Three-stage Procedure Research Articles

Nanofiltration membrane comprising structural regulator Cyclen for efficient Li+/Mg2+ separation

Selective lithium recovery from salt lake brine using emerging nanofiltration membranes is expected to solve the insufficient supply of lithium resources. In this work, 1,4,7,10-tetraazacyclododecane (Cyclen) was employed as a novel structural regulator through interfacial polymerization of polyethyleneimine (PEI) and trimesoyl chloride (TMC) to develop polyamide NF membrane with efficient Li+/Mg2+ separation performance. After the introduction of Cyclen to aqueous phase, the PEI/Cyclen-TMC selective layer was confirmed to possess a higher crosslinking degree and larger d-spacing than PEI-TMC layer, endowing a dedicated channel for Li+ transport. The water permeance of PEI/Cyclen-TMC composite membrane reached 14.0 L·m−2·h−1·bar−1, about 3.8 times higher than PEI-TMC composite membrane, and meanwhile the separation factor (SLi,Mg) could be stabilized as 8.7 to realize a considerable reduction of Mg2+/Li+ mass ratio from 20 to 2.3. Additionally, PEI/Cyclen-TMC composite membrane was utilized to operate a three-stage nanofiltration treatment procedure of a simulated salt lake brine (Mg2+/Li+ mass ratio: 40). The results indicated that Li+ could be efficiently retracted to obtain a solution with 19.5 mg·L−1 Li+ and Mg2+/Li+ mass ratio of 0.3. After the subsequent precipitation and filtration, the obtained Li2CO3 purity could reach 93 %, indicating the potential application of nanofiltration for lithium recovery.

Chemical Speciation of Trace Elements in Soil Fertilized with Biomass Combustion Ash and Their Accumulation in Winter Oilseed Rape Plants

The impact of fertilization of fly ashes from biomass combustion (BAs) on the changes in the chemical speciation of trace elements (Zn, Cu, Cr, Ni, Pb, Cd) in Gleyic Chernozem soil was analyzed in field-experiment conditions, under cultivation of winter oilseed rape plants. The three-year field experiment was carried out in southeastern Poland (50°3′ N, 22°47′ E). The three-stage sequential extraction procedure developed by the Measurements and Testing Program (BCR) was used for the fractionation of trace elements in BAs and soil. The risk assessment code (RAC) coefficient was used to assess potential soil contamination with trace elements from Bas. The total content of Zn, Cu, Cr, Ni, Pb, and Cd in BAs used in the experiment was 470, 311, 29, 78, 38, and 3.7 mg kg−1, respectively. The present study showed that the application of BAs significantly increased the total concentration of Zn and Cu in the surface layer of the Gleyic Chernozem soil, and did not significantly increase the concentration of Cr, Ni, Pb, and Cd. Generally, using BAs does not significantly change the chemical speciation of trace elements in soil. Regardless of the applied fertilization, residual fraction (F4) was the most abundant, whereas the exchangeable/extractable (F1) fraction and reducible (F2) fraction were present in the smallest amounts. Due to the low share of exchangeable/extractable fraction (F1), the BAs used in the experiment were characterized by a low RAC coefficient; hence, their use as a soil fertilizer is relatively safe for the environment. The BAs fertilization did not cause significant changes in the content of trace elements in the different parts of the winter oilseed rape plants. Due to the relatively high content of trace elements in fly ashes from biomass combustion, an analysis of the content of individual trace element fractions should be carried out to assess their actual impact on the environment. This can help indicate further actions that should be taken to limit their negative environmental impact.

Integration of Physics- and Data-Driven Power System Models in Transient Analysis After Major Disturbances

The article explores the analysis of transient phenomena in large-scale power systems subjected to major disturbances from the aspect of interleaving, coordinating, and refining physics- and data-driven models. Major disturbances can lead to cascading failures and ultimately to the partial power system blackout. Our primary interest is in a framework that would enable coordinated and seamlessly integrated use of the two types of models in engineered systems. Parts of this framework include: 1) optimized compressed sensing, 2) customized finite-dimensional approximations of the Koopman operator, and 3) gray-box integration of physics-driven (equation-based) and data-driven (deep neural network-based) models. The proposed three-stage procedure is applied to the transient stability analysis on the multimachine benchmark example of a 441-bus real-world test system, where the results are shown for a synchronous generator with local measurements in the connection point.

Impact of Soil Conservation on Household Income in East Wollega, H/G/ Wollaga and West Shawa Zones of Oromia Region

Land degradation in many third world countries threatens the livelihood of millions of people and constrains the ability of countries to develop a healthy agricultural and natural resource base. This study was conducted to explore Impact of Soil Conservation on Household Income in East Wollega, H/G/ Wollaga and West Shawa Zones of Oromia Region. In this study, three-stage sampling procedure was used to select six districts, tuwelve kebeles and 252 specific sample farm households. Descriptive and econometric analyses were employed. This study has been designed with objective of to assess the impacts of the SWC on yields and farmers’ income, to assess community perception towards the ongoing SWC interventions. and to identify constraints and opportunities on SWC practices in the study area. The analysis is based on the data collected from randomly selected 252 farm households in western Ethiopia. a propensity score matching method for impact analysis to avoid bias arising from possible self-selection. The descriptive analysis showed that, out of the 252 household heads, in the study area the average farm size of the respondents was fragmented into 3.36 parcel, each with average 2.26 hectares. In the sampled area, 13.3%, 57.8%, 14.8%, and 14.1% of the interviewed farmers has been built SWC structures on cultivated land by SLM programme, by campaign, with their family and through both (campaign and family) respectively. The results obtained through a propensity score matching method was 7931.3 Ethiopian Birr net on household income of farmers increase for adopters as compared to non-adopters.

A novel powder-metallurgical eco-friendly recycling process for tool steel grinding sludge

This work comprehensively investigates the reuse of AISI D2 tool steel grinding sludge as secondary raw material into a powder metallurgical process route. The tool steel grinding sludge initially contains about 15 mass% of silicon carbide and aluminium oxide abrasive particles as well as residual cooling lubricant emulsion consisting of water and oil leading to an increased carbon content of 2.56 mass%. A three-stage decontamination procedure of the grinding sludge is performed, including drying, removing non-metallic abrasive particles via magnetic separation, and recovering the cooling lubricant oil by supercritical carbon dioxide extraction. Subsequently, the prepared grinding metal chips are densified by a novel energy efficient short-time sintering technique called electric discharge sintering. The carbon content of the sludge could be reduced to 1.71 mass%. However, it was found that remaining contaminations lead to a change in the alloying composition of the recycled material, which influences the tempering behavior. Increased carbon and silicon levels promoted a high retained austenite fraction after quenching of more than 67 vol%. By adopting the heat treatment, the hardness of the recycled samples could be adjusted to a level similar to that of the cast reference material in quenched and tempered condition. Reducing the retained austenite content to 2.3% by tempering led to a hardness of roughly 700 HV1.However, the recycled material showed less than 40% of the compressive strength of the cast reference material. On the one hand, the lower compressive strength can be attributed to the inadequate removal of oxidic abrasive particles during the recycling process and their poor integration into the metal matrix of the compacted specimens. In addition, oxidized layers on the chip surfaces counteract metallurgical bonding between the chips during electric discharge sintering.

ANALYSIS OF CASSAVA TUBER MARKETING IN RURAL AND URBAN MARKETS IN EDO SOUTH AGRO-ECOLOGICAL ZONE, EDO STATE, NIGERIA

Cassava farmers and marketers are faced with problems bothering on poor pricing of the product locally, with attendant negative implications on their profitability. Hence, this study focused on the profitability of cassava marketing in rural and urban markets in Edo South Agro-Ecological Zone, Edo State, Nigeria. A three-stage sampling procedure was used in drawing up a sample of 161 cassava marketers from seven purposely selected major cassava markets. Data collected with the aid of a well-structured questionnaire were analyzed using descriptive statistics, budgetary analysis and regression analysis. Cassava tuber marketing was shown to be profitable in the study area with a monthly gross margin of ₦29,061.4 and a return per Naira invested of 0.29 (29%) for rural marketers. Urban marketers had a mean monthly gross margin of ₦19, 961.3 per marketer and a return per Naira invested of 0.32 (32%). Rural markets were found to be more efficient (576.78%) than urban markets (168.84%). The major factor militating against the farmers and marketers in their adopted management practices was having little money to spend. It is concluded that in order to improve the profitability of cassava tuber marketers in the study area, measures should be taken to cut down on the cost of transportation.

Analysis of factors affecting technical efficiency of A1 smallholder maize farmers under command agriculture scheme in Zimbabwe: The case of Chegutu and Zvimba Districts

In an effort to address the decline in maize productivity, the government of Zimbabwe in 2016/17 endorsed a special program for input support named command agriculture scheme (CAS). Against this background, the study questioned the beneficiaries’ technical efficiency and factors that influence farmers to gravitate towards the frontier using Chegutu and Zvimba districts of Zimbabwe as case studies. The study used a cross-sectional survey of 240 households randomly selected through a three-stage multiple-sampling procedure. The single-stage modelling stochastic frontier approach was applied to assess technical efficiency of A1 smallholder command agriculture maize farmers. The study revealed that A1 smallholder command agriculture maize farmers in Chegutu and Zvimba districts were technically efficient at 85% and 94%, respectively. The major determinants of technical efficiency were basal fertilizer, labour, area allocated to maize production and topdressing fertilizer which all indicated a positive relationship. The main determinants of technical inefficiency were age, maize farming experience, level of education, marital status, occupation status and other sources of income. Results further revealed that farmers from Chegutu district had increasing returns to scale (1.43) while farmers from Zvimba district had decreasing returns to scale (0.54). The study therefore argues that despite the observed high technical efficiencies, Chegutu farmers could bridge their 15% gap between the observed output and the frontier output by focusing more on input usage with increasing returns to scale while Zvimba farmers could bridge their 6% gap by focusing more on socio-economic drivers of technical inefficiency given their decreasing returns to scale.

APESTNet with Mask R-CNN for Liver Tumor Segmentation and Classification.

Diagnosis and treatment of hepatocellular carcinoma or metastases rely heavily on accurate segmentation and classification of liver tumours. However, due to the liver tumor's hazy borders and wide range of possible shapes, sizes, and positions, accurate and automatic tumour segmentation and classification remains a difficult challenge. With the advancement of computing, new models in artificial intelligence have evolved. Following its success in Natural language processing (NLP), the transformer paradigm has been adopted by the computer vision (CV) community of the NLP. While there are already accepted approaches to classifying the liver, especially in clinical settings, there is room for advancement in terms of their precision. This paper makes an effort to apply a novel model for segmenting and classifying liver tumours built on deep learning. In order to accomplish this, the created model follows a three-stage procedure consisting of (a) pre-processing, (b) liver segmentation, and (c) classification. In the first phase, the collected Computed Tomography (CT) images undergo three stages of pre-processing, including contrast improvement via histogram equalization and noise reduction via the median filter. Next, an enhanced mask region-based convolutional neural networks (Mask R-CNN) model is used to separate the liver from the CT abdominal image. To prevent overfitting, the segmented picture is fed onto an Enhanced Swin Transformer Network with Adversarial Propagation (APESTNet). The experimental results prove the superior performance of the proposed perfect on a wide variety of CT images, as well as its efficiency and low sensitivity to noise.

Retrograde Intrarenal Surgery for Nephrolithiasis with Partially Migrated Renal Artery Embolisation Coil: A Case Report

Transcatheter renal artery embolisation is an effective and minimally invasive treatment option for acute renal bleeding. However, it is associated with a variety of complications, which can be classified as early or late according to the time of presentation. Coil migration leading to renal calculi formation is a late complication of transcatheter or percutaneous renal arterial embolisation. A 47- year-old diabetic male patient presented with a recurrent right renal staghorn calculus. Four years ago, the patient underwent a right Percutaneous Nephrolithotomy (PCNL). Following the procedure, he had to undergo a renal arterial embolisation for postoperative haemorrhage. The patient this time did not consent for repeat PCNL, therefore a staged right Retrograde Intrarenal Surgery (RIRS) was performed. Complete clearance of stone and extraction of the migrated coil was achieved in a three-staged procedure. Embolisation coils in the proximity of the pelvi-calyceal system, can migrate into the system, and form a nidus for stone formation. These stones and the migrated coil can be managed effectively and safely with RIRS.

An Efficient and Secured Triple-Layered Wireless Sensor Network with Machine Learning Techniques

Replacement of physical labor and repetitive tasks by the agents is an attractive issue in the Smart Environment (SE). SE is distinguished by its ability to be controlled from a distance, to facilitate the connection between devices through middleware, to gather and share data from sensors, to improve the intelligence of devices, and to make decisions. To be effective, SE design must make use of information and networks that already exist in the actual world. Effective SE design is complicated by several difficulties, including monitoring, data collecting, assessment, evaluation, prediction of important data, and meaningful presentation. For SE, the most important step is gathering information from a variety of sensors in various locations. Wireless sensor networks provide an underlying architecture for the coordinated collection of data from many sensors that have common characteristics (WSN). An essential aspect of sensor networks is their inability to function in the currently complicated environment for wireless network security. In the realm of remote sensor businesses, cryptology is an essential part of safety measures. Several of the prevalent cryptographic methods have significant flaws that prevent them from being fully reliable. In this paper, we provide a unified, three-stage cryptographic procedure that combines public-key and secret-key techniques for maximum security. Due to consideration of Public-key management and high degree of security, Rijndael Encryption Approach (REA), Horst Feistel's Encryption Approach (HFEA), and the more sophisticated Rivest-Shamir-Adleman (e-RSA). Time spent in both execution and decoding of the suggested approach was utilized to rank the quality of displays. The suggested set of rules uses a single evaluation boundary or computation time, which is different from the methodologies used before. Low Encryption Time (LET) and Low Unscrambling Time (LDT) values of 1.12 and 1.26 were observed on texts ranging in size from 6 to 184 MB, respectively. Comparisons show that the suggested hybrid form is 2.9% more efficient than AES+RSA, 1.36 times more efficient than ECC+RSA+MD-5, 1.36 times more efficient than AES+ECC, and 1.36 times more efficient than AES+ECC+RSA+MD-5.

Building Occupancy Detection and Localization Using CCTV Camera and Deep Learning

Occupancy information plays a key role in analyzing and improving building energy performance. The advances of Internet of Things (IoT) technologies have engendered a shift in measuring building occupancy with IoT sensors, in which cameras in closed-circuit television (CCTV) systems can provide richer measurements. However, existing camera-based occupancy detection approaches cannot function well when scanning videos with a number of occupants and determining occupants’ locations. This article aims to develop a novel deep-learning-based approach for better building occupancy detection based on CCTV cameras. To do so, this research proposes a deep-learning model to detect the number of occupants and determine their locations in videos. This model consists of two main modules, namely, feature extraction and three-stage occupancy detection. The first module presents a deep convolutional neural network to perform residual and multibranch convolutional calculation to extract shallow and semantic features, and constructs feature pyramids through a bidirectional feature network. The second module performs a three-stage detection procedure with three sequential and homogeneous detectors which have increasing Intersection over Union (IoU) thresholds. Empirical experiments evaluate the detection performance of the approach with CCTV videos from a university building. Experimental results show that the approach achieves the superior detection performance when compared with baseline models.

Integral methods of measuring the population life quality in local communities of the region

The presented article discusses the method of constructing an integral indicator of measuring the life quality. An important problem in assessing the life quality of the population is the complex nature of this concept, covering a variety of quantitative and qualitative characteristics. Currently, in the absence of the possibility of conducting scientific research on a wide range of indicators at once, selective methods are used using a small number of indicators for assessing the life quality of the population. The authors propose to use a three-stage procedure for constructing an integral indicator based on the calculation of primary indicators, the procedure for their normalization and the construction of the final integral indicator for assessing the life quality of the population. Such a technique opens up wide opportunities for further scientific regional research, since it allows conducting research in the context of local territories of the region, as well as on the entire region scale.

Application of cloud computing and big data in three-stage dynamic modeling of disaster relief logistics and wounded transportation: a case study.

Collecting and sharing information about affected areas is an important activity for optimal decision-making in relief processes. Defects such as over-sending some items to affected areas and mistakes in transferring injured people to medical centers in accidents are due to improper management of this information. Because cloud computing as a processing and storage platform for big data is independent of the device and location and can also perform high-speed processing, its use in disasters has been highly regarded by researchers. In this environment, a three-stage dynamic procedure for evacuation operations and logistics issues is presented. The first stage of the proposed model is image processing and tweet mining in a cloud center in order to determine the disaster parameters. In stage II, a mixed-integer multi-commodity model is presented for the relief commodity delivery, wounded people transportation with capacity constraints, and locating of the possible on-site clinics and local distribution centers near disaster areas. In stage III, by using a system of equations, detailed vehicle load/unload instructions are obtained. Finally, the effectiveness of the proposed model on the data of an earthquake disaster in Iran is investigated. The results of comparing the proposed approach with a two-stage algorithm show that the total number of unsatisfied demand for all types of commodities in the proposed approach was better than the other. Also, the number of survivors in the three-stage model is significantly higher than in the two-stage one. The better performance of the proposed algorithm is due to the fact that online data is continuously available and that decisions such as sending relief items and dispatching are made more effectively.

Food Expenditure Pattern of Household in Delta State, Nigeria: Economic Rationality Essentials

Parametric utility model that predicts preferences of heterogeneous food consumers is flawed with issues of economic rationality. Using axiomatic preference indexes on food data from 459 household selected from a three-stage sampling procedure, the aim of the study was to check whether a finite set of price and demand observations made on household consumers in Delta state is rationalizable by some form of utility maximization that is common across all households. The study found heterogeneity in food consumption behaviour with evidence against rationality in utility maximization for food expenditure choices at Afriat Efficiency Index (AEI) of unity, violating the GARP, SARP, SGARP, HARP and CM outside the optimum AEI of between 0.536 and 0.982 inclusive. In three of the four food choice categories, households had below the Varian AEI threshold of 0.95. Particularly, household expenditure behavior in the State violated the GARP axiom of revealed preference at 0.018, 0.07, 0.104, 0.05, and 0.081 severity of violations for food in general, protein, carbohydrate, fats and oil, and fruits and vegetables sub-food categories respectively with 5-45% of inconsistent household behaviour. At AEI of unity, 14.30%, 4.79%, 11.43% and 45.04% of the households failed the zero tolerance in the carbohydrate, protein, fats and oil, and fruits and vegetables categories respectively. Only about three to six revealed preferences were found necessary to fully rationalise observed food expenditure choices in the State. Thus, not only are households irrational in utility maximization, there is unstable preference in food demand. Therefore, there is, in the aggregate, no exact one continuous, strictly increasing, piecewise strictly concave, skew-symmetric, and/or homothetic preference function that would completely rationalize households food consumption behaviour in Delta state.

Employing a three-stage procedure to develop a sizing system for medical gloves

There is a need for gloves that are designed based on the dimensions of the hand of each society because the proper size is a key factor that affects performance. This study aimed to design and develop a glove sizing system for Iranian healthcare workers using anthropometric data. This study was conducted on a sample including 540 healthcare workers across Iran classified by ethnicity and gender. Thirty-three dimensions were measured as the anthropometric data. Principal Component Analysis (PCA) and clustering analysis were used to create classifications for glove sizes. The most effective dimensions in defining the hand sizes of Iranian healthcare workers were middle finger length and the handbreadth. The designed six-size system covered 94% of the sample. This system can be used to design suitable gloves for Iranians. The sizes presented can be used to compare size differences in different communities.

Home Health Care Problem with Synchronization Visits and Considering Samples Transferring Time: A Case Study in Tehran, Iran.

Health care facilities have not increased in response to the growing population. Therefore, government and health agencies are constantly seeking cost-effective alternatives so they can provide effective health care to their constituents. Around the world, health care organizations provide home health care (HHC) services to patients, especially the elderly, as an efficient alternative to hospital care. In addition, recent pandemics have demonstrated the importance of home health care as a means of preventing infection. This study is the first to simultaneously take into account nurses' working preferences and skill levels. Since transferring samples from the patient's home to the laboratory may affect the test results, this study takes into account the time it takes to transfer samples. In order to solve large instances, two metaheuristic algorithms are proposed: Genetic Algorithms and Particle Swarm Optimization. Nurses are assigned tasks according to their time windows and the tasks' time windows in a three-stage scheduling procedure. Using a case study set in Tehran, Iran, the proposed model is demonstrated. Even in emergencies, models can generate effective strategies. There are significant implications for health service management and health policymakers in countries where home health care services are receiving more attention. Furthermore, they contribute to the growing body of knowledge regarding health system strategies by providing new theoretical and practical insights.

Ergonomic Maturity Model: A tool for integrating ergonomics/human factors into organizations.

Currently, there is a need for models, methods, and tools that allow ergonomics/human factor (E/HF) practitioners to assess the level of E/HF integration into organizations from a macroergonomics perspective. This paper aims to propose the Ergonomic Maturity Model (EMM) and the tools for its application as a framework for integrating E/HF in organizations. The EMM is a macroergonomic tool that allows stakeholders to evaluate the degree of development and integration of E/HF in the organization based on a participatory and macroergonomic approach. The EMM classifies organizations into five gradual levels of maturity: Ignorance, Understanding, Experimentation, Regular use, and Innovation. In this paper, we provide a three-stage procedure for guiding the application of the EMM: preparation of the evaluation, evaluation, and improvement plan and implementation. We include four tools developed specifically for applying EMM in organizations: evaluation matrix, weighting questionnaire, quick questionnaire, and prioritization matrix. Also, we present a Colombian floriculture company's case study to exemplify the use of the EMM. The EMM provides a framework for integrating E/HF into organizations from the macroergonomics approach. E/HF practitioners can find in the EMM a tool to help them channel the actions taken by the different organizational actors to improve the safety, health, well-being, and performance of work systems. Finally, it should be noted that further studies on the reliability and validity of the EMM are needed, which would contribute to demonstrating that the EMM can effectively and successfully guide change in E/HF maturity levels in organizations.

Diagnostic assessment of novice EFL learners’ discourse competence in academic writing: a case study

Discourse competence is an essential component of communicative competence and central to the mastery of academic writing. This article reports a three-tiered diagnostic assessment of two English as a foreign language (EFL) student writers’ discourse competence in terms of textual features, composing strategies, and knowledge about academic writing. Drawing on extensive analyses of their writing samples, writer logs, and semi-structured interviews, we identified their discourse-level weaknesses and examined their writing strategies and academic writing knowledge status to ascertain their relationships with the observed weaknesses. Global coherence, which conveys the macros-level structure of the whole discourse, was found to be a shared problem of the two students. An investigation into their writing processes found that both students were deadline fighters whose poor time management seemed to account for the problems in their texts. Both spent too much time researching content knowledge but did not reserve sufficient time for writing and revision. Having limited knowledge of the disciplinary content and the required genre type and lacking adequate writing strategies were three salient blocks that impeded their composition of disciplinary essays. Based on the above, we propose a three-stage instructional procedure to facilitate novice EFL learners’ development of discourse competence in English academic writing.

Evaluation of a modernization project of the main condensate scheme at CHP-10 power unit No. 5 using its customized simulation model

We investigate the effect of modernizing the main condensate scheme applied at the power unit No.5, CHP-10 of Baikal Energy Company LLC, on its energy and economic efficiency using a customized simulation model. Simulation modelling was carried out in the Machine Program Building System software environment. The constructed model was verified using the results of measuring control parameters in several operating modes according to a three-stage procedure of verifying the mathematical models of complex thermal power units. We propose an original approach to modernizing the main condensate thermal scheme at the power unit under study in order to reduce the specific fuel consumption for balance-of-plant needs. The idea was to expand the main condensate scheme by including an additional sealing pump to the feedwater electric pumps of the 1Кs-20-110 unit in order to avoid the incorrect selection of condensate pumps. The study showed that the redistribution of the main condensate flow between the existing condensate pumps and the proposed 1Ks-20-110 sealing pump leads to a reduction in the specific fuel consumption for the electric energy generation to 0.32 g of fuel per kWh across the range of electrical loads from 137 to 150 mW. As a result, the net efficiency of the power unit can be raised by 0.03%. It should be noted that the proposed modernization project may reduce the consumption of electricity for balance-of-plant needs when the feedwater electric pump is switched to the standby mode during an emergency shutdown of the power unit. Based on the performed energy and economic calculations, energy savings for the period of 2019 comprise 82,653 kWh, while the total annual savings are estimated at 78,030 rubles. Thus, the conducted research demonstrates the high efficiency of applying simulation modelling in the study and optimization of existing thermal power plants.

The relationship between secondary traumatic stress and burnout in critical care nurses: The mediating effect of resilience

PurposeTo examine the mediating factor on the association of secondary traumatic stress and burnout among critical care nurses. DesignA correlational study. MethodsData were collected from a convenience sampling of 147 nurses from two general hospitals who had six or more months of experience working in an intensive care unit. The collected data were analyzed through t-test, ANOVA, Scheffé test, Mann-Whitney test, Kruskal-Wallis test, Bonferroni correction, and Pearson’s correlation coefficient using SPSS 25.0. The mediating effect of resilience was analyzed through the three-stage mediation effect test procedure using hierarchical regression analysis and the Sobel test. ResultsSecondary traumatic stress had a statistically significant positive correlation with burnout (r = 0.45, p <.001), and a statistically significant negative correlation between burnout and resilience (r = −0.54, p <.001) was observed. Secondary traumatic stress was found to have a statistically significant effect on resilience, which was the mediating variable (β = −0.17, p =.042). Additionally, secondary traumatic stress had a statistically significant effect on burnout (β = 0.45, p <.001). The significance of the mediating effect of resilience on the relationship between secondary traumatic stress and burnout was investigated using the Sobel test, and the mediating effect of resilience was found to be statistically significant (Z = 1.98, p =.048). ConclusionResilience was found to have a partial mediating effect in the relationship between critical care nurses’ secondary traumatic stress and burnout. The study thus provides basic data on the importance of resilience in preventing burnout from secondary traumatic stress.