Fuzzy implication,as a critical logical connective,holds substantial research significance for its construction and characteriza-tion within the domain of fuzzy logic.In this paper,we first construct a novel class of fuzzy implications,termed(ξ,s)-generated implica-tions,by employing a pair of multiplicative and additive generators derived from triangular conorms.Secondly,we investigate the funda-mental properties of this new class of implications.Finally,we examine the relationships between the(ξ,s)-generated implications and other established classes of fuzzy implications,including Yager-,h-,k-,(θ,t)-,(S,N)-and R-implication.The results indicate that the(ξ,s)-generated implications distinctly differ from these known types.
In the field of image denoising,the non-local self-similarity(NSS)prior has been widely validated.By exploiting the similar structural details within groups of similar patches to effectively extract redundant information,it significantly improves the accuracy and quality of image restoration.This method can well preserve textures and edges while removing noise.However,NSS-based methods have certain limitations.They usually process patch groups as a whole and neglect the differences among patches within a group.In addition,constructing similar patch groups using NSS is challenging for highly noisy images,suffering from problems such as scarce similar patches and low similarity.To address these issues,this paper proposes an image denoising model with multi-scale group sparse representation based on weighted log-sum penalty.Based on the original-scale image,a multi-scale image sequence is constructed via upsampling and downsampling operations,which not only generates a large number of similar image patches at each individual scale to expand the overall pool of patch candidates,but also excavates structurally correlated similar patches across different scales through a cross-scale patch matching strategy,thus effectively enhancing the inter-patch similarity.Especially for images with high noise intensity,original image patches are severely disturbed by noise,making it difficult to find a sufficient number of highly similar matching patches at a single scale.In contrast,multi-scale construction can weaken the concentrated impact of noise at a single scale,highlight the inherent structural features of the image at other scales,help select more representative similar patch groups,and alleviate the core problems of scarce similar patches and insufficient similarity in high-noise scenarios.Experimental results demonstrate that the proposed MSGSR-Log model outperforms the state-of-the-art methods.
To investigate the embryonic and larval developmental characteristics of Leiocassis longirostris(L.longirostris)and determine the Point of No Return(PNR)of starved larvae,fertilized eggs were cultured in a recirculating glass aquarium maintained at a water tem-perature of(24.5±0.5)℃.Respectively,the chronological characteristics of embryonic and larval development were observed under a mi-croscope,and starvation experiments were conducted on newly hatched larvae to study their morphological development,growth traits,and feeding capacity.The results indicated that the fertilized eggs of L.longirostris reached a diameter of(3.46±0.16)mm after water ab-sorption and swelling,and the embryonic incubation period was 68-70 h.Embryonic development was observed to progress through eight consecutive stages:fertilized egg,cleavage,blastula,gastrula,neurula,organogenesis,pre-hatching,and hatching.Subsequently,we ob-served that newly hatched larvae undergo three distinct developmental phases before initial feeding:the appearance of body pigments,the formation of the intestinal tract,and the first coiling of the intestinal tube.Thereafter,results from the larval starvation experiment indi-cated that L.longirostris larvae relied on endogenous nutrition within the first 4 days post-hatching(dph).Initial feeding occurred at 5 dph,with a feeding rate of(63.33±2.89)%,marking the onset of the mixed nutritional stage.By 9 dph,the yolk sac was fully absorbed,and the larvae transitioned to exclusive exogenous nutrition.Moreover,the feeding rate remained at 100%from 8 to 11 dph,followed by a decline.The PNR was identified at 16 dph.Subsequently,complete starvation-induced mortality occurred between 16 and 17 dph.Thus,the opti-mal initial feeding time for L.longirostris larvae is recommended to be 5 dph.In summary,the findings of this study provide fundamental data on the early developmental stages of L.longirostris,which has significant practical implications for improving larval rearing effi-ciency in aquaculture.
Limnoperna fortunei(L.fortunei)is a major fouling organism in hydraulic systems,where chemical control remains a com-mon practice.This study evaluated the molluscicidal efficacy and mechanisms of eight chemical agents including copper sulfate(CuSO4),chloramine,sodium hypochlorite(NaClO),salicylic acid,glyphosate,chitosan-based flocculant,nicotinoyl aniline sulfate(C12H10N2O·H2SO4,abbreviated as NS)and polyquaternium.The results show that the order of toxicity from high to low was NS>CuSO4>NaClO>polyquaternium>salicylic acid>glyphosate>chloramine>chitosan-based flocculant.Notably,NS(2 mg/L),CuSO4(1 mg/L),and NaClO(3 mg/L)each achieved over 73%mortality of L.fortunei.Enzymatic activity analysis revealed distinct response patterns.NS caused sustained increases in superoxide dismutase(SOD)and glutathione-S-transferase(GST),malondialdehyde(MDA)increased sig-nificantly at 70%mortality,succinate dehydrogenase(SDH)were all below the control group,while acetylcholinesterase(AChE)slightly increased and then decreased.CuSO4 induced continuous SOD increase,fluctuated MDA and GST levels,similar inhibition of SDH to NS,elevated AChE at 50%mortality.NaClO resulted in moderate SOD increase,severe MDA accumulation,an initially GST increase and then decrease,elevated SDH at 70%mortality,and higher AChE at 50%mortality.These results suggest that NS and CuSO4 suppress the physiological activity of L.fortunei primarily through oxidative stress and mitochondrial inhibition,whereas NaClO acts directly via membrane damage and oxidative injury at late stage.Histological examination of gills and gonads at 50%and 70%mortality revealed that NS triggered gill structural abnormalities and gonad atroph,CuSO4 caused gill atrophy and gonad cavitation,NaClO induced only mi-nor changes at 50%mortality but major gill cell loss and gonad nuclear disappearance at 70%mortality.The results of HE showed that all three chemical agents caused structural disorder of the gill filaments,gonadal atrophy and cavitation,and even disappearance of nuclei in L.fortunei,leading to significant tissue damage.These findings provide theoretical basis for selecting effective chemical controls includ-ing NS,CuSO4 and NaClO against L.fortunei in hydraulic and enclosed infrastructure.
In the context of rapid advancements in laser scanning technology,the scale of point cloud data acquisition has increased sig-nificantly.Existing registration algorithms face escalating computational costs when processing medium-and large-scale point clouds,which severely impairs registration efficiency.To address this issue,we propose an enhanced registration framework based on Fast Point Feature Histogram(FPFH)that incorporates dynamic downsampling and adaptive neighborhood optimization.Specifically,the global aver-age point spacing is first computed to guide the downsampling process.Subsequently,the FPFH neighborhood radius is dynamically ad-justed according to this global average spacing.Experimental results on two datasets indicate that our approach maintains robust accuracy while cutting computation time by approximately 55%compared with the standard FPFH algorithm for medium-and large-scale clouds.Furthermore,compared with the traditional 3D Shape Context(3DSC)algorithm,our approach requires less than 10%of the processing time and achieves significantly higher registration precision.
Sulfamethoxazole(SMX)and other antibiotics pose significant risks to humans and the environment even at trace concentra-tions,whereas conventional physicochemical and biological degradation methods are often ineffective.This study employed an integrated strategy combining photocatalysis with heterogeneous Fenton technology for SMX removal,and compared the removal efficiency of the UV-H2O2 and the UV-zeolite-supported Cu/Mn bimetallic heterogeneous Fenton method.The results demonstrate that the catalytic activity is primarily influenced by the calcination temperature,followed by the calcination time and the Cu/Mn molar ratio in the impregnation solu-tion.The optimal catalyst is prepared with a Cu/Mn molar ratio of 2∶1 and calcined at 300℃for 3 h.In the catalyst,copper and manga-nese exist primarily as CuO,Cu2O,Cu/Mn oxides,and MnO2/Mn3O4.At pH=7.2 and an initial SMX concentration of 20 mg/L,the opti-mized UV-Cu/Mn-zeolite heterogeneous Fenton system with 0.15 g/L catalyst and 7.5 mmol/L H2O2 achieved a 77.3%SMX removal rate.This represents a 15.1%improvement over the conventional UV-H2O2 process,and the degradation follows pseudo-first-order kinetics.Metal leaching remained below 0.5 mg/L after 90-min reaction,and the catalyst lost less than 5%of its initial activity after four reuse cycles.
In this paper,a model of branching processes with migration and affected by viral infectivity in independent and identically dis-tributed(i.i.d.)random environments is established firstly.Then the Markov property,conditional probability generating function and con-ditional expectation of the model are studied.Finally,under certain conditions,some sufficient conditions for certain extinction of pro-cesses are given,and some related theories of branching processes in random environments are generalized.
The predation mechanism of invertebrates(e.g.,Tortanus dextrilobatus)on plankton in aquatic population ecosystem is a significant research topic.In this paper,the interaction between invertebrates and plankton is simulated by a modified Leslie-Gower predator-prey model.Using the theory of reaction-diffusion equations,a priori estimate,existence,uniqueness and stability conditions of the positive steady state solution are established.Furthermore,numerical simulations are conducted to quantitatively analyze the dynamical behavior.The research shows that as long as the Allee effect constant satisfies the appropriate relationship and the growth rates of predator and prey are appropriately large,the predator and prey can not only coexist,but also the coexistence mode is unique and stable under low predation-rate.In addition,the numerical simulations show that the coexistence may be stable under high predation-rate.Meanwhile,with the increase of predation rate,the population density of predators will decrease.
The purpose of this paper is to investigate the generators and relations for little q -Schur superalgebra [see formula in PDF]. The basis of [see formula in PDF] is obtained through the Poincaré-Birkhoff-Witt (PBW) basis of q -Schur superalgebra [see formula in PDF], then we present a new set for generators and relations for [see formula in PDF] by PBW basis.
To quantitatively analyze the physical and biological dynamics of terrestrial organic carbon(TOC),phytoplankton,and zoo-plankton,and to clarify the relationship between global stability and the input TOC concentration,this paper proposes a mathematical model for aquatic ecosystems.The interactive dynamics are analyzed by using Hurwitz's criterion,LaSalle's invariance principle,and ap-propriate Lyapunov functions.Key results show that the phytoplankton-free equilibrium is globally asymptotically stable at high input TOC concentrations.In contrast,the coexisting equilibrium exhibits global asymptotic stability under low input TOC conditions.These theoretical findings are validated by numerical simulations,highlighting the importance of monitoring and regulating input TOC concentra-tions to preserve biodiversity.
Antibiotic resistance genes(ARGs)are emerging environmental contaminants that pose significant threats to public health due to their persistence,migration and dissemination in aquatic environments.This review systematically summarized the mechanisms of ARG resistance,their spread in human and animal populations,and primary input pathways into water bodies,including medical and aquaculture wastewater.Key environmental drivers of ARG evolution and dissemination are analyzed,encompassing selective pressures from antibiot-ics and heavy metals,horizontal gene transfer mediated by mobile genetic elements,and physicochemical factors such as dissolved oxy-gen,pH,and nutrient levels.Finally,current research gaps are highlighted,and future directions are proposed for monitoring and control-ling ARG transmission,and assessing associated health risks under the One Health framework.This review provides a scientific basis for understanding the ARG crisis in aquatic environments and guiding integrated management strategies.
The past few decades witnessed a significant increase in the incidence of thyroid cancer worldwide.Hürthle cell carcinoma(HCC),which was also known as oncocytic carcinoma of the thyroid,was reclassified as a distinct histological type of thyroid cancer by the WHO in 2022.Although HCC has a relative poorer prognosis and is generally insensitive to radioiodine treatment,the mechanisms be-hind HCC are poorly understood currently.In this paper,ioinformatics methods were employed to identify differentially expressed proteins(DEPs)and to analyze their functions in disease.R project was used to identify DEPs in HCC and Hürthle cell adenoma(HCA)with data from the iProx database.DEPs were annotated using the DAVID tool.Protein-protein interaction networks were constructed and visualized using the STRING database and the Cytoscape software.NetworkAnalyst was used to explore the relationships of DEPs,transcription fac-tors,diseases,and drugs.The predicting ability of DEPs were evaluated with receiver operating characteristic(ROC)curves.Three DEPs with best performance were validated using immunohistochemistry.Experimental results show that a total of 793 and 295 DEPs were iden-tified in HCC-normal and HCA-normal comparisons,respectively.The common DEPs of the two comparisons included ATP5F1A,ATP5F1B,UQCRFS1,ATP5F1D,ATP5F1C,COX5A,ATP5PD,ATP5PO,SUCLG1,and ACO2.The ROC analysis showed that ATP5F1B,ATP5F1C,and ATP5PD demonstrated the highest diagnostic accuracy,as indicated by their area under the curve(AUC)values,highlighting their superior performance.Immunohistochemistry confirmed the upregulation of the three proteins in HCC.Differential ex-pression analysis revealed DEPs as potential biomarkers for HCC and HCA.Notably,the most dysregulated proteins are generally in-volved in the assembly of complex V,indicating a potential association between oxidative phosphorylation and the carcinogenesis of HCC.
The increasing prevalence of cardiovascular and cerebrovascular diseases in recent years has brought thrombolytic drugs into the focus of researchers, drug makers, and the general public alike. Nattokinase (NK), an alkaline serine protease secreted by Bacillus subtilis natto , exhibits strong thrombolytic activity, reduces blood viscosity, and enhances blood vessel elasticity. With its advantages of high stability, good absorption, long half-life, low cost and fewer side effects, it is considered an ideal natural medicine for preventing and treating blood clots, with promising potential in the field of health food development. This review systematically summarizes research on nattokinase relating to its physicochemical properties, thrombolytic and anticoagulant mechanisms, physiological function, fermentation technology, activity determination, and isolation and purification methods, as well as the latest research on the targeted delivery system of nattokinase. Furthermore, we elaborate on the key future research directions of NK, involving strain optimization, purification technology upgrade, targeted delivery improvement and clinical application verification, in order to provide theoretical support for in-depth research in this field and its application.
The newly-issued 2025 policy on deepening the market-oriented reform of new energy feed-in tariffs has exerted a profound impact on reshaping the development pattern of new energy industries, such as photovoltaic power. In this evolving context, collaborative grid-connection among photovoltaic power generation enterprises, power grid enterprises, and government agencies is crucial for enhancing the competitiveness of the new energy industry and achieving energy transition. This paper constructs a tripartite evolutionary game model to deeply explore the strategy selection and key influencing factors of each subject in the grid-connection process. It integrates large language models (LLMs) to analyze factors affecting strategy selection among different stakeholders and utilizes LLMs to capture the heterogeneous cognitive characteristics of different subjects, thereby overcoming the limitations of "strong assumptions" commonly found in traditional game models. Through multi-round semantic parsing, it identifies key influencing factors such as market-oriented electricity price fluctuations, technological innovation costs, and assessment penalty. Furthermore, based on the actual data of photovoltaic industry development in Jiangxi and Hubei Provinces, numerical simulations are employed to analyze the impact of key factors (e.g., market-oriented electricity price fluctuations) on the strategic choices of the three stakeholder parties under the new policy framework and verify the model's effectiveness. The study clarifies the critical thresholds affecting collaborative grid connection, providing a data-driven theoretical basis for the government to implement targeted policies and enterprises to optimize decision-making.
The order r of an element a in the multiplicative group(Z/nZ)*,denoted by order(a,n),or la(n)for short,plays a significant role in the period of certain pseudo-random number generators and is particularly important in Shor's quantum integer factorization algorithm,as well as in various cryptographic applications.In this paper,we present some numerical results and evidence of suitable a for which la(n)are small and relatively easy to obtain,in the light of quantum integer factorization.The results indicate that the higher the order,the larger of the number of a.Therefore,we propose a quantum algorithm for finding a in a2k≡ 1(mod n)with k≥1,explicitly excluding the trivial solution a≡ 1(mod n),based on Grover's search,but using fewer quantum bits.Moreover,the proposed algorithm achieves a success probability close to 1.As this type of n is commonly used as an RSA modulus,once such an a is found,RSA cryptographic system will be broken.
The injection ring is a critical component for supplying fuel to the combustion chamber of an engine. The performance of the engine is directly affected by the uniformity of the outlet fuel flow distribution of the nozzle. To address the issue of the uneven outlet fuel flow distribution of nozzles of the injection ring, this paper uses the ANSYS Fluent for numerical simulations. The fuel flow values at each nozzle outlet of the injection ring and the pressure drop between the inlet and outlet were calculated, and the influence of inlet flow and nozzle inner diameter on the fuel flow distribution and the pressure drop between the inlet and outlet were analyzed. The research results indicate that reducing the nozzle inner diameter and increasing the inlet flow lead to a more uniform fuel flow distribution at the nozzle outlets. Additionally, decreasing the nozzle inner diameter increases the pressure drop between the inlet and outlet. The Leiting LT70 micro-turbojet engine discussed in this paper is compatible with an injection ring with a nozzle inner diameter of 600 μm.
This paper investigates the existence of ground state solutions to the following nonlinear Schrödinger-Poisson system by varia-tional methods{-△u+ωu+V(x)u+eϕu=|u|p-2u,x∈R3,△ϕ=e/2(u2-ρ(x)),x∈R3,provided that ρ(x)≥0 and e2‖ρ‖6/5≤ρ0 with ρ0>0 small enough,where 40 denotes a coupling constant,ω>0 is a Lagrange multiplier,the potential V(x)is coercive and the doping profile ρ(x)satisfies ap-propriate decay conditions.The introduction of ρ(x)compromises the coercivity of the energy functional.Therefore,we establish the exis-tence of ground state solutions by considering the minimization problem on Nehari manifold.
In this paper, we prove the global existence of strong solutions to a two-dimensional (2D) Keller-Segel-Navier-Stokes system with subcritical sensitivity in a bounded domain. Using energy methods, interpolation inequalities and the Gronwall lemma, we establish uniform a priori estimates for the solutions. We prove the existence and uniqueness of global strong solutions under appropriate initial conditions, along with higher-order Sobolev regularity of solutions. The result extends existing conclusions and enriches the global well-posedness theory for chemotaxis-fluid coupled models.
In the field of mathematical analysis,the Monotone Convergence Theorem(MCT),Fatou's lemma,and the Dominated Conver-gence Theorem(DCT)play a crucial role in the study of the interchangeability of limits and integrals(or norms).Among them,the DCT when applied to series of numbers,namely Tannery's theorem,has been explored to a certain extent.However,the MCT and Fatou's lemma related to series of numbers still lack in-depth research in existing literature.This paper proposes and proves Fatou's lemma and the MCT in ℓ∞ space.By constructing counterexamples,it demonstrates that the DCT does not hold in ℓ∞ space.In the research of series of numbers,this paper uses the property of the infimum of real numbers to prove Fatou's lemma for series of numbers.Taking this as a theo-retical foundation,it further derives the MCT and the DCT related to series of numbers.Through an in-depth analysis of the logical rela-tionships among these three theorems,an equivalence relation among them is established,and their application values in practical prob-lems are demonstrated through examples.In addition,based on the theory of abstract measure and integration,the proofs of the three theo-rems related to series of numbers are provided.It is particularly worth noting that the classical Fatou's lemma and the MCT usually require that the corresponding sequence of functions satisfies the prerequisite of being non-negative and measurable.However,Fatou's lemma and the MCT in ℓ∞ space no longer impose the non-negativity requirement on the sequence of functions.This characteristic may have potential application prospects.
Diabetic nephropathy(DN)begins with diabetes-related disruptions in glucose metabolism,with oxidative stress playing a cru-cial role.Neutrophil extracellular traps(NETs)are extensive web-like formations composed of cytosolic and granule proteins,which are dependent on oxidative stress for their formation and function.This study aimed to identify potential targets for DN progression,focusing on NETs,using bioinformatic analysis and quantitative Real-Time PCR(qRT-PCR).We performed differential gene expression(DEG)analysis on two DN-related RNA-seq datasets(GSE142025 and GSE163603)and NETs-related genes.Subsequent analysis included gene set enrichment analysis(GSEA),gene set variation analysis(GSVA),GeneMANIA,and receiver operating characteristic(ROC)curves.Immune cell infiltration levels were assessed via single-sample GSEA,and a regulatory network involving RNA-binding proteins(RBPs)and their associated target mRNA was constructed.qRT-PCR was conducted on high glucose(HG)-treated and control HK-2 cells.Our analysis identified a set of 22 hub genes through the intersection of differentially expressed genes(DEGs)with NETs-related genes.Im-mune infiltration assessments revealed significant differences across 23 immune cell types among the analyzed groups.Hub genes includ-ing calcineurin-like phosphoesterase domain-containing 1(CPPED1)showed high diagnostic values(AUC over 0.6).qRT-PCR indicated reduced gene expression levels.In summary,this study identified 22 significantly upregulated DEGs that play a vital role in DN by using gene expression omnibus(GEO)database,GSEA,GSVA,immune infiltration analysis and ROC.The expression levels of CPPED1 may serve as novel diagnostic biomarkers and therapeutic targets.
