Comparison of Interruption in Relatively Formal and Informal Talk Show Programs

Interruption,as a linguistic phenomenon,can be see everywhere.And talk show programs are common setting for interruptions.So in this thesis three questions are addressed as followed:What function does the interruption have in these two kinds of talk shows(relatively formal and informal) respectively;what are the similarities of relatively formal and informal talk show programs;what are the differences between relatively formal and informal talk shows.

Integral Sequences of Infinite Length Whose Terms Are Relatively Prime

It is given in Weil and Rosenlicht ([1], p. 15) that (resp. 2) for all non-negative integers m and n with m≠n if c is any even (resp. odd) integer. In the present paper we generalize this. Our purpose is to give other integral sequences such that G.C.D.(ym,yn)=1 for all positive integers m and n with m≠n. Roughly speaking we show the following 1) and 2). 1) There are infinitely many polynomial sequences such that G.C.D.(fm(a),fn(a))=1 for all positive integers m and n with with m≠n and infinitely many rational?integers a. 2) There are polynomial sequences such that G.C.D.(gm(a,b),gn(a,b))=1 for all positive integers m and n with m≠n and arbitrary (rational or odd) integers a and b with G.C.D.(a,b)=1. Main results of the present paper are Theorems 1 and 2, and Corollaries 3, 4 and 5.

Structure of Relatively Accelerating Universe

This article is about the structure of expanding universe. Here I am trying to create a structural model of universe according to my thoughts. Studies showthat universe is accelerating its rate of expansion. Here I am trying to get some conclusions according to my thoughts. In my opinion, our universe is under a gravitational frame with all the matters in it. In this gravitational frame of universe we can consider our universe as a closed system and the empty space outside the frame as an open system. There are two possibilities we can find. One is relative motion of the objects inside the frame. By this way we can feel the universe is accelerating its expansion, but it is not. Another one is the vacuum energy absorption and negative pressure inside the frame. According to this thought, we can say that universe is accelerating and it can continue its motion at present conditions on it, even the force created by the big bang is decreasing. The other point is that, once the absorbed vacuum can create a negative pressure inside the frame, there is no need for the concept of dark energy in our universe [1]. According to this model, negative pressure inside the frame will be created by the absorbed vacuum from the space. So the existence of dark energy can be questioned. In this model, dark energy doesn't play any role in the expansion or rate of acceleration on the expansion of universe. So the dark energy doesn’t exist in this model. During the absorption of vacuum to the frame, it will increase the volume of the frame. It will create free spaces inside the frame to accommodate the vacuum inside the frame. The rest of the absorbed vacuum will move to the center of the frame by the action against gravity and the force created by the big bang. It will increase the density of the absorbed vacuum in the center and can create the negative pressure on the frame to pull it outside to the empty space. It will cause the acceleration on expansion of universe. These things are explained deeply in this article. And here it also explains the destiny of universe according to the frame and expansion of universe.

Research on Model of Guiding Rural Residents' Relatively Centralized Residence——A Case Study of Chongqing City

On the basis of expounding the status quo of rural residents' residence, the thesis notes that influenced by the weak foundation of rural economy, the characteristic of mountain landscape, smallholder consciousness, shortage of capital and other factors, the rural residents in Chongqing City mainly live scattered. In addition to opportunities of the expansion and drive of city, rural market development, rural resources development, rural industrial development, and rural ecological migration, the model of urban development promotion, the model of market development drive, the model of land development drive, the model of rural industry construction and the model of resettlement and reconstruction are advocated in order to guide the rural residents to adopt relative centralized residence. The suggestions concerning guiding rural residents' relative centralized residence are put forward as follows: firstly, act according to circumstances and conduct scientific planning and design; secondly, propagate extensively and activate famers' willingness; thirdly, first experiment and exert the exemplary guide; fourthly, perfect policy and guarantee farmers' benefit; fifthly, strengthen leadership and decrease the risk of centralized residence; sixthly, boost gradually and realize moderate centralized residence.

A Joint Entity Relation Extraction Model Based on Relation Semantic Template Automatically Constructed

The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of defining the semantic template of relation manually is particularly prominent in the extraction effect because it can obtain the deep semantic information of relation.However,this method has some problems,such as relying on expert experience and poor portability.Inspired by the rule-based entity relation extraction method,this paper proposes a joint entity relation extraction model based on a relation semantic template automatically constructed,which is abbreviated as RSTAC.This model refines the extraction rules of relation semantic templates from relation corpus through dependency parsing and realizes the automatic construction of relation semantic templates.Based on the relation semantic template,the process of relation classification and triplet extraction is constrained,and finally,the entity relation triplet is obtained.The experimental results on the three major Chinese datasets of DuIE,SanWen,and FinRE showthat the RSTAC model successfully obtains rich deep semantics of relation,improves the extraction effect of entity relation triples,and the F1 scores are increased by an average of 0.96% compared with classical joint extraction models such as CasRel,TPLinker,and RFBFN.

The chemical characteristics of different sodium iron ethylenediaminetetraacetate sources and their relative bioavailabilities for broilers fed with a conventional corn‑soybean meal diet

Background Our previous studies demonstrated that divalent organic iron(Fe)proteinate sources with higher complexation or chelation strengths as expressed by the greater quotient of formation(Qf)values displayed higher Fe bioavailabilities for broilers.Sodium iron ethylenediaminetetraacetate(NaFeEDTA)is a trivalent organic Fe source with the strongest chelating ligand EDTA.However,the bioavailability of Fe when administered as NaFeEDTA in broilers and other agricultural animals remains untested.Herein,the chemical characteristics of 12 NaFeEDTA products were determined.Of these,one feed grade NaFeEDTA(Qf=2.07×10^(8)),one food grade NaFeEDTA(Qf=3.31×10^(8)),and one Fe proteinate with an extremely strong chelation strength(Fe-Prot ES,Qf value=8,590)were selected.Their bioavailabilities relative to Fe sulfate(FeSO_(4)·7H_(2)O)for broilers fed with a conventional corn-soybean meal diet were evaluated during d 1 to 21 by investigating the effects of the above Fe sources and added Fe levels on the growth performance,hematological indices,Fe contents,activities and gene expressions of Fe-containing enzymes in various tissues of broilers.Results NaFeEDTA sources varied greatly in their chemical characteristics.Plasma Fe concentration(PI),transferrin saturation(TS),liver Fe content,succinate dehydrogenase(SDH)activities in liver,heart,and kidney,catalase(CAT)activity in liver,and SDH mRNA expressions in liver and kidney increased linearly(P<0.05)with increasing levels of Fe supplementation.However,differences among Fe sources were detected(P<0.05)only for PI,liver Fe content,CAT activity in liver,SDH activities in heart and kidney,and SDH mRNA expressions in liver and kidney.Based on slope ratios from multiple linear regressions of the above indices on daily dietary analyzed Fe intake,the average bioavailabilities of Fe-Prot ES,feed grade NaFeEDTA,and food grade NaFeEDTA relative to the inorganic FeSO_(4)·7H_(2)O(100%)for broilers were 139%,155%,and 166%,respectively.Conclusions The bioavailabilities of organic Fe sources relative to FeSO_(4)·7H_(2)O were closely related to their Qf values,and NaFeEDTA sources with higher Qf values showed higher Fe bioavailabilities for broilers fed with a conventional corn-soybean meal diet.

Tunable dispersion relations manipulated by strain in skyrmion-based magnonic crystals

We theoretically investigate the propagation characteristics of spin waves in skyrmion-based magnonic crystals. It is found that the dispersion relation can be manipulated by strains through magneto-elastic coupling. Especially, the allowed bands and forbidden bands in dispersion relations shift to higher frequency with strain changing from compressive to tensile,while shifting to lower frequency with strain changing from tensile to compressive. We also confirm that the spin wave with specific frequency can pass the magnonic crystal or be blocked by tuning the strains. The result provides an advanced platform for studying the tunable skyrmion-based spin wave devices.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Understanding the Relationship Between Shrinking Cities and Land Prices:Spatial Pattern,Effectiveness,and Policy Implications

Urban shrinkage has emerged as a widespread phenomenon globally and has a significant impact on land,particularly in terms of land use and price.This study focuses on 2851 county-level cities in China in 2005–2018(excluding Hong Kong,Macao,Taiwan,and‘no data’areas in Qinhai-Tibet Plateau)as the fundamental units of analysis.By employing nighttime light(NTL)data to identify shrinking cities,the propensity score matching(PSM)model was used to quantitatively examine the impact of shrinking cities on land prices,and evaluate the magnitude of this influence.The findings demonstrate the following:1)there were 613 shrinking cities in China,with moderate shrinkage being the most prevalent and severe shrinkage being the least.2)Regional disparities are evident in the spatial distribution of shrinking cities,especially in areas with diverse terrain.3)The spatial pattern of land price exhibits a significant correlated to the economic and administrative levels.4)Shrinking cities significantly negatively impact on the overall land price(ATT=–0.1241,P<0.05).However,the extent of the effect varies significantly among different spatial regions.This study contributes novel insights into the investigation of land prices and shrinking cities,ultimately serving as a foundation for government efforts to promote the sustainable development of urban areas.

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

Hard life for sons in the nest?Sex-dependent offspring mortality in Great Tits in urban and forest areas

Sex-biased mortality can occur in birds during development,for example due to sexual differences in energy requirement and/or environmental sensitivity,or the effects of sex hormones or sex differences in the expression of mutations linked to sex chromosomes.The extent of sex-bias in mortality may also be related to environmental conditions that influence offspring development and survival.Urban areas often provide poorer conditions for nestling development resulting in higher offspring mortality compared to natural areas,which may accelerate sex differences in offspring mortality in cities.To test this hypothesis,we examined the sex ratio of dead offspring in Great Tits(Parus major),using 427 samples of unhatched eggs and dead nestlings collected in two urban and two forest sites between 2013 and 2019.The ratio of males in the whole sample of dead offspring(56.9%)was significantly higher than expected by an 1:1 ratio,and the strongest sex biases were detected in urban areas(57.6%males)and in young nestlings(<14 days old,59.0%males).However,the sex ratios of dead offspring did not differ significantly among study sites and between offspring developmental stages.29.3%of unhatched eggs contained a visible embryo,and the proportion of embryo-containing unhatched eggs did not differ significantly between urban and forest study sites.These results suggest male-biased offspring mortality in Great Tits,and highlight the need of large datasets to detect subtle differences between habitats and developmental stages.

Relational Turkish Text Classification Using Distant Supervised Entities and Relations

Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)models.Focusing on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from texts.The adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational information.Experiments conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector Machine,Logistic Regression,Deep Neural Network,and Convolutional Neural Network.The results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP applications.Contributions of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational database.By demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)tools.Additionally,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.

Complementary monogamy and polygamy properties among multipartite systems

Monogamy and polygamy relations are essential properties of quantum entanglement,which characterize the distributions of entanglement in multipartite systems.In this paper,we establish the general monogamy relations forγ-th(0≤γ≤α,α≥1)power of quantum entanglement based on unified-(q,s)entanglement and polygamy relations forδ-th(δ≥β,0≤β≤1)power of entanglement of assistance based on unified-(q,s)entanglement of assistance,which provides a complement to the previous research in terms of different parameter regions ofγandδ.These results are then applied to specific quantum correlations,e.g.,entanglement of formation,Renyi-q entanglement of assistance and Tsallis-q entanglement of assistance to get the corresponding monogamy and polygamy inequalities.Moreover,typical examples are presented for illustration.

High-rate electrochemical H_(2)O_(2) production over multimetallic atom catalysts under acidic–neutral conditions

Hydrogen peroxide(H_(2)O_(2))production by the electrochemical 2-electron oxygen reduction reaction(2e−ORR)is a promising alternative to the energy-intensive anthraquinone process,and single-atom electrocatalysts show the unique capability of high selectivity toward 2e−ORR against the 4e−one.The extremely low surface density of the single-atom sites and the inflexibility in manipulating their geometric/electronic configurations,however,compromise the H_(2)O_(2) yield and impede further performance enhancement.Herein,we construct a family of multiatom catalysts(MACs),on which two or three single atoms are closely coordinated to form high-density active sites that are versatile in their atomic configurations for optimal adsorption of essential*OOH species.Among them,the Cox–Ni MAC presents excellent electrocatalytic performance for 2e−ORR,in terms of its exceptionally high H_(2)O_(2) yield in acidic electrolytes(28.96 mol L^(−1) gcat.^(−1) h^(−1))and high selectivity under acidic to neutral conditions in a wide potential region(>80%,0–0.7 V).Operando X-ray absorption and density functional theory analyses jointly unveil its unique trimetallic Co2NiN8 configuration,which efficiently induces an appropriate Ni–d orbital filling and modulates the*OOH adsorption,together boosting the electrocatalytic 2e−ORR capability.This work thus provides a new MAC strategy for tuning the geometric/electronic structure of active sites for 2e−ORR and other potential electrochemical processes.

A Survey of Knowledge Graph Construction Using Machine Learning

Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured framework.This framework facilitates a transformation in information retrieval,transitioning it from mere string matching to far more sophisticated entity matching.In this transformative process,the advancement of artificial intelligence and intelligent information services is invigorated.Meanwhile,the role ofmachine learningmethod in the construction of KG is important,and these techniques have already achieved initial success.This article embarks on a comprehensive journey through the last strides in the field of KG via machine learning.With a profound amalgamation of cutting-edge research in machine learning,this article undertakes a systematical exploration of KG construction methods in three distinct phases:entity learning,ontology learning,and knowledge reasoning.Especially,a meticulous dissection of machine learningdriven algorithms is conducted,spotlighting their contributions to critical facets such as entity extraction,relation extraction,entity linking,and link prediction.Moreover,this article also provides an analysis of the unresolved challenges and emerging trajectories that beckon within the expansive application of machine learning-fueled,large-scale KG construction.

Isogeometric Analysis of Hyperelastic Material Characteristics for Calcified Aortic Valve

This study explores the implementation of computed tomography(CT)reconstruction and simulation techniques for patient-specific valves,aiming to dissect the mechanical attributes of calcified valves within transcatheter heart valve replacement(TAVR)procedures.In order to facilitate this exploration,it derives pertinent formulas for 3D multi-material isogeometric hyperelastic analysis based on Hounsfield unit(HU)values,thereby unlocking foundational capabilities for isogeometric analysis in calcified aortic valves.A series of uniaxial and biaxial tensile tests is executed to obtain an accurate constitutive model for calcified active valves.To mitigate discretization errors,methodologies for reconstructing volumetric parametric models,integrating both geometric and material attributes,are introduced.Applying these analytical formulas,constitutive models,and precise analytical models to isogeometric analyses of calcified valves,the research ascertains their close alignment with experimental results through the close fit in displacement-stress curves,compellingly validating the accuracy and reliability of the method.This study presents a step-by-step approach to analyzing themechanical characteristics of patient-specific valves obtained fromCT images,holding significant clinical implications and assisting in the selection of treatment strategies and surgical intervention approaches in TAVR procedures.

Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

Predicting impact forces on pipelines from deep-sea fluidized slides:A comprehensive review of key factors

Deep-sea pipelines play a pivotal role in seabed mineral resource development,global energy and resource supply provision,network communication,and environmental protection.However,the placement of these pipelines on the seabed surface exposes them to potential risks arising from the complex deep-sea hydrodynamic and geological environment,particularly submarine slides.Historical incidents have highlighted the substantial damage to pipelines due to slides.Specifically,deep-sea fluidized slides(in a debris/mud flow or turbidity current physical state),characterized by high speed,pose a significant threat.Accurately assessing the impact forces exerted on pipelines by fluidized submarine slides is crucial for ensuring pipeline safety.This study aimed to provide a comprehensive overview of recent advancements in understanding pipeline impact forces caused by fluidized deep-sea slides,thereby identifying key factors and corresponding mechanisms that influence pipeline impact forces.These factors include the velocity,density,and shear behavior of deep-sea fluidized slides,as well as the geometry,stiffness,self-weight,and mechanical model of pipelines.Additionally,the interface contact conditions and spatial relations were examined within the context of deep-sea slides and their interactions with pipelines.Building upon a thorough review of these achievements,future directions were proposed for assessing and characterizing the key factors affecting slide impact loading on pipelines.A comprehensive understanding of these results is essential for the sustainable development of deep-sea pipeline projects associated with seabed resource development and the implementation of disaster prevention measures.

Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.