Color Matching of Pre-colored Fiber Blends Based on Two-Constant Kubelka-Munk Theory

Some modifications of two-constant Kubelka-Munk theory has been made for the color matching of pre-colored fiber blends. The scattering coefficients of three primaries are averaged and taken as initial coefficients in each wavelength. The unit sums of concentration in E-Allen’s Algorithm were removed in the case of pre-colored fiber blends. Predicted blend ratios and reflectance curves agree very well with measured ones and color differences are within the tolerant limit, showing satisfactory matching results.

Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter

In traditional finite-temperature Kohn–Sham density functional theory(KSDFT),the partial occupation of a large number of high-energy KS eigenstates restricts the use of first-principles molecular dynamics methods at extremely high temperatures.However,stochastic density functional theory(SDFT)can overcome this limitation.Recently,SDFT and the related mixed stochastic–deterministic density functional theory,based on a plane-wave basis set,have been implemented in the first-principles electronic structure software ABACUS[Q.Liu and M.Chen,Phys.Rev.B 106,125132(2022)].In this study,we combine SDFT with the Born–Oppenheimer molecular dynamics method to investigate systems with temperatures ranging from a few tens of eV to 1000 eV.Importantly,we train machine-learning-based interatomic models using the SDFT data and employ these deep potential models to simulate large-scale systems with long trajectories.Subsequently,we compute and analyze the structural properties,dynamic properties,and transport coefficients of warm dense matter.

基于Kubelka-Munk双常数理论的涤/黏双组分三色混色纤维配方预测

为了提高原液着色涤/黏双组分混配色打样效率,基于Kubelka-Munk双常数理论模型,选用3种单色(大红、宝兰G、金黄)涤纶短纤维和3种单色(大红、蓝色、黄色)黏胶短纤维为研究对象,以6种单色纤维进行双组分混色,按9种不同混合比例共得到54种三色混色双组分纤维样品。利用测色仪测定混色样的颜色特征参数:反射率(R)、颜色深度(K/S)、明亮度(L)、红绿色度(a)及黄蓝色度(b),利用最小二乘法对数据进行处理;最后对计算混色比例与实际混色比例之间的误差进行评价,以验证Kubelka-Munk双常数理论模型在双组分混配色中的适用性。结果表明,54种样品的色差均在1.0以下,均值为0.2775,标准差为0.2177,预测比例与实际比例差距较小,红色涤纶与蓝色、黄色黏胶组合的平均比例误差最小,为1.109%,说明其比例预测效果较好,而黄色涤纶与红色、蓝色黏胶组合的平均色差最小,为0.1721,说明其颜色预测较好。

基于约束Kubelka-Munk模型与梯度局部优化算法耦合的色剂配色方法

针对人工实现快速、准确的色剂配色非常困难的问题,本研究提出了一个基于约束Kubelka-Munk模型与梯度局部优化算法耦合的色剂配色方法,实现涂料和印刷行业半透明和不透明色剂的配方预测。在此方法中,先利用梯度局部优化算法求解在基色色剂和冲淡剂混合基础上的目标函数,计算出基色色剂的吸收系数(K)和散射系数(S)。然后,为了实现任意目标色剂中基色色剂的混合配比,利用基色色剂与冲淡剂的吸收系数与散射系数物理属性对Kubelka-Munk模型进行约束,并通过最小化目标色剂与基色色剂之间的吸收系数与散射系数比值,构建了约束Kubelka-Munk模型,用于预测半透明着色剂和不透明色剂的配方。配方差、光谱反射率差,以及色差的实验结果表明,与传统的Kubelka-Munk模型相比,该方法建立的模型预测混色效果更优。

面向全色域转杯纺纱的Kubelka-Munk双常数理论模型构建及颜色预测

为了能在色纺纱的纺纱阶段即时调控纱线颜色,减少混色成本,缩短工艺流程,结合三通道数控转杯纺纱的特点构建了全色域网格化混色模型,该模型可在纺纱过程中进行全色域范围内的色相调控、明度调控和彩度调控。为了解决色纺纱的测配色问题,得到与之相匹配的测配色系统,根据来样快速进行计算机测配色,节约成本,结合传统Kubelka-Munk双常数理论模型的特点,从构建的全色域网格化混色模型中选取混合样来进行颜色预测。从传统Kubelka-Munk双常数理论模型颜色预测的结果发现,部分混合样的预测反射率明显低于实际的反射率,针对这个问题,重新构建了新的Kubelka-Munk双常数理论模型来进行颜色预测得到新的预测反射率,并用插值替换的方法,把传统Kubelka-Munk双常数理论模型预测结果中明显低于实际反射率的部分用新的预测反射率替换,得到最终的混合样预测反射率。结果表明:与传统的Kubelka-Munk双常数理论模型预测混合样颜色结果相比,新的Kubelka-Munk双常数理论模型预测颜色并用插值替换法替换后得到的最终的混合样的颜色,色差平均值从1.48降低到1.04,且所有混合样的色差均能控制在2.0以内。该预测方法较传统Kubelka-Munk双常数理论模型具有更好的预测精度,所构建的全色域网格化混色模型和新的Kubelka-Munk双常数理论模型可应用于多基色纤维混色色彩和混合比的预测。

Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.

Density functional theory study of B- and Si-doped carbons and their adsorption interactions with sulfur compounds

Understanding the adsorption interactions between carbon materials and sulfur compounds has far-reaching impacts,in addition to their well-known important role in energy storage and conversion,such as lithium-ion batteries.In this paper,properties of intrinsic B or Si single-atom doped,and B-Si codoped graphene(GR)and graphdiyne(GDY)were investigated by using density functional theory-based calculations,in which the optimal doping configurations were explored for potential applications in adsorbing sulfur compounds.Results showed that both B or Si single-atom doping and B-Si codoping could substantially enhance the electron transport properties of GR and GDY,improving their surface activity.Notably,B and Si atoms displayed synergistic effects for the codoped configurations,where B-Si codoped GR/GDY exhibited much better performance in the adsorption of sulfurcontaining chemicals than single-atom doped systems.In addition,results demonstrated that,after B-Si codoping,the adsorption energy and charge transfer amounts of GDY with sulfur compounds were much larger than those of GR,indicating that B-Si codoped GDY might be a favorable material for more effectively interacting with sulfur reagents.

Local thermal conductivity of inhomogeneous nano-fluidic films:A density functional theory perspective

Combining the mean field Pozhar-Gubbins(PG)theory and the weighted density approximation,a novel method for local thermal conductivity of inhomogeneous fluids is proposed.The correlation effect that is beyond the mean field treatment is taken into account by the simulation-based empirical correlations.The application of this method to confined argon in slit pore shows that its prediction agrees well with the simulation results,and that it performs better than the original PG theory as well as the local averaged density model(LADM).In its further application to the nano-fluidic films,the influences of fluid parameters and pore parameters on the thermal conductivity are calculated and investigated.It is found that both the local thermal conductivity and the overall thermal conductivity can be significantly modulated by these parameters.Specifically,in the supercritical states,the thermal conductivity of the confined fluid shows positive correlation to the bulk density as well as the temperature.However,when the bulk density is small,the thermal conductivity exhibits a decrease-increase transition as the temperature is increased.This is also the case in which the temperature is low.In fact,the decrease-increase transition in both the small-bulk-density and low-temperature cases arises from the capillary condensation in the pore.Furthermore,smaller pore width and/or stronger adsorption potential can raise the critical temperature for condensation,and then are beneficial to the enhancement of the thermal conductivity.These modulation behaviors of the local thermal conductivity lead immediately to the significant difference of the overall thermal conductivity in different phase regions.

Comparative study on phase transition behaviors of fractional molecular field theory and random-site Ising model

Fractional molecular field theory(FMFT)is a phenomenological theory that describes phase transitions in crystals with randomly distributed components,such as the relaxor-ferroelectrics and spin glasses.In order to verify the feasibility of this theory,this paper fits it to the Monte Carlo simulations of specific heat and susceptibility versus temperature of two-dimensional(2D)random-site Ising model(2D-RSIM).The results indicate that the FMFT deviates from the 2D-RSIM significantly.The main reason for the deviation is that the 2D-RSIM is a typical system of component random distribution,where the real order parameter is spatially heterogeneous and has no symmetry of space translation,but the basic assumption of FMFT means that the parameter is spatially uniform and has symmetry of space translation.

Corrigendum to“Atomic-scale electromagnetic theory bridging optics in microscopic world and macroscopic world”

The signs of the electric field markers in Figs.2 and 4 of the paper[Chin.Phys.B 32104211(2023)]have been corrected.These modifications do not affect the results derived in the paper.

Foundations of the Scale-Symmetric Theory and the Illusory Total Width of the Off-Shell Higgs Bosons

Here we present the foundations of the Scale-Symmetric Theory (SST), i.e. the fundamental phase transitions of the initial inflation field, the atom-like structure of baryons and different types of black holes. Within SST we show that the transition from the nuclear strong interactions in the off-shell Higgs boson production to the nuclear weak interactions causes that the real total width of the Higgs boson from the Higgs line shape (i.e. 3.3 GeV) decreases to 4.3 MeV that is the illusory total width. Moreover, there appear some glueballs/condensates with the energy 3.3 GeV that accompany the production of the off-shell Higgs bosons.

The Fate of Supersymmetry in Quantum Field Theories

We analyze the significance of supersymmetry in two topological models and the standard model (SM). We conclude that the two topological field theory models favor hidden supersymmetry. The SM superpartners, instead, have not been found.

Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

The Nature of Inertia Explained Using the Field Theory

Analysis of free fall and acceleration of the mass on the Earth shows that using abstract entities such as absolute space or inertial space to explain mass dynamics leads to the violation of the principle of action and reaction. Many scientists including Newton, Mach, and Einstein recognized that inertial force has no reaction that originates on mass. Einstein calls the lack of reaction to the inertial force a serious criticism of the space-time continuum concept. Presented is the hypothesis that the inertial force develops in an interaction of two masses via the force field. The inertial force created by such a field has reaction force. The dynamic gravitational field predicted is strong enough to be detected in the laboratory. This article describes the laboratory experiment which can prove or disprove the hypothesis of the dynamic gravitational field. The inertial force, calculated using the equation for the dynamic gravitational field, agrees with the behavior of inertial force observed in the experiments on the Earth. The movement of the planets in our solar system calculated using that equation is the same as that calculated using Newton’s method. The space properties calculated by the candidate equation explain the aberration of light and the results of light propagation experiments. The dynamic gravitational field can explain the discrepancy between the observed velocity of stars in the galaxy and those predicted by Newton’s theory of gravitation without the need for the dark matter hypothesis.

The Place of Nursing Theory in the Management of Post-Operative Infections in a Hospital Environment: Case of Cibitoke District Hospital

Introduction: Post-operative infections, such as surgical site infections (SSIs), are a significant concern in healthcare settings. Nurses play a crucial role in the prevention and management of these infections. The use of nursing theory could contribute to the prevention of SSIs. The aim of this study was to evaluate the role of nursing theory in the management of surgical site infections (SSIs) in a hospital environment. Method: A cross-sectional study was conducted using descriptive and analytical methods to assess the role of nursing theory in the management of Post-operative infections (POI) in a hospital setting in October 2023. The study population consisted of nurses working in the Surgery, Emergency, and Maternity units at Cibitoke District Hospital. A sample size of 71 nurses working full or part time in the Surgery were invited to participate in this study. A questionnaire was used to collect the data, and SPSS version 21.0 software was used for analysis. Results: The study found that nursing theory did not have any statistically significant place in the management of POI (p-value = 0.523). However, the results showed that experience was the only significant factor influencing the management of POI (p-value = 0.004). This is explained by the analysis of the net effects of the explanatory variable where we noticed that those who had more experience were more likely to manage post-operative infections. The participants’ knowledge regarding nursing theory in the management was poor as they scored less than 30% in all the variables used to measure their knowledge. Conclusion: The study revealed that nurses’ knowledge of nursing theories and their applications in the management of SSIs was poor. Continuing professional development, curriculum review, and in-service training were highly recommended.

Extreme value theory applied to the auroral electrojet indices

The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various fields.This research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value theory.By fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time series.Consequently,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are rare.As a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly challenging.It is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.

An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

Towards 6D Little String Theory of Particles

A model for particles based on preons in chiral, vector and tensor/graviton supermultiplets of unbroken global supersymmetry is engineered. The framework of the model is little string theory. Phenomenological predictions are discussed.

Game Theory Based Model for Predictive Analytics Using Distributed Position Function

This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are distributed over a position spectrum. We generalize the concept of position in the model to incorporate continuous positions for the actors, enabling them to have more flexibility in defining their targets. We explore different possible functions to study the role of the position function and discuss appropriate distance measures for computing the distance between the positions of actors. To validate the proposed extension, we demonstrate the trustworthiness of our model’s performance and interpretation by replicating the results based on data used in earlier studies.

SHARP MORREY REGULARITY THEORY FOR A FOURTH ORDER GEOMETRICAL EQUATION

This paper is a continuation of recent work by Guo-Xiang-Zheng[10].We deduce the sharp Morrey regularity theory for weak solutions to the fourth order nonhomogeneous Lamm-Rivière equation △^{2}u=△(V▽u)+div(w▽u)+(▽ω+F)·▽u+f in B^(4),under the smallest regularity assumptions of V,ω,ω,F,where f belongs to some Morrey spaces.This work was motivated by many geometrical problems such as the flow of biharmonic mappings.Our results deepens the Lp type regularity theory of[10],and generalizes the work of Du,Kang and Wang[4]on a second order problem to our fourth order problems.