To investigate the role of CHS4 in P. chrysogenum morphogenesis, we developed an RNA interference system to silence the class III chitin synthase gene chs4. After transformation, mutants exhibited a slow growth rate and shorter and more branched hyphae, which were distinct from those of the original strain. The results also showed that the conidiation efficiency of all transformants was reduced sharply and indicated that chs4 is essential in conidia development. The morphologies of all transformants and the original strain in penicillin production were investigated by light microscopy, which showed that changes in chs4 expression led to a completely different morphology during fermentation and eventually caused distinct penicillin yields, especially in the transformants PcRNAi1-17 and PcRNAi2-1 where penicillin production rose by 27 % and 41 %, respectively. [ABSTRACT FROM AUTHOR]

Purpose: Previously, we demonstrated that heavy ions kill more cells at the same dose than X-rays because DNA-clustered lesions produced by heavy ions affect nonhomologous end-joining (NHEJ) repair but not homologous recombination repair (HRR). We have also shown that our designed artificial microRNAs (amiRs) could efficiently target XRCC4 (an essential factor for NHEJ) or XRCC2 (an essential factor for HRR) and sensitize human tumor cells to X-rays. Based on these data, we were interested in testing the hypothesis that combining heavy ions and amiRs to target HRR but not NHEJ should more efficiently kill human tumor cells. Methods and Materials: Human tumor cell lines (U87MG, a brain tumor cell line, and A549, a lung cancer cell line) and their counterparts, overexpressed with amiR to target XRCC2, XRCC4 or both, were used in this study. Survival sensitivities were examined using a clonogenic assay after these cells were exposed to X-rays or heavy ions. In addition, these cell lines were subcutaneously injected into nude mice to form xenografts and the tumor size was compared after the tumor areas were exposed to X-rays or heavy ions. Results: Although targeting either XRCC4 (NHEJ factor) or XRCC2 (HRR factor) sensitized the human tumor cells to X-rays, in vitro and the xenograft animal model, targeting only XRCC2 but not XRCC4 sensitized the human tumor cells to heavy ions in vitro and in the xenograft animal model. Conclusions: Combining heavy ions with targeting the HRR pathway, but not the NHEJ pathway, could significantly improve the efficiency of tumor cell death. [Copyright &y& Elsevier]

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]

Abstract: A bio-imprinting technique was applied to activate tannase in order to enhance its biocatalytic activity. Specifically, the effects of three bio-imprinting methods (i.e. substrate imprinting, pH imprinting, and interfacial imprinting) on the activating factor of tannase were investigated. The results show that bio-imprinting methods can activate tannase remarkably, and they were combined to develop a tannase biocatalyst with a 40% conversion rate of substrate, 100-fold higher than that of the control. This approach can be used to construct an effective way to produce propyl gallate as well as to exploit readily available tannic acid. The immobilized bio-imprinted tannase can catalyze the synthesis of propyl gallate from tannic acid by transesterification in organic media. This work not only presents an effective means of making use of various tannic acid-rich agro-forestry residues, but also broadens the field of applications of the bio-imprinting technique. [Copyright &y& Elsevier]

Abstract: This paper proves that the winning strategy for Hauser’s version of Hironaka’s polyhedra game is almost arbitrary. The winning strategy and its associated invariants are based on an algorithm of matrix triangulations and matrix diagonalizations. It is proved that if a set sequence constitutes a winning strategy for the game, then so does every set sequence containing it. The same holds for Hironaka’s version of the game if every move is permissible. [Copyright &y& Elsevier]

Abstract: In this paper, we present a new algorithm for computing local extrema by modifying and combining algorithms in symbolic and numerical computation. This new algorithm improves the classical steepest descent method that may not terminate, by combining a Sturm’s theorem based separation method and a sufficient condition on infeasibility. In addition, we incorporate a grid subdivision method into our algorithm to approximate all local extrema. The complexity of our algorithm is polynomial in a newly defined condition number, and singly exponential in the number of variables. [Copyright &y& Elsevier]

The published online version contains some errors. [ABSTRACT FROM AUTHOR]

Improving phosphorus (P) fertilizer efficiency while minimizing environmental impacts requires better understanding of the dynamics of applied P in soils. This study assessed the fate of fertilizer P applied in Quebec Humaquepts. A pot experiment with five textural Humaquepts, each receiving 0 (P0), 10 (P10), 20 (P20) and 40 (P40) mg P kg -1 soil was conducted under barley ( Hordeum vulgare L.)-soybean ( Glycine max L.) rotations. A modified Hedley procedure was used for soil P fractionation. The clayey soils reached a plateau of dry matter at less P applied than the coarser-textured soils. Plant P uptake, soil labile inorganic P (resin-P?+?NaHCO 3 -P i ) and moderately labile inorganic P (NaOH-P i ) increased proportionally with P rate. The coarser-textured soils had lower contents of labile and moderately labile P i , but a larger increase in labile P i than the finer-textured soils after receiving P additions. The applied P was retained primarily as soil labile P i , accounting for 43–69% of total soil recovery of applied P, compared to 20–30% recovered as moderately labile P i , and 7–29% assumed to be sparingly soluble P (HCl-P?+?H 2 SO 4 -P). The labile P i recovery of applied P was linearly depressed with clay content, compared to a quadratic relation for the moderately labile P i recovery. The results suggest the importance of accounting for soil texture along with soil P adsorption capacity when assessing the efficiency of applied P, P accumulation in soils and subsequently P nutrient management. [ABSTRACT FROM AUTHOR]

Supercritical flow in spherical Couette system with a rotating inner sphere and a fixed outer sphere has been investigated for a medium gap of the clearance ratio 0.206 in terms of the structure, wave-number, fundamental, and rotational frequencies of disturbances. Consequently, ring vortices and traveling letter-x-like waves were found within the Ekman-type secondary flow as new disturbances, in addition to Stuart vortices and shear waves. Also, interior waves were found within toroidal Taylor-Görtler (TG) vortices as a new disturbance, in addition to twists. Further, the wavy outflow boundary at the equator of the turbulent basic flow was found. Each ring vortex occurring successively around the pole moves toward the pole for one wavelength in the meridian direction (θ= 10°) while it rotates for one wavelength in the azimuthal direction (φ = 90°), because it has four traveling waves. The rotational direction of Stuart vortices is opposite to that of the inner sphere. The wave speed (rotation frequency) of interior waves or twists is the same as that of oscillating inflow boundary between two toroidal TG vortex cells, and the wave speed of shear waves is the same as that of the oscillating outflow boundary between the toroidal TG vortex cell and the Ekman-type secondary flow. Also, the wave speed of the oscillating outflow boundary is about two times the oscillating inflow boundary. [ABSTRACT FROM AUTHOR]

In the laminar-turbulent transition of spherical Couette flow with only the inner sphere rotating in the case of gap ratio 0.14, we have studied experimentally the evolution of mean and fluctuating velocities with increasing Reynolds number at two meridian angles, θ= 60° and 90° (the equator), respectively. For a reduced Reynolds number, R[sup *] = 1.2, the phase of a fluctuating velocity component in the main-flow direction advances radially inward from the outer to the inner sphere at θ=90°, but delays radially inward at θ=60°. When R[sup *] is 4.2 and 6.0, the phase slightly advances radially inward at θ=90°, but does not change so much at θ=60°. The phase-averaged profile of fluctuating velocity in the presence of spiral Taylor-Görtler (TG) vortices differs from that in the presence of traveling azimuthal waves. Spiral TG vortices make the amplitude of fluctuating velocity large in the central part of the gap. But traveling azimuthal waves make it large somewhat near the inner sphere. For the flow with spiral TG vortices and/or traveling waves at low R[sup *], the root-mean square value of fluctuating velocity tends to be large on the outer-sphere side at θ = 60°, while on the inner-sphere side at θ=90°. In the fully turbulent flow for R[sup *] ...20, the rms value of fluctuation velocity becomes large near the fixed outer sphere at both θ=60° and 90°, and log-laws on mean azimuthal velocity profiles hold there. [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 present paper aims to introduce the concept of weak-fuzzy contraction mappings in the graph structure within the context of fuzzy cone metric spaces. We prove some fixed point results endowed with a graph using weak-fuzzy contractions. By relaxing the continuity condition of mappings involved, our results enrich and generalize some well-known results in fixed point theory. With the help of new lemmas, our proofs are straight forward. We furnish the validity of our findings with appropriate examples. This approach is completely new and will be beneficial for the future aspects of the related study. We provide an application of integral equations to illustrate the usability of our theory. [ABSTRACT FROM AUTHOR]

• Proposed a novel maintenance cycle predictive framework for large energy equipment based data-oriented. • The multi-level adversarial domain adaptation model generated a feature subspace, ensuring the transfer foundation of degradation knowledge. • The federated learning strategy improved predictive performance with limited training samples while ensuring data security. Failures in natural gas compressor units can lead to significant production incidents that impact energy security, making intelligent preventative maintenance of this equipment critically important. Given the limited and sensitive data from critical energy equipment like natural gas compressor units, this paper conducts preventative maintenance research based on domain adaptation and federated learning (DFPM), and proposes a novel maintenance cycle prediction framework. The feasibility of the proposed method was validated through historical operational data from field natural gas compressor units, providing a data-oriented reference for maintenance decision-making. Verification results demonstrate that the proposed multi-level adversarial domain adaptation method possesses superior feature representation capability, enhancing the preservation of the original degradation trend for time series data compared to traditional DA models. The novel federated adversarial strategy presented in this paper can effectively transfer source domain knowledge to the target domain, further enhancing the cross-unit predictive performance of the target domain model with limited samples. Additionally, this strategy with the chaotic multi-mode predictive model further improves the limitations of low parallelism and efficiency in traditional RNN-based prediction models while ensuring data security. This research provides a new perspective for the intelligent operation and maintenance of large energy equipment, which is of significance in practical engineering. [ABSTRACT FROM AUTHOR]

• A facile and efficient approach was used to prepare magnetic nanocomposite. • The immobilized NovQ exhibits good tolerance towards pH and temperature. • Immobilized NovQ displays improved storage stability and reusability. • The nanoparticles occupy an inessential domain away from active center of NovQ. Prenyltransferase NovQ immobilized carboxymethyl cellulose magnetic nanoparticles (NCMNs) were successfully synthesized via a valuable approach integrated from nanocomposite preparation, and applied for the production of vitamin K 2 using menadione hydroquinol and dimethylallyl diphosphate (DMAPP) as substrates. To investigate the interaction between nanoparticles and NovQ, we characterized the nanocomposite, and revealed that carboxymethyl cellulose (CMC) and Fe 3 O 4 formed a core-shell structure to absorb NovQ in the reaction systems, resulting from the high affinity of immobilized materials. Meanwhile, NCMNs with excellent pH and temperature tolerance, enhanced prenylated activity, and improved stability were found. Molecular docking analysis was also conducted to justify the contribution of multiple amino acids and effect of nanoparticles on catalytic properties of NovQ. Taken together, our study introduces a promising strategy to prepare magnetic nanoparticles and improve the performance of catalyst, which aims for opening new orientations for synthesis of magnetic nanoparticles used for prenyltransferase immobilization. [ABSTRACT FROM AUTHOR]

To remove the impacts of polarization interference on satellite-to-ground high-speed data transmission systems, the major factors that affect polarization interference are concluded, the deteriorations of bit error rate (BER) of different modulation systems and channel coding modes are simulated, and the parallel adaptive filtering technology is presented to resolve the high symbol-rate signal transmission polarization interference. It has been verified by experiments that the effects of this method is remarkable. In the situation of QPSK system, 500MSPS symbol rate and 10 dB polarization isolation, the BER performance can be improved 4.5 dB by using this method. [ABSTRACT FROM AUTHOR]

The stability of random Boolean networks (RBNs) has aroused continuous attention due to its profound applications in genetic regulatory. With extensive research on the joint influence of network topology and update rules, the interaction between RBN stability and other dynamic processes remains to be investigated. In this paper we propose an interactive multiplex model and study the dynamical interplay between RBN stability and awareness propagation. Theoretical analysis reveals that the stability of RBN is enhanced by awareness propagation. Specifically, its transition point between stable and unstable phases is determined by the main eigenvalue of H , which is closely related to the prevalence of awareness propagation and coupling strength between two layers. In addition, we illustrate the existence of a meta-critical point, from which awareness propagates and thus inhibits chaotic behaviors in RBN. Our work sheds light on the interaction between RBN stability and awareness propagation, and provides theoretical guidance to intervention of real Boolean systems. • The dynamical interplay between RBN stability with awareness propagation is investigated in a multiplex model. • The stability of RBN layer is affected by the prevalence of awareness propagation and coupling strength between two layers. • The transition point between stable and unstable phases is determined by matrix H. • Awareness propagation defines a meta-critical point from which RBN stability is enhanced. [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]

In this paper, we present some weakly compatible and quasi-contraction results for self-mappings in fuzzy cone metric spaces and prove some coincidence point and common fixed point theorems in the said space. Moreover, we use two Urysohn type integral equations to get the existence theorem for common solution to support our results. The two Urysohn type integral equations are as follows: x (l) = ∫ 0 1 K 1 (l , v , x (v)) d v + g (l) , y (l) = ∫ 0 1 K 2 (l , v , y (v)) d v + g (l) , where l ∈ [ 0 , 1 ] and x , y , g ∈ E , where E is a real Banach space and K 1 , K 2 : [ 0 , 1 ] × [ 0 , 1 ] × R → R . [ABSTRACT FROM AUTHOR]

Purpose: Metamodeling is an effective method to approximate the relations between input and output parameters when significant efforts of experiments and simulations are required to collect the data to build the relations. This paper aims to develop a new sequential sampling method for adaptive metamodeling by using the data with highly nonlinear relation between input and output parameters. Design/methodology/approach: In this method, the Latin hypercube sampling method is used to sample the initial data, and kriging method is used to construct the metamodel. In this work, input parameter values for collecting the next output data to update the currently achieved metamodel are determined based on qualities of data in both the input and output parameter spaces. Uniformity is used to evaluate data in the input parameter space. Leave-one-out errors and sensitivities are considered to evaluate data in the output parameter space. Findings: This new method has been compared with the existing methods to demonstrate its effectiveness in approximation. This new method has also been compared with the existing methods in solving global optimization problems. An engineering case is used at last to verify the method further. Originality/value: This paper provides an effective sequential sampling method for adaptive metamodeling to approximate highly nonlinear relations between input and output parameters. [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]

Models of contagion dynamics, originally developed for infectious diseases, have proven relevant to the study of information, news, and political opinions in online social systems. Modelling diffusion processes and predicting viral information cascades are important problems in network science. Yet, many studies of information cascades neglect the variation in infectivity across different pieces of information. Here, we employ early-time observations of online cascades to estimate the infectivity of distinct pieces of information. Using simulations and data from real-world Twitter retweets, we demonstrate that these estimated infectivities can be used to improve predictions about the virality of an information cascade. Developing our simulations to mimic the real-world data, we consider the effect of the limited effective time for transmission of a cascade and demonstrate that a simple model of slow but non-negligible decay of the infectivity captures the essential properties of retweet distributions. These results demonstrate the interplay between the intrinsic infectivity of a tweet and the complex network environment within which it diffuses, strongly influencing the likelihood of becoming a viral cascade. [ABSTRACT FROM AUTHOR]

In this paper, we study targeted immunization in a multilayer Boolean network model for genetic regulatory networks. Given a specific set of nodes immune to perturbations, we find that the stability of a multilayer Boolean network is determined by the largest eigenvalue of the weighted non-backtracking matrix of corresponding aggregated network. Aimed to minimize this largest eigenvalue, we developed the metric of multilayer collective influence (MCI) to quantify the impact of immunizing individual nodes on the stability of the system. Compared with other competing heuristics, immunizing nodes with high MCI scores can stabilize an unstable multilayer network with higher efficiency on both synthetic and real-world networks. Moreover, despite that coupling nodes can exert direct influence across multiple layers, they are found to exhibit less importance as measured by the MCI score. Our work reveals the mechanism of maintaining the stability of multilayer Boolean networks and provides an efficient targeted immunization strategy, which can be potentially applied to the location of pathogenesis of diseases and the development of targeted therapy. [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]

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]

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]

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]