Euler’s First-Order Explicit Method–Peridynamic Differential Operator for Solving Population Balance Equations of the Crystallization Process

Using Euler’s first-order explicit(EE)method and the peridynamic differential operator(PDDO)to discretize the time and internal crystal-size derivatives,respectively,the Euler’s first-order explicit method–peridynamic differential operator(EE–PDDO)was obtained for solving the one-dimensional population balance equation in crystallization.Four different conditions during crystallization were studied:size-independent growth,sizedependent growth in a batch process,nucleation and size-independent growth,and nucleation and size-dependent growth in a continuous process.The high accuracy of the EE–PDDO method was confirmed by comparing it with the numerical results obtained using the second-order upwind and HR-van methods.The method is characterized by non-oscillation and high accuracy,especially in the discontinuous and sharp crystal size distribution.The stability of the EE–PDDO method,choice of weight function in the PDDO method,and optimal time step are also discussed.

Energy Stable Nodal DG Methods for Maxwell’s Equations of Mixed-Order Form in Nonlinear Optical Media

In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic Kerr response,and the nonlinear delayed Raman molecular vibrational response.Unlike the first-order PDE-ODE governing equations considered previously in Bokil et al.(J Comput Phys 350:420–452,2017)and Lyu et al.(J Sci Comput 89:1–42,2021),a model of mixed-order form is adopted here that consists of the first-order PDE part for Maxwell’s equations coupled with the second-order ODE part(i.e.,the auxiliary differential equations)modeling the linear and nonlinear dispersion in the material.The main contribution is a new numerical strategy to treat the Kerr and Raman nonlinearities to achieve provable energy stability property within a second-order temporal discretization.A nodal discontinuous Galerkin(DG)method is further applied in space for efficiently handling nonlinear terms at the algebraic level,while preserving the energy stability and achieving high-order accuracy.Indeed with d_(E)as the number of the components of the electric field,only a d_(E)×d_(E)nonlinear algebraic system needs to be solved at each interpolation node,and more importantly,all these small nonlinear systems are completely decoupled over one time step,rendering very high parallel efficiency.We evaluate the proposed schemes by comparing them with the methods in Bokil et al.(2017)and Lyu et al.(2021)(implemented in nodal form)regarding the accuracy,computational efficiency,and energy stability,by a parallel scalability study,and also through the simulations of the soliton-like wave propagation in one dimension,as well as the spatial-soliton propagation and two-beam interactions modeled by the two-dimensional transverse electric(TE)mode of the equations.

The forecasting efficiency under different selected regions by Pattern Informatics Method and seismic potential estimation in the North-South Seismic Zone

In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.

Research on the Application of Montessori Education Method in Cognitive Training of Patients with Alzheimer’s Disease

Objective:To study the application of the Montessori education method in cognitive training in patients with Alzheimer’s disease(AD).Methods:40 cases of senile dementia patients who were admitted to our hospital from January 2022 to January 2023 were selected and randomly divided into an intervention group and a control group according to the single and double number table method,with 20 cases in each group.The intervention group used the Montessori education method,the principle of which was to implement individualized health interventions based on the individual conditions of the patients,for a period of 6 months;the control group was given conventional treatment and nursing of the disease.The Mini-Mental State Examination(MMSE)was used to compare the effects of the two groups of patients before and after health intervention and conduct statistical analysis.Results:The score of the intervention group was higher than that of the control group,and there was a statistical difference between the two(P<0.05).Conclusion:Implementing the Montessori education method for diagnosed Alzheimer’s patients can effectively improve their cognitive function and delay the progress of further dementia.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

Critical care nurses and their clinical reasoning for customizing monitor alarms:a mixed-method study

Objective:To explore the clinical rationale of critical care nurses for personalizing monitor alarms.One of the most crucial jobs assigned to critical care nurses is monitoring patients'physiological indicators and carrying out the necessary associated interventions.Successful use of equipment in the nursing practice environment will be improved by a thorough understanding of the nurse's approach to alarm configuration.Methods:A mixed-method design integrating quantitative and qualitative components was used.The sample of this study recruited a convenience sample of 60 nurses who have worked in critical care areas.This study took place at Lebanese American University Medical Center Rizk Hospital,utilizing a semi-structured interview with participants.Results:The study demonstrated the high incidence of nuisance alarms and the desensitization of critical care nurses to vital ones.According to the nurses,frequent false alarms and a shortage of staff are the 2 main causes of alarm desensitization.Age was significantly associated with the perception of Smart alarms,according to the data(P=0.03).Four interconnected themes and subcategories that reflect the clinical reasoning process for alarm customization were developed as a result of the study's qualitative component:(1)unit alarm environment;(2)nursing style;(3)motivation to customize;and(4)clinical and technological customization.Conclusions:According to this study,nurses believe that alarms are valuable.However,a qualitative analysis of the experiences revealed that customization has been severely limited since the healthcare team depends on nurses to complete these tasks independently.Additionally,a staffing shortage and lack of technical training at the start of placement have also hindered customization.

沉降预测中的Asaoka法应用研究

系统介绍了Asaoka法的基础知识,并基于抛物插值法和直线最小二乘拟合法,编制了该法预测地基最终沉降的程序。结合工程实例,详细分析了时间间隔△t对Asaoka法的预测结果及相关指标的影响,给出了△t的建议取值范围,同时对多级荷载下的某路堤沉降进行了预测。计算结果表明:程序中采用的抛物插值法等是可行的,且Asaoka法自身的优点决定了其具有较高的应用价值。

Asaoka法中时间间隔取值范围的应用研究

系统介绍了Asaoka法的原理和利用最小二乘法对观测数据进行等时距处理的方法。结合工程实例,详细分析了时间间隔Δt对Asaoka法的预测结果及相关指标的影响,得出如下结论:以往在Asaoka法推算过程中,选取相关系数较好的沉降值作为最终沉降值的方法有不合理之处;将预测结果可靠性的优化指标定为两次预测的差值,选取使两次预测差值较小的时间间隔较为合理。

基于Asaoka法的非等间隔地基沉降数据预测

现有地基沉降预测模型多数是数学统计模型,参数意义不够明确,而Asaoka方程具有明确的理论基础,在工程中得到了广泛应用。针对实际工程中出现的非等间隔沉降观测数据,通过将微分方程用差分形式表示,建立了可以用于非等间隔数据处理的Asaoka法,同时给出了基于该法的沉降预测表达式。通过工程实例,将新方法与Asaoka图解法进行分析比较,给出了Asaoka法的应用建议。实例应用结果表明,新方法可以较好地预测地基沉降。

路基沉降预测的非等间隔Asaoka法

路基沉降预测对于确保高速铁路无砟轨道结构铺设质量非常重要。《客运专线铁路无砟轨道铺设条件评估技术指南》中推荐的沉降预测方法对沉降观测数据时间间隔的要求并不一样。其中,Asaoka公式是根据一维固结问题推导得出,具有明确的物理意义,但需要沉降观测数据为等时间间隔数据。根据微分变差分原理,采用前向差分和后向差分推导出了非等间隔Asaoka法。工程实例应用结果显示非等间隔Asaoka法具有较好的预测效果,可以直接应用于非等间隔沉降数据,避免了Asaoka方法在应用中存在的问题。

矿井井架基础沉降预测中的Asaoka法和灰色模型

通过对Asaoka法和灰色模型的基本原理及其选取原则进行简介,并结合对某矿区矿井井架的多期观测,分别采用Asaoka法和灰色模型对实测数据进行分析进而预测,结果证明2种方法在短期内的预测结果相同,预测精度较高,对煤矿的实际生产具有重要意义,但2种方法都无法对下沉的机理做出科学合理的解释,同时其长期预测精度尚待进一步验证.

基于Asaoka法的软基处理动态设计

在软基处理工程中,对实测沉降数据的分析通常仅局限于推算最终沉降和固结度。以Asaoka法为基础,可以利用实测沉降数据建立软基处理动态设计的完整流程。总结了采用Asaoka法推算预压荷载下的最终沉降和固结度的方法,提出进行水平向固结系数、压缩指数等土体参数反演分析和预压工期预测的实用方法,并通过工程实例介绍了其应用。该流程可以充分利用监测数据,实现软基处理的动态化设计,对设计和施工具有较强的指导意义。

基于重排S-method的多分量辐射源信号分析方法

为实现多分量辐射源信号的有效检测和识别,提出了基于重排S-method(RSM)的多分量辐射源信号分析方法.针对Wigner-Ville分布交叉项严重和计算复杂度高的问题,采用RSM分析密集、交叠的辐射源信号,给出了其算法的硬件实现和计算复杂度分析.该方法能处理线性和非线性调频信号,算法简单,易于实现.复杂体制多分量辐射源信号分析的实验结果表明,该方法能有效分析多分量辐射源信号,时频分辨率高,不受交叉项干扰,具有比Wigner-Ville分布和S-method更强的噪声抑制能力.

基于S-method的多分量雷达辐射源信号检测

针对传统时频方法在处理多分量雷达辐射源信号时存在交叉项,不能检测各分量信号时域参数,难以适应低信噪比环境的问题,提出一种基于S-method(SM)的多分量雷达辐射源信号检测新方法。该方法首先计算信号的SM时频分布,然后在时频面的基础上检测各信号分量的瞬时频率和脉冲起止时间。实验结果表明,该方法能处理线性及非线性调频信号、时频分辨率高且不受交叉项干扰,时域检测精度大于98.60%,频域检测精度大于99.48%,信噪比降低时仍然保持强检测能力。

基于Asaoka法的软基沉降量预测研究与应用

介绍了Asaoka法的基本理论知识,并以温州某软基加固工程为例,详细分析了取舍初始沉降值、时间间隔(Δt)对Asaoka法预测最终沉降量以及相关指标的影响,确定了以相关系数(R)的大小来判别沉降预测好坏的方法,为类似软土地基沉降预测提供了依据。

Comparative Analysis of Improving Effects of 12 Maize Populations with Improved S_1 Selection Method

ln this study, 12 maize populations were improved with the improved S1 selection method, aiming to increase the improvement efficiency of maize popula-tions. The results showed that number of rows per spike, number of grains per row and 100-grain weight were the three important component traits of maize yield. The highest genetic increment was found in Mengqun 2, fol owed by Mengqun 4, Mengqun 1 and other 7 maize populations. Negative genetic increment was shown in Mengqun 3 and 3 introduced foreign maize populations. Some changes were shown in spikes, plant traits and genetic diversity of maize populations. Based on our results, we concluded that Mengqun 2, Mengqun 4, Zhongzong 7, Mengqun C and Mengqun A could be directly used for the line breeding by selfing for their higher genetic increment of yield and better improvement effects of other agricultural traits. Compared with these 5 populations, the improvement potential of other maize populations was limited for their lower genetic increment.

Asaoka法在软基处理中的沉降预测应用

系统地介绍了利用Asaoka法进行沉降预测计算最终沉降的基本原理,并引用工程实例,通过实际沉降监测数据建立曲线并进行拟合,获得Asaoka法关键计算系数,并进行了沉降预测,可用于指导超载预压的卸载控制和沉降固结分析。

建筑地基沉降预测的灰色模型与Asaoka法

在众多的建筑地基沉降预测模型中,Asaoka公式参数意义明确,在实际工程中得到了广泛应用,但是其存在局限性。根据灰色模型理论与Asaoka法一阶微分方程的一致性,通过构建满足白指数率预测无偏性的变权灰色预测模型,避免了Asaoka法应用的局限性。实例应用结果显示,变权灰色预测模型提高了预测精度,对非等时距沉降序列的分析预测具有更高的应用价值。

Asaoka法对路堤沉降越级预测初探

Asaoka法可很好地根据有限次沉降观测结果推算建筑物的最终沉降,但遗憾的是其只能基于本级荷载下沉降观测记录对本级荷载下最终沉降进行预测。本文针对多级填土下的路堤沉降问题,探讨了如何利用该法进行越级预测的思路,给出了该法图解中每级荷载下沉降数据对应的直线在纵坐标轴上截距与路堤高度之间的近似关系。最后,结合工程实例,根据某级荷载下沉降记录对下一级最终沉降作了预测,所得的结果精度还是令人满意的。

运用Asaoka法进行固结参数的反演计算

由于诸多因素的影响,室内试验测定的固结系数往往与实际值存在相当大的差并,因此试验结果的代表性难以保证。为了提高固结系数取值的准确性和合理性,根据工程施工期和运营期的原位观测沉降资料反演分析软土地基的固结系数不失为解决上述问题的一种较为有效的综合取值方法。Asaoka法因其数学形式简单,参数易于理解与确定,只需要很少的观测数据就可通过作图法求解固结系数。