Effective Tool Research Articles

Surface-Based Probabilistic Fiber Tracking in Superficial White Matter.

The short association fibers or U-fibers travel in the superficial white matter (SWM) beneath the cortical layer. While the U-fibers play a crucial role in various brain disorders, there is a lack of effective tools to reconstruct their highly curved trajectory from diffusion MRI (dMRI). In this work, we propose a novel surface-based framework for the probabilistic tracking of fibers on the triangular mesh representation of the SWM. By deriving a closed-form solution to transform the spherical harmonics (SPHARM) coefficients of 3D fiber orientation distributions (FODs) to local coordinate systems on each triangle, we develop a novel approach to project the FODs onto the tangent space of the SWM. After that, we utilize parallel transport to realize the intrinsic propagation of streamlines on SWM following probabilistically sampled fiber directions. Our intrinsic and surface-based method eliminates the need to perform the necessary but challenging sharp turns in 3D compared with conventional volume-based tractography methods. Using data from the Human Connectome Project (HCP), we performed quantitative comparisons to demonstrate the proposed algorithm can more effectively reconstruct the U-fibers connecting the precentral and postcentral gyrus than previous methods. Quantitative validations were then performed on post-mortem MRIs to show the reconstructed U-fibers from our method more faithfully follow the SWM than volume-based tractography. Finally, we applied our algorithm to study the parietal U-fiber connectivity changes in autosomal dominant Alzheimer's disease (ADAD) patients and successfully detected significant associations between U-fiber connectivity and disease severity.

A Semi-Implicit Parallel Leapfrog Solver With Half-Step Sampling Technique for FPGA-Based Real-Time HIL Simulation of Power Converters

Field Programmable Gate Array (FPGA) based Hardware-in-the-loop (HIL) simulation is an effective tool to verify the performance of physical controllers and shorten the development cycle of power converters. In HIL simulations, sampling accuracy is of concern and is desired to be improved by reducing the step size. However, due to the cost of computational time, the step size is hard to reduce indefinitely to meet the requirements for high switching frequency applications. To improve the sampling accuracy and simulation performance of HIL simulation, this paper proposes a semi-implicit parallel leapfrog (SPL) solver with half-step sampling technique. In this solver, the switches and the rest part of the system are implemented to be computed parallel when the switch leg model operates in continuous current mode. Besides, the solver is formulated in leapfrog format to reduce computational costs and to compute at half-step as a minimum step-size. With this format, the half-step sampling technique can be employed to increase the sampling rate by onefold, even in cases where it is challenging to reduce the simulation step size further. A dual active bridge converter case is implemented on the FPGA board with a 12.5-ns sampling step-size, retaining the simulation accuracy while switched at 400 kHz. To further verify the advantages, the results are compared with other HIL method and experimental results.

Energy loss analyses of amorphous magnetic ribbons by multi-frequency single sheet tester

Due to low values of both thickness and conductivity, Fe-based amorphous soft magnetic ribbon (AR) is an attractive alternative to crystalline silicon steel (CS) for elevated frequencies f up to several kHz. On the other hand, for corresponding tests of losses P, the only standardized method is restricted to just 400 Hz. Recently, we reported “Physically Consistent Loss Testing” (CLT) for loss tests of CS for f up to 10 kHz. Here, we describe an adaptation of a corresponding multi-frequency single sheet tester for AR-applications. The CS single sheet is replaced by six 50 cm long and 17 cm wide ARs, loosely inserted into a paper envelope. This “envelope technique” provides (i) simple sample arrangement in an absolutely flat state, (ii) high repeatability, (iii) robust sensor signals, (iv) avoidance of loss increases due to magneto-mechanical effects, and (v) averaging over thickness variations of ARs through as much as 100 g of sample mass. Here, we report the results of frequency analyses for sinusoidal magnetization in the longitudinal direction for induction up to 1.5 T for f < 1 kHz and 0.4 T for 10 kHz, with P up to 50 W/kg. Anisotropy tests confirm a very weak dominance of the transverse direction. In conclusion, CLT proves to be an effective tool for loss tests on both CS and AR as a physically consistent principle. Therefore, for the ongoing standardization of SST with H-coil, we recommend considering the integration of the “envelope technique” in order to establish rapid and universal multi-frequency loss testing.

Development and Validation of a Novel Predictive Model for the Early Differentiation of Cardiac and Non-Cardiac Syncope.

The diagnosis of cardiac syncope remains a challenge. This study sought to develop and validate a diagnostic model for the early identification of individuals likely to have a cardiac cause. 877 syncope patients with a determined cause were retrospectively enrolled at a tertiary heart center. They were randomly divided into the training set and validation set at a 7:3 ratio. We analyzed the demographic information, medical history, laboratory tests, electrocardiogram, and echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. Then a multivariable logistic regression analysis was performed to identify independent predictors and construct a diagnostic model. The receiver operating characteristic curves, area under the curve (AUC), calibration curves, and decision curve analysis were used to evaluate the predictive accuracy and clinical value of this nomogram. Five independent predictors for cardiac syncope were selected: BMI (OR 1.088; 95% CI 1.022-1.158; P =0.008), chest symptoms preceding syncope (OR 5.251; 95% CI 3.326-8.288; P <0.001), logarithmic NT-proBNP (OR 1.463; 95% CI 1.240-1.727; P <0.001), left ventricular ejection fraction (OR 0.940; 95% CI 0.908-0.973; P <0.001), and abnormal electrocardiogram (OR 6.171; 95% CI 3.966-9.600; P <0.001). Subsequently, a nomogram based on a multivariate logistic regression model was developed and validated, yielding AUC of 0.873 (95% CI 0.845-0.902) and 0.856 (95% CI 0.809-0.903), respectively. The calibration curves showcased the nomogram's reasonable calibration, and the decision curve analysis demonstrated good clinical utility. A diagnostic tool providing individualized probability predictions for cardiac syncope was developed and validated, which may potentially serve as an effective tool to facilitate early identification of such patients.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

BackgroundMalignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer. MethodsThe BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool. ResultsBRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans. ConclusionThe MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Effect of Cognitive Behavioral Therapy on tobacco usage and dependency among adult male tobacco users in Palam area of Delhi

Background: Tobacco use is a recognized risk factor for many chronic diseases such as chronic obstructive pulmonary disease (COPD), hypertension, cardiovascular disease, atherosclerosis, diabetes, cancer and microbial infections (respiratory tract infections, bacterial meningitis), etc. Material and Methods: A community-based "One group" interventional study was conducted to see the effect of cognitive behavioural therapy in reducing tobacco usage and its dependency among all the adult males population aged 18 years and above residing in Palam area of Delhi. Data was collected using a semi-structured, self-designed interview schedule to collect information from study subjects. Fagerstrom and Modified Fagerstrom questionnaire was used to assess the subject’s nicotine dependence status. Result: The total population study was 274 out of which 105 were tobacco users. Out of 105,2 did not give consent for cognitive behaviour therapy.A total of 103 study subjects were given cognitive behavioral therapy and then followed at 2 weeks, 4 weeks, 3 months, and 6 months respectively, and analyzed for quitting at each follow-up. Study subjects who had quitted tobacco was 11 i.e. 10.6%. Change in Nicotine dependency was statistically significant. Conclusion: Cognitive behaviour therapy is found to be a very effective tool in reducing tobacco usage as well as nicotine dependency.

Анализ по методу иерархий информационных инструментов в обеспечении расчетов стоимости в гражданском судостроении

Currently, the development of shipbuilding is one of the critically important areas of Russia's industrial policy. According to the “Strategy for the development of the shipbuilding industry for the period up to 2035”, optimization of production facilities, their modernization and technical re-equipment, among others, are identified as its key tasks. The issue of digitalization of shipbuilding design is relevant, namely, the development and implementation of effective digital tools for the modernization and development of work on the design of shipbuilding facilities in terms of work on determining the cost of their construction and preparation of feasibility studies. The article considers the creation of a concept for the structure of digital tools to ensure the production of cost calculations in the process of designing civil shipbuilding facilities. A comprehensive analysis of the digitalization processes of the industry and the dynamics of the development of regulatory and methodological support for calculating the cost of designed products made it possible to formulate the key advantages of introducing digital technologies in the paradigm of digital transformation of shipbuilding, as well as to justify the expediency of searching and developing relevant digital tools in ensuring production processes in shipbuilding, in particular when preparing cost calculations for projected facilities. The choice of the most effective concept of an information tool in providing cost calculations for projected objects in the field of civil shipbuilding was carried out using the hierarchy analysis method. The criteria by which an effective alternative was chosen are formulated, three possible alternatives of an information tool in providing cost calculations for projected objects in the field of civil shipbuilding are considered.

Cash flow management, performance and risk: evidence from Greece

PurposeI seek to identify whether cash flow management can affect the performance and risk of the Greek listed companies.Design/methodology/approachThis study examines the relationship of cash flow management with performance and risk, using a sample of 80 non-financial companies listed in the Athens Exchange. The study covers the period 2018–2022, and panel data analysis is applied. Both financial performance and stock return are taken into consideration, while risk concerns the volatility of the companies’ share prices. The various explanatory variables used include the net cash flow, free cash flow, cash conversion cycle days, cash flow from operating activities, cash flow from investing activities, cash flow from financing activities, inventory days, customer days and supplier days.FindingsThe empirical results provide evidence of a positive relationship between financial performance and net cash flow and free cash flow. In addition, operating cash flow is positively related to financial performance. The opposite is the case for investing and financing cash flow. Finally, some evidence of a negative relationship between financial performance and inventory and customer days is provided too. On the other hand, stock return and risk are not related to the cash flow management variables at all.Originality/valueTo the best of my knowledge, this is one of the few studies to examine the relationship of cash flow management with performance and risk, using data from the Greek stock market. The results can form an effective selection tool for investors seeking Greek companies with the highest financial performance potential, which may reward them with higher dividends.

Physics learning module on google sites-assisted case-based learning measure-ment material

This study introduced the development of a physics learning module on the topic of measurements based on case-based learning, supported by Google Sites. In the research background, the importance of innovative approaches in physics education for enhancing student understanding had been recognized. Therefore, the primary aim of this research was to develop an effective instructional module that would improve students' comprehension of measurement concepts. The research adopted a research and development approach using the 4D development model (Define, Design, Develop, Disseminate). During the "Define" phase, the need for the module and the scope of the teaching material were identified. Subsequently, in the "Design" phase, the module structure was designed, and case-based learning strategies were planned. The "Develop" phase involved creating the module as per the specified design, including the integration of case-based scenarios and the utilization of the Google Sites platform. In the final "Disseminate" phase, an assessment was conducted on the usability and effectiveness of the developed module. The result of this study yielded a comprehensive physics learning module centered around measurement concepts and utilizing case-based learning techniques. The module was successfully validated as an effective teaching tool capable of enhancing students' understanding of measurement concepts.

Role of Audio Visual Aids to Impart Garden-Based Nutrition Education for Preschoolers

Introduction: One of the most critical period in human life is the preschool years. In order to develop healthy food habits nutrition education need to be imparted at this age. There is a novel strategy to deliver nutrition education to children namely Garden-Based Nutrition Education (GBNE). Utilization of nutrition education tools can be an effective way for the delivery of GBNE.&#x0D; Aim: To develop PowerPoint presentation on the importance of fruits and vegetables converts to video form and a child friendly gardening video for preschool children and assess the feasibility and acceptability.&#x0D; Materials and Methods: Audio visual aids like power point presentation and videos were developed. Power point presentation on importance of fruits and vegetables was developed in such a way that it can reach the respondents and convey the intended message for preschool children with a total of 13 slides.&#x0D; A documentary child friendly gardening video was constructed having a duration of nearly seven minutes with the title “Garden Based Nutrition Education” with the intention to inculcate gardening skills among children from their early childhood years. Both the tools were developed using standardized procedures and was subjected to pre study. In order to assess the feasibility and acceptability of the developed GBNE tools it was subjected to preschool teachers/anganwadi workers and parents of preschool children. The sample consisted of 75 parents and 75 preschool teachers which was randomly selected from Kollam and Thiruvananthapuram districts of Kerala.&#x0D; Results: The study reveals that, both parents and teachers finds child friendly gardening video as the most feasible and acceptable tool to impart garden-based nutrition education.&#x0D; Discussion: Preschool children loves gardening ad watering. Child friendly gardening video is most involving and interesting in nature when compared to power point video.&#x0D; Conclusion: Therefore it can be concluded that power point video on importance of fruits and vegetables and child friendly gardening video can be used as effective GBNE tool to teach the significance of fruits and vegetables through gardening activities.

Environmental Prediction Model of Solar Greenhouse Based on Improved Harris Hawks Optimization-CatBoost

Solar greenhouses provide a favorable climate environment for the production of counter-seasonal crops in northern China. The greenhouse environment is a key factor affecting crop growth, so accurate prediction of greenhouse environment changes helps to precisely regulate the crop growth environment and helps to promote the growth of fruits and vegetables. In this study, an environmental prediction model based on the combination of a gradient boosting tree and the Harris hawk optimization algorithm (IHHO-Catboost) is constructed, and in response to the problems of the HHO algorithm, such as the fact that the adjustment of the search process is not flexible enough, it cannot be targeted to carry out a stage search, and sometimes it will fall into the local optimum to make the algorithm’s search accuracy relatively poor, an algorithm based on the improved Harris hawk optimization (IHHO) algorithm-based parameter identification method is constructed. The model considers the internal and external environmental and regulatory factors affecting crop growth, which include indoor temperature and humidity, light intensity, carbon dioxide concentration, soil temperature and humidity, outdoor temperature and humidity, light intensity, carbon dioxide concentration, wind direction, wind speed, and opening and closing of upper and lower air openings of the cotton quilt, and is input into a prediction model with a time series for training and testing. The experimental results show that the MAE (mean absolute error) values of temperature, relative humidity, carbon dioxide concentration, and light intensity of the model are reduced to 49.8%, 35.3%, 72.7%, and 32.1%, respectively, compared with LSTM (Long Short-Term Memory), which is a significant decrease in error. It shows that the proposed multi-parameter prediction model for solar greenhouse environments presents an effective method for accurate prediction of environmental data in solar greenhouses. The model not only improves prediction accuracy but also reduces dependence on large data volumes, reduces computational costs, and improves the transparency and interpretability of the model. Through this approach, an effective tool for greenhouse agriculture is provided to help farmers optimize the use of resources, reduce waste, and improve crop yield and quality, ultimately leading to a more efficient and environmentally friendly agricultural production system.

The Energy Transition in SMEs: The Italian Experience

Encouraging energy transition (ET) has become a global imperative for nations and companies, and not just large ones. Not all economic organizations pursue this process with the same intensity. Particularly, the factors driving Small and Medium Enterprises (SMEs) towards ET are not yet clearly defined, despite SMEs representing most companies and bearing a significant responsibility for pollution. To shed light on this matter, this study presents a framework of the main drivers that stimulate SMEs placed in Italy to pursue energy transition. We conducted a Partial Least Squares (PLS) analysis on data collected from innovation-oriented SMEs enlisted in a specific register of the Italian Ministry of Economic Development. The research findings show a weak interest among SMEs towards ET. While country-specific conditions and social and psychological traits affect the decision to invest in ET, firm-specific factors and ‘stakeholder’ pressures seem to be almost irrelevant. Policy measures with a different focus are necessary. Specifically, the provision of facilitation emerges as the most effective tool for encouraging ET among SMEs.

Validation of a New Sham Acupuncture Needle for Double-Blind Trials: A Study Protocol

Background: To establish efficacy in acupuncture treatment, rigorous randomized controlled trials (RCT) are needed. Non-invasive sham acupuncture needles are an effective tool for practitioner/participant blinding. This study presents a protocol for the validation of a newly developed sham acupuncture needle.Methods: A double-blind RCT will be conducted on 66 healthy adults who will be randomly assigned (using computer-generated random numbers) to either the verum (&lt;i&gt;n&lt;/i&gt; = 33) or sham (&lt;i&gt;n&lt;/i&gt; = 33) acupuncture needle group. The needles will be inserted at 2 acupuncture points: LI4 (upper limb) and ST36 (lower limb). The primary outcome measure is the practitioner/participants belief that they received verum or sham acupuncture. The secondary outcome measures are participant-rated sensations (penetration, pain, and de qi). Adverse events will be recorded with detailed explanations, categorizing occurrences according to related or unrelated to acupuncture. As the newly developed sham acupuncture has not been studied before, an exploratory approach has been adopted. Descriptive statistics, t test, and χ² test will be applied appropriately.Results: This study is intended to provide a protocol for the validation of a sham acupuncture needle by using a double-blind RCT setting, and the results will hopefully contribute to the standardization of the needles used for sham acupuncture. The outcomes aim to determine the reliability of practitioner/participant blinding, participant experience of sensations, and lay groundwork for a standardized control group for clinical trials in the future. The newly developed non-invasive sham acupuncture needle may reduce bias and improve reliability in the size effect of acupuncture treatment.

“I Always Screen for a T Visa”: The Role of Legal Representatives in Supporting Human Trafficking Victims

ABSTRACT The T visa was created to protect immigrant victims and to strengthen law enforcement’s ability to investigate human trafficking cases. Yet, there is limited information on the process of obtaining these visas. The current study sought to fill this gap by interviewing six legal representatives in Nebraska who have assisted 22 foreign national trafficking victims from Latin America. This project addresses UN Sustainable Development Goal 16 (promoting just, peaceful and inclusive societies) by assessing how our T visa policy can protect vulnerable individuals from harm. Findings highlight the importance of law enforcement certification, challenges in filing the T visa application, and hardships if the T visa is not granted. Representatives noted that individuals who were approved were able to obtain employment and enroll in school. Other victims were still waiting on the results of their filed application, were still in consultations, or had been denied – resulting in uncertainty or deportation. Overall, the T visa was seen as an effective tool for responding to trafficking when it was successful. However, obtaining approval is an onerous task that can take substantial time and resources to meet all criteria. It will be important for future research to continue to explore the T visa process and outcomes.

Measuring Online Customer Satisfaction Based on Customer Reviews: Topic Modeling Method Using Latent Dirichlet Allocation (LDA) Algorithm

Companies invest significant resources in retaining their customers. Nonetheless, organizations have witnessed customer attrition due to inadequate loyalty. This trend is particularly prevalent among online customer bases. The root cause of this issue lies in the absence of an effective tool for measuring online customer satisfaction that surpasses the capabilities of existing methods. To address this concern, a quantitative study explored the dimensions of online customer satisfaction measurement and established a model applicable across industries for gauging and predicting online customer satisfaction. This was accomplished by conducting an online survey via SurveyMonkey with 384 respondents, employing supervised and unsupervised machine learning techniques in conjunction with the topic modeling algorithm, Latent Dirichlet Allocation (LDA). The findings of this study revealed a significant relationship between predictor variables such as navigation, playfulness, information quality, trust, personalization, and responsiveness and the target variable, online customer satisfaction, employing multiple linear modeling (LSM). Furthermore, it was observed that this phenomenon transcends age groups, impacting both younger and older customers alike. However, it is essential to acknowledge certain limitations, including the risk of overfitting, challenges in establishing external validity, a narrow focus on the retail sector (B2C), and a restricted scope limited to the United States market.

Application of Problem-Solving Learning to Improve Mathematics Learning Outcomes in Elementary Schools

Application of Problem-Solving Learning to Improve Mathematics Learning Outcomes in Elementary Schools

Media and its dominance in contemporary Iraqi painting

The current study deals with the topic of the effectiveness of narrated, visual, and printed media as documents and data conveying the culture and knowledge of people, as well as a discursive structure with sensory authority that affected the nature of the artistic experience through the dynamic interaction between the artist’s creative intentions and his experience, in addition to the intellectual and historical influences resulting from the power of the medium as an effective tool in directing the artist’s vision The research was divided into four chapters, first chapter devoted to the research problem, which ended with the following question: What are the areas of media structure and how do they dominated on the visual surface appearances? The second chapter, it included two sections, the first section entitled Mediality of language/versus the oral and the copied, while the second section was entitled Mediality of the Image/versus the audio-visual. The third chapter contained the research procedures represented by the method, community, research tool, and analysis of the research sample which included three models. The fourth chapter included the results and conclusions. The following are some of the results: 1-The effectiveness of the medium emerged as a symbolic and ideological material that enhances the concept of cultural identity through artists adopting it. 2-The media appeared as a reference that carries data from which the artist draws his cultural and historical topics, as well as daily events.

Wood identification based on macroscopic images using deep and transfer learning approaches.

Identifying forest types is vital for evaluating the ecological, economic, and social benefits provided by forests, and for protecting, managing, and sustaining them. Although traditionally based on expert observation, recent developments have increased the use of technologies such as artificial intelligence (AI). The use of advanced methods such as deep learning will make forest species recognition faster and easier. In this study, the deep network models RestNet18, GoogLeNet, VGG19, Inceptionv3, MobileNetv2, DenseNet201, InceptionResNetv2, EfficientNet and ShuffleNet, which were pre-trained with ImageNet dataset, were adapted to a new dataset. In this adaptation, transfer learning method is used. These models have different architectures that allow a wide range of performance evaluation. The performance of the model was evaluated by accuracy, recall, precision, F1-score, specificity and Matthews correlation coefficient. ShuffleNet was proposed as a lightweight network model that achieves high performance with low computational power and resource requirements. This model was an efficient model with an accuracy close to other models with customisation. This study reveals that deep network models are an effective tool in the field of forest species recognition. This study makes an important contribution to the conservation and management of forests.

HABERTAN: Game Petualangan 3D Dengan Tema Pemilahan Sampah Sebagai Upaya Pendekatan Inovatif Untuk Pengenalan Lingkungan

The increasing awareness of the importance of maintaining forest cleanliness as a primary ecosystem is becoming more urgent, especially in remote areas with limited deep socialization. This research aims to develop an innovative game titled "HABERTAN" focusing on waste sorting in forest areas to raise public awareness of the waste present in the forest. By utilizing a 3D model for visual assets with stages of 2D sketch, 3D modeling, UV Mapping, and Texture Baking. The development of this game is conducted using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) method. The ADDIE method is used to ensure a systematic game development process, starting from needs analysis to performance evaluation. The goal of this game is to provide players with an interactive experience that not only entertains but also provides a deep understanding of the impact of waste on forest sustainability. The game "HABERTAN (Let's Clean the Forest)" is designed to provide players with a fun and educational learning experience. The results of the development of this game show that "HABERTAN" provides a unique experience for players, with the ability to learn while playing. It is hoped that this game can be an effective tool in raising public awareness of the importance of maintaining forest cleanliness, especially in the context of waste sorting. Through this innovative approach, it is hoped to encourage active participation from the community in preserving forests as extremely valuable natural resources.

Effectiveness of simulation-based paediatric cardiopulmonary resuscitation training program among nursing students in Saudi Arabia.

The main objective of this study was to adopt a simulation-based advanced cardiac life support training program to assess nursing students' level of knowledge and practice regarding paediatric advanced cardiac life support and to identify the major knowledge and practice gaps. The methods used in this study were pre-experimental, one group pre and post-test investigation. This study was conducted between September 2022 and November 2022, at the University College of Farasan in the Kingdom of Saudi Arabia. Quantitative data were obtained using the "Cardio Pulmonary Resuscitation Knowledge Questionnaire", "Students' Satisfaction and Self-Confidence Scale," and the "CPR Skill Checklist," which were applied to 75 participants in focus groups. Before the simulation-based CPR training, the students' mean pre-test Paediatric CPR knowledge score was 6.5±2.3 out of 42.0. After the simulation, the mean post-test CPR knowledge score (38.1±2.9) considerably improved (p 0.05). The mean post-test CPR skills score (44.7±1.2) was also considerably higher than the mean pre-test CPR skills score (11.4±2.8) at (p 0.05). Additionally, after the simulation training, students' happiness and confidence levels (61.9±2.2) greatly increased. Themes from the qualitative data showed that the simulation was viewed as an engaging and effective teaching tool by the students. Two themes emerged from the study: "Worries before simulation" and "Satisfaction after simulation". Simulation-based paediatric cardio Pulmonary resuscitation training program has raised nursing students' level of expertise in knowledge, performance, and self-efficacy. Additionally, strong satisfaction and self-confidence levels were discovered following the simulation training.