Problem-solving model guided by stimulus-organism-response theory:State of mind and coping styles of depressed mothers after cesarean delivery

BACKGROUND The use of a problem-solving model guided by stimulus-organism-response(SOR)theory for women with postpartum depression after cesarean delivery may inform nursing interventions for women with postpartum depression.AIM To explore the state of mind and coping style of women with depression after cesarean delivery guided by SOR theory.METHODS Eighty postpartum depressed women with cesarean delivery admitted to the hospital between January 2022 and October 2023 were selected and divided into two groups of 40 cases each,according to the random number table method.In the control group,the observation group adopted the problem-solving nursing model under SOR theory.The two groups were consecutively intervened for 12 weeks,and the state of mind,coping styles,and degree of post-partum depression were analyzed at the end of the intervention.RESULTS The Edinburgh Postnatal Depression Scale and Hamilton Depression Scale-24-item scores of the observation group were lower than in the control group after care,and the level of improvement in the state of mind was higher than that of the control group(P<0.05).The level of coping with illness in the observation group after care(26.48±3.35)was higher than that in the control group(21.73±3.20),and the level of avoidance(12.04±2.68)and submission(8.14±1.15)was lower than that in the control group(15.75±2.69 and 9.95±1.20),with significant differences(P<0.05).CONCLUSION Adopting the problem-solving nursing model using SOR theory for postpartum depressed mothers after cesarean delivery reduced maternal depression,improved their state of mind,and coping level with illness.

A simple method for solving unidirectional methane gas flow in coal seam based on similarity solution

The equation used to model the unidirectional flow of methane gas in coal seams is usually formulated as a nonlinear partial differential equation, which needs to be solved numerically with a computer program.Nevertheless, for people without access to the computer program, the conventional numerical method may be inconvenient. Thus, the objective here is to seek some method simpler than the conventional one for solving the flow problem. A commonly used model of the unidirectional methane gas flow is considered, where the methane adsorption is described by the Langmuir isotherm and the free gas is treated as real gas. By introducing the similarity solution, a simple method for solving the flow model is proposed, which can be done on a hand calculator. It is shown by two examples that the gas pressure profile obtained by the proposed method agrees well with the direct numerical solution of the flow model.

MODELING METHOD FOR PRODUCT STRUCTURE MAPPING BASED ON REVERSE SOLVING OF LOCUS AND MOTION

Aiming at the problem of structure design in reverse-design of mechanism, a structure mapping method based on reverse solving of locus and motion （RSLM） is presented. The mechanism scheme meeting the requirements of geometric and structural features is obtained through RSLM. The element instance subsets related to component are established based on the element type mapping, pair structure type mapping and design knowledge mapping between components and elements layer by layer. The assembly position mapping of elements is established based on the topological structure information of mechanism scheme, and the product modeling of structure mapping is realized. The algorithm program and prototype system of product structure mapping based on RSLM are developed. Application samples show that the method implements the integration of scheme design, assembly design and structure design, and modeling for product structure mapping based on RSLM. The feasibility of assembly is analyzed in scheme design that contributes to reducing the design error, and raising the design efficiency and quality.

A METHOD FOR SOLVING DOA ESTIMATION AMBIGUITY IN ESPRIT ALGORITHM

This paper introduces a method for solving DOA estimation ambiguity in ESPRIT algorithm with the conventional beamformer. With the help of it, for any space of two subarrays, the signal DOA in [-π/2 ,π/2] can be estimated effectively by using ESPRIT algorithm. Finally, some simulation results to verify the theoretical analyses are presented.

Solving geometric constraints with genetic simulated annealing algorithm

This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally. It has advantages (due to its not being sensitive to the initial values) over the Newton-Raphson method, and its yielding of multiple solutions, is an advantage over other optimal methods for multi-solution constraint system. Our experiments have proved the robustness and efficiency of this method.

Applying the disciplinary relation matrix to multidisciplinary design optimization modeling and solving

A new efficient coupling relationship description method has been developed to provide an automated and visualized way to multidisciplinary design optimization (MDO) modeling and solving. The disciplinary relation matrix (DRM) is proposed to describe the coupling relationship according to disciplinary input/output variables, and the MDO definition has been reformulated to adopt the new interfaces. Based on these, a universal MDO solving procedure is proposed to establish an automated and efficient way for MDO modeling and solving. Through a simple and convenient initial configuration, MDO problems can be solved using any of available MDO architectures with no further effort. Several examples are used to verify the proposed MDO modeling and solving process. Result shows that the DRM method has the ability to simplify and automate the MDO procedure, and the related MDO framework can evaluate the MDO problem automatically and efficiently.

Uncertain optimal model and solving method to platform scheduling problem in battlefield

The platform scheduling problem in battlefield is one of the important problems in military operational research.It needs to minimize mission completing time and meanwhile maximize the mission completing accuracy with a limited number of platforms.Though the traditional certain models obtain some good results,uncertain model is still needed to be introduced since the battlefield environment is complex and unstable.An uncertain model is prposed for the platform scheduling problem.Related parameters in this model are set to be fuzzy or stochastic.Due to the inherent disadvantage of the solving methods for traditional models,a new method is proposed to solve the uncertain model.Finally,the practicability and availability of the proposed method are demonstrated with a case of joint campaign.

Integration of axiomatic design and theory of inventive problem solving for conceptual design

Axiomatic design (AD) and theory of inventive problem solving (TRIZ) are widely used in conceptual design. Both of them have limitations, however. We presented an integrated model of these two methods to increase the efficiency and quality of the problem solving process for conceptual design. AD is used for systematically defining and structuring a problem into a hierarchy. Sometimes, the design matrix is coupled in AD which indicates the functional requirements are coupled. TRIZ separation principles can be used to separate non-independent design parameters, which provide innovative solutions at each hierarchical level. We applied the integrated model to the heating and drying equipment of bitumen reproduction device. The result verifies that the integrated model can work very well in conceptual design.

Second-order problem solving:Nurses'perspectives on learning from.near misses

Objectives:Near misses happen more frequently than actual errors,and highlight system vulnerabilities without causing any harm,thus provide a safe space for organizational learning.Second-order problem solving behavior offers a new perspective to better understand how nurses promote learning from near misses to improve organizational outcomes.This study aimed to explore frontline nurses’perspectives on using second-order problem solving behavior in learning from near misses to improve patient safety.Methods:A qualitative exploratory study design was employed.This study was conducted in three tertiary hospitals in east China from June to November 2015.Purposive sampling was used to recruit 19 frontline nurses.Semi-structured interviews and a qualitative directed content analysis was undertaken using Crossan’s 4I Framework of Organizational Learning as a coding framework.Results:Second-order problem solving behavior,based on the 4I Framework of Organizational Learning,was referred to as being a leader in exposing near misses,pushing forward the cause analysis within limited capacity,balancing the active and passive role during improvement project,and promoting the continuous improvement with passion while feeling low-powered.Conclusions:4I Framework of Organizational Learning can be an underlying guide to enrich frontline nurses’role in promoting organizations to learn from near misses.In this study,nurses displayed their pivotal role in organizational learning from near misses by using second-order problem solving.However,additional knowledge,skills,and support are needed to maximize the application of second-order problem solving behavior when near misses are recognized.

Effect of Solving Models on Euler Vectors

In the process of solving Euler vectors based on GNSS horizontal movement field,the number of estimated parameters can affect Euler vector results. This issue is analyzed through theoretical deduction and practical example in this paper. Firstly,the difference between the results of Euler vectors in different solving models is deduced. Meanwhile, based on GNSS horizontal movement field in the Chinese mainland from 2004 to 2007,two common models( RRM and REHSM) are used to discuss the impact of solving models on Euler vectors and the follow-up study. The result shows that the maximum value of the difference in a block's entire rotation can reach 2. 6mm /a,and should not be ignored. Therefore,the results of horizontal movement are different using different kinematic block models,and this should be paid more attention in the analysis of crustal horizontal movement.

An Easy Algorithm for Solving Radiative Transfer Equation in Clear Atmosphere

An accurate and rapid method for solving radiative transfer equation is presented in this paper. According to the fact that the multiple scattering component of radiance is less sensitive to the error of phase function than the single scattering component is,we calculate the multiple scattering component by using delta-Eddington approximation and the single scattering component by solving radiative transfer equation. On the ground, when multiple sattering component is small, for example, when the total optical depth T is small, the accurate radiance can be obtained with this method. For the need of the space remote sensing, the upward radiance at the top of the atmosphere is mainly studied, and an approximate expression is presented to correct the multiple scattering component. Compared with the more precise Gauss-Seidel method.the results from this method show an accuracy of better than 10% when zenith angle 0 < 50 掳 and T < 1. The computational speed of this method is, however, much faster than that of Gauss-Seidel method.

An Open Environment for Cooperative Equational Solving

We describe a system called CFLP which aims at the integration of the best features of functional logic programming (FLP), cooperative constraint solving (CCS), and distributed computing. FLP provides support for defining one's own abstractions over a constraint domain in an easy and comfortable way, whereas CCS is employed to solve systems of mixed constraints by iterating specialized constraint solving methods in accordance with a well defined strategy. The system is a distributed implementation of a cooperative constraint functional logic programming scheme that combines higher order lazy narrowing with cooperative constraint solving. The model takes advantage of the existence of several constraint solving resources located in a distributed environment (e.g., a network of computers), which communicate asynchronously via message passing. To increase the openness of the system, we are redesigning CFLP based on CORBA. We discuss some design and implementation issues of the system.

Self-directed learning readiness and social problem solving of nursing students in Macao

Objective The aims of this study were to describe nursing students′self-directed learning readiness and social problem solving and test their correlations in Macao.Methods This descriptive cross-sectional study was conducted on 140baccalaureate nursing students.A stratified random sampling was performed.The Self-directed Learning Readiness(SDLR)Scale and Chinese Social Problem-Solving Inventory-Revised(C-SPSI-R)were used.Results The response rate was 79.3%.Students possessed readiness for self-directed learning(mean 149.09±12.53,51.4%at high level,48.6%at low level).Regarding to social problem solving,the mean scores of each subscale were 9.35±3.25(Rational Problem Solving,RPS),10.26±3.23(Positive Problem Orientation,PPO),8.14±4.06(Negative Problem Orientation,NPO),5.67±4.44(Avoidance Style,AS),and 4.84±3.03(Impulsivity/Carelessness Style,ICS).SDLR was positively related to RPS and PPO,but was negatively related to AS.Conclusion Half of students possessed stronger readiness for self-directed learning.Students had a belief in the ability to solve problems,and adopted relevant strategies in solving problems.However,students still had negative and dysfunctional orientation and defective attempts in solving problems.Self-directed learning was positively related to positive and constructive orientation,but was negatively related to defective problem-solving pattern.Nurse educators should create educational climates for promoting student confidence and mutual responsibility for learning and their thinking process for problem solving.

Is it Visual? The Importance of a Problem Solving Module within a Computing Course

This paper looks at student's view of the usefulness of a problem solving and programming module in the first year of a 3-year undergraduate program.The School of Science and Technology,University of Northampton,UK has been investigating,over the last seven years the teaching of problem solving.Including looking at whether a more visual approach has any benefits(the visual programming includes both 2-d and graphical user interfaces).Whilst the authors have discussed the subject problem solving and programming in the past [1] this paper considers the students perspective from research collected/collated by a student researcher under a new initiative within the University.All students interviewed either had completed the module within the two years of the survey or were completing the problem-solving module in their first year.

Post Secondary Students’ Level of Proficiency in Solving Real World Problems in Mathematics

The problem solving competency is the primary goal in all mathematics education curricula. It is acquired by solving mathematical problems belonging either to routine or non-routine category. The study describes the post-secondary students’ levels of proficiency in solving non-routine math problems. The three-stage process in solving mathematics problems by Mayer was used as the frame of analysis. Using the data generated from researcher made instruments, and semi-structured interview of 50 purposively selected participants, the study found that: Majority of the participants showed “good proficiency” in “problem representation” and “problem solving”, the real world problems in Math. It is also revealed that those who are good in problem representation phase are also good in problem solution phase. In general, participants do not always consider answer verification phase as important in the process of solving real world problems in math. The most common difficulties encountered by participants are: language inadequacy and unfamiliarity with the context of the problems. The researchers recommended that the same study be done in some other context and local and if the results are consistent with this study, may consider redesigning new curriculum in post-secondary mathematics education.

An ADI technique for solving three-dimensional coastal circulation

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Use of Analogy by Public Health Nurses in Problem Solving for Individual Consultations in Japan: A Multiple Case Study

Aim: Nurses must develop good problem-solving skills (PSS) to work in the complex health care environment. This study explored PHNs’ use of analogy in PSS development. The purposes of the study were to clarify how PSS developed in one area (i.e., mental health) could be applied to another area (i.e., maternal health) and whether new PSS could develop in response to PSS gained in another area. Methods: A multiple case study was conducted using interviews. We interviewed 27 consultations from eight Japanese PHNs who consulted in mental health departments before transferring to maternal health departments. The data on how PHNs applied PSS in the selection, mapping, evaluation, and learning stages of the analogy process were extracted from transcribed interviewed data and compared. Results: PHNs provided 59 PSS used in 27 consultations. All PHNs applied past mental health PSS to solve new problems in maternal health. They tended to select past PSS based on structural similarity and to apply PSS via low-level abstraction in serious situations or preventively to avoid causing the current situation to worsen. Notably, PHNs developed maternal health PSS by using past mental health PSS;these new PSS were derived through analogy from various failures and successes. Conclusions: PSS developed in one area can be applied in another area, and new PSS can develop through applying these previous PSS. Identification of structural similarities and preventive analogies must be included in nursing education, especially for nurses working in public health fields.

The Continuous Analogy of Newton’s Method for Solving a System of Linear Algebraic Equations

We propose a continuous analogy of Newton’s method with inner iteration for solving a system of linear algebraic equations. Implementation of inner iterations is carried out in two ways. The former is to fix the number of inner iterations in advance. The latter is to use the inexact Newton method for solution of the linear system of equations that arises at each stage of outer iterations. We give some new choices of iteration parameter and of forcing term, that ensure the convergence of iterations. The performance and efficiency of the proposed iteration is illustrated by numerical examples that represent a wide range of typical systems.

Problem-Solving Based Intervention for Informal Caregivers: A Scoping Review

Background: Caregiving for someone is a huge task for informal caregivers. The caregiving role is often challenging and overwhelming for them. Stress, burden, and depression have been frequently identified as the negative caregiving experiences. This systematic review synthesized the available evidence for the problem-based intervention provided for caregivers as there is little insight about the effects of problem-based intervention on caregivers. Objectives: To describe: 1) the design of problem-solving intervention;2) the effects of problem-solving intervention for caregiver outcomes. Methods: This review followed Arksey and O’Malley’s methodological framework for conducting scoping reviews which entail setting research questions, selecting relevant studies, charting the data and synthesizing the results. FPRISMA guidelines were adopted and several databases were searched including MEDLINE;EMBASE;web of science. This review contains literature from 2012 to 2019 on problem-solving-based intervention which intended to caregivers. Results: 41 publications representing 27 unique problem-based interventions. Problem-solving-based intervention has different extent effects on caregiver emotion status, burden and quality of life. Conclusions: Problem-solving intervention is promising in caregiver intervention which could reduce caregiver depression, anxiety and burden.

Kolmogorov entropy changes and cortical lateralization during complex problem solving task measured with EEG

The objective is to study changes in EEG time-domain Kolmogorov entropy and cortical lateralization of brain function areas during complex problem solving mental task in healthy human subjects. EEG data for healthy subjects are acquired during complex problem solving mental task using a net of 6 electrodes. The subject was given a nontrivial multiplication problem to solve and the signals were recorded for 10s during the task. Kolmogorov entropy values during the task were calculated. It was found that Kolmogorov entropy values were obviously greater in P4 channel (right) than ones in P3 channel (left) during complex problem solving task. It indicated that all subjects presented significant left parietal lateralization for the total frequency spectrum. These results suggest that it may be possible to noninvasively lateralize, and even eventually localize, cerebral regions essential for particular mental tasks from scalp EEG data.