With an increase of suction efficiency of fresh concrete pumping in confined spaces, the laminar flow state will be damaged by the return flow caused by distribution value direction changes and concrete gravity. This is a fact, but one which is rarely studied. In this work, the flow state, flow velocity, and suction efficiency of fresh concrete pumping are simulated using the coupled smooth particle hydrodynamics and Discrete Elements Method (SPH-DEM). The rheological parameters and Herschel-Bulkley-Papanastasiou (HBP) rheological model are adopted to simulate fresh concrete in the numerical simulation model. The study reveals that the error between the slump experimental result and that obtained by the HBP model is negligible. A model is therefore established for numerical simulations of the suction efficiency of fresh concrete pumping. An experimental concrete pumping platform is built, and the pressure and efficiency data during pumping are collected. A comparison of the numerical simulation with experimental results shows that the error is less than 10%. Despite advances in computer technology and numerical simulations, several problems regarding the pumping and delivery of fresh concrete have not been solved, such as its rheological behavior, precipitation, and water secretion. Knowing the rheological behavior of concrete during pumping and delivery may help to improve performance ,2,3. HowCurrently, there are many studies on the components of concrete and the application of various additives to improve its quality. Roussel  categoriThe conventional CFD method treats concrete as a single fluid phase, ignoring many solid aggregates, steel fibers, and other components. The Eulerian method is applied to calculate concrete grid fluxes to obtain the velocity variation of the flow process and its shear deformation region ,8,9. SomThe DEM method discretizes concrete into particles such as aggregates, and slurry, and performs simulations using the friction coefficient and collision restitution coefficient among different materials. For example, Krenzer et al.  mixed drThe multi-phase fluid-solid coupling method is usually used to study the flow of concrete in a static pipe or an L-box without an external load. Gram A  utilizedThe smooth particle hydrodynamics (SPH) method, in which the continuous fluid phase medium is discretized into individual particle locations, can create a realistic three-dimensional simulation. Many software packages for the SPH method are available for public use, such as the open-source Dualsphysics . The SPHThe flow of fresh concrete in pipes has received the attention of many scholars, while concrete pumping has not. Most recent studies have focused on the effects of material additions on concrete properties, while the suction efficiency and concrete flow in the pumping cylinder and pipe have attracted very little attention.In summary, previous studies on fresh concrete using DEM have paid little attention to the laminar flow state during pumping. Conventional CFD methods generally do not correspond to actual concrete composition ratios. On the other hand, most studies related to the CFD-DEM double-way coupling have focused on discontinuing the static pipes only. Therefore, the need for new research approaches to describe the continuous pumping and components of fresh concrete has been recognized.The suction efficiency of concrete pumping is numerically simulated in this work using coupled SPH-DEM  open-source software coupled with the Project Chrono open-source software). Firstly, SPH-DEM is utilized to create a fresh concrete simulation and analysis model. Secondly, the practicality of the SPH-DEM to produce new concrete is proved by experimentally evaluating the numerical simulation features of the concrete using concrete aggregate grading and slump flow tests, as well as a rheometer. Then, experiments are performed using the verified completed concrete and numerical models of the pumping process. Finally, the theoretical velocity of concrete movement in the cylinder is compared to that of the numerical simulation.SPH  is one oty. Ye T  determinFor slightly compressible fluids , the SPH is usually approximated by replacing it with an artificially incompressible fluid, which is the basis of most finite difference algorithms. Another approach to SPH calculations is to approximate a weakly compressible fluid, which requires that the speed of sound is large enough for density fluctuations to be negligible. When the air pressure is negligible, the form can be described by Equation (4), according to Morrison :(4)P=c2ρlagrossi , β = 100 in Wang .SPH adopts the smooth kernel function for calculations. If the particle boundary is within the particle computational domain of the SPH smooth kernel function, the second-order accuracy of the calculation and analysis can be guaranteed. However, when intersecting with the boundary, the smooth kernel function is truncated by the boundary, and its integral value is no longer 1. The computational error will cause a loss of the second-order accuracy of the SPH smooth kernel function . To solvInelastic fluid behavior is common in several non-Newtonian applications. Springless fluid behavior is expressed as the shear rate in follow equation:In rheology, the standard Bingham model  is usualIn Equation (7), if  results . TherefoIn Equation (8), if There are two unique coefficients, As indicated in The particle force is divided into normal and the tangential forces. Both are made up of the material’s completely elastic collision force and damping dissipation force. The normal force can be calculated using Coulomb’s law of friction, as in Equations (10) and (11).Experiments on concrete-related ratios and the slump-related gradation related to slump are required to determine the judgement criteria of the pumping procedure. The concrete is proportioned and matched in accordance with the characteristics listed in The aggregate is sieved for size and density, and graded in order to refine the concrete for the pumping. The results are displayed in The aggregate in After being certified, the aggregates are mixed into the concrete. Then the mixed material described in Slump tests were carried out for both proportions of the concrete described in After that, the rheological properties of fresh concrete and the related rheological coefficient are measured, as shown in The focus of this work is the response of the concrete suction process relative to an actual physical model during concrete pumping; hence, the pumping mechanism is shown in As concrete is not transparent, it is difficult to observe the changes of internal shape during delivery. Improving the concrete pump inhalation efficiency means observing and studying the experimental process by using a concrete pump which is constantly inhaling and pushing out concrete. As a result, the performance of the total quantity of concrete inhaled by the pump can be characterized by using the weight of the concrete pump output. This yields large amounts of data and records the mass during the delivery. Before pumping, the concrete density is determined, and the concrete output squared is calculated using the concrete weight.The hydraulic pump output flow rate can be determined, and the average efficiency in many pumping trials can be calculated using the ratio of the two flow rates. The experimental process should be performed ten times, with each group employing concrete pumps. The findings on efficiency and mass are displayed in According to the experimental results, the mass of every ten pumping instances was 1890–2380 kg. The average weight of each pumping in the 12 groups was 2156 kg. The pumping efficiency was 82.1–92.61% using the hydraulic pump output flow rate as determined from the hydraulic system. The pumping efficiency for the 12 groups was 86.9%, on average.In this work, the HBP model was adopted to investigate the rheological behavior, and the DEM method was employed to solve the forces between the fluid and the solid. The HBP model is an excellent non-Newtonian fluid model for simulating fresh concrete, and it can accurately simulate the Bingham or Power-law models used to describe slurry flow.To offer a thorough depiction of the pumping process, the concrete simulation analysis model, which is a comparison of the experimental data, first had to be calibrated. The parameters of the simulation model were defined based on the experimental results listed in The simulation of the Group 1 slumps is shown in In The simulation results of Group 2 are shown in The simulation analysis results of Group 2 were compared with the experimental data, as shown in The flow during concrete pumping is difficult to observe and represent, since it is in a restricted environment. Furthermore, there is no clear theory for how aggregate and slurry are separated in concrete, and this can only be determined by waiting for the former to accumulate, resulting in pipe obstruction. To describe the pumping process completely using the current computer technology, it is necessary to compare the pumping efficiency of a simulation analysis with the actual efficiency to determine whether they are compatible.Therefore, the mass of concrete pushed via the pumping cylinder is approximated by that sucked by the pumping cylinder, i.e., the conservation of mass. It is critical to investigate the efficiency and mass sucked by the pumping cylinder. The experimental process is complex. As such, simulation analyses were used to find a way to optimize the experimental prototype, which can be understood as approximating and matching the changing trend of the simulation analysis system and the actual experimental model. The actual experiment model contains too much information in the edges and corners, increasing the difficulty for the simulation analysis model to focus on real issues. Therefore, the edges and corners must be simplified. The redundant hole features in the pumping structure model shown in The Y–Y section is shown in The distribution valve is in the left position of the cylinder when the pumping model is at 0 s; after a reversal at 0.2 s, it moves to the right position. In accordance with the experimental procedure, the stirrer was operating at 20 rpm. Pumping in the experimental process was repeated 20 times per minute. The matching pumping speed was approximately 1 m/s, and the simulation analysis speed was assumed to be 1 m/s. The pumping cylinder of the simulation analysis model was 1.4 m long. When the suction finished after 1.4 s, the simulation analysis showed that the suction full tube position was 1.2 m, which corresponded to a single inhalation of 85.714%. The suction efficiency of the physical experiment was calculated to be 86.9%, as shown in The Bingham fluid in the pipe with the resolved motion velocity gives the flow velocity of concrete in the pipe via Equation (15):r/R, the parameters of the moving process were introduced into the preceding equation. The velocity of the concrete radial motion in the pipe is shown, and the two analyses are compared in To obtain the theoretical velocity in the respective region of The theoretical motion velocity of Bingham fluid in the pipe was well fitted to that in the numerical simulation.This work aimed to develop a new method to determine fresh concrete behavior during pumping.The results showed that the SPH-DEM method could be utilized to simulate fresh concrete through slump tests. The rheological parameters of fresh concrete were identified by a rheometer. The slump test error between simulation and experiment results was compared and shown to be less than 10%. Therefore, the SPH-DEM numerical simulation could potentially be used to react a real physical model.A numerical simulation model of the pumping process was established to analyze the effects of variations in the plastic viscosity of fresh concrete on the suction efficiency. In addition, the suction efficiency was studied experimentally. The numerical simulation results were compared with the experimental results, and the average error of suction efficiency was less than 5%.The gradient variation of the pressure loss along the pipe (Dp/L) was calculated and the theoretical flow rate of concrete in the pipe was analyzed. Compared with the numerical simulation, the theoretical velocity analysis showed that the results from the SPH-DEM numerical model approached those of the theoretical analysis. The issue of the pipe blocking mechanism is an intriguing one which should be further explored in future research.


Megaprojects and specifically ‘green’ construction of residential megaprojects can contain significant risks of failure. To design proper risk mitigation strategies, after identifying key risk factors, the next step is to conduct assessments that would facilitate the process of risk element prioritization. Risk assessment comprises the establishment of factor interrelation and discerning the indicators of importance. This research proposes a novel version of an integrated prioritization method and analyzes twelve all-inclusive key supply chain oriented risk factors identified in a previous study. Through a comprehensive literature review three criteria, impact, probability, and manageability are selected. Also, a fourth criterion namely influence rate is included in the model, based on the driving powers that can also be derived from the Interpretive Structural Modeling’s (ISM) assessment. Fundamentally, the calculations hinge on the Analytic Network Process (ANP) method which provides an assessment of the alternatives’ weights based on pairwise comparisons concerning the criteria specified. To enhance the accuracy of the perceptive judgments of the expert panelists, a bell-shaped fuzzy function is used to convert the verbal statements to crisp values. In addition, Row Sensitivity Analysis is administered to check the stability of the results and provide predictive scenarios. To validate the model, a case study, located in Iran, was conducted, where an expert panel consisting of four individuals made the pair-wise comparisons through an ANP questionnaire. Results indicate priority and sensitivity of the alternatives concerning criteria, for the case under study. The green construction industry aims to minimize resource depletion and emission of any kind of pollution, controlling energy consumption through environmentally friendly practices  and Multi Attribute Decision Making (MADM) methods have been used in the realm of operations research, engineering, and management science  is included to render scenarios interpreting the importance of the alternatives and criteria, and the effects of the criteria on the prominence of the alternatives.The main contributions of the current research are our proposing and demonstrating a novel integrated Fuzzy-ANP-ISM method to prioritize supply chain oriented key risk factors, and applying it (for the first time to our knowledge) in a real setting of green construction of residential megaprojects. This required formulation of specific parameters for this setting. Another new contribution is the inclusion of an infrequently used supply chain risk property, namely manageability, other than the severity of impact and the probability of occurrence. And finally, utilization of a new fuzzy environment for the Fuzzy-ANP body of knowledge, especially for that the scope of the questionnaire remains intact, through the fuzzy-fi-cation.The following are the highlights of the remaining sections. Section While the prime goal of supply chain management is to provide fluent functionality of processes to satisfy customers’ demands , can be detected. A third feature, namely manageability, can be inferred, as a risk component related to controllability and resilience. Manageability measures the degree to which disruptions and or interruptions are controllable due to prevention or reactive mitigation. The last feature used in the current study, namely influence rate, leans on the term causal pathway. Influence rate is defined to compare the degree of influence each risk factor can inflict on other triggering events. No investigation has previously been conducted on the subject of prioritization of the supply chain oriented risk factors in the green construction of residential megaprojects, and a robust prioritization method would greatly contribute to the subject matter’s body of knowledge. Table This section introduces the methodological development of the integrated problem-solving method utilized in the current research. The basic principles of each method, necessary for understanding the data analysis, are explained and a step-by-step procedure is determined  ≤ 0.1 Saaty . C.I., cRelative importance weights of the initial super-matrix, namely local priorities, can be calculated using different optimization methods such as the eigenvalue method, the least squares, the logarithmic least squares, or the weighted least squares , represents MF, the letter d is the factor that controls the width of the curve, the letter x represents the horizontal axis and the letter c is the center of the corresponding bell graph. Using the one expert’s direct intuitionistic judgment method  method the accumulated resulting fuzzy number is defuzzified to a crisp number. The discrete form of the SG method follows the equation below.A(x), represents MF; the symbol xi is any point on the horizontal axis. It is worth recalling that in the ANP questionnaire i = 1, 2, 3, …, 9. The resulting fuzzy numbers equivalent to each verbal statement are calculated using the software MATLAB and are shown in Table The letter a, represents a specified distance of the center of gravity from the vertical axis; the symbol entclass1pt{minimaThe sample example below illuminates the calculation required to convert experts’ linguistic responses into a crisp number. To bring light on the subject matter, consider in a given expert panel consisting of four individuals, the responses were ‘moderately more important than Second’; ‘strongly more important than’; ‘very strongly more important than’; ‘extremely more important’. The corresponding fuzzy sets would be as shown in Table To produce an average out of the fuzzy sets resulting, the average of the values allotted to each step should be calculated. The resulting would be a fuzzy number, as shown in Table The calculations should proceed with multiplying each step’s value by its step number. The resulting would be a weighted fuzzy number, as shown in Table Finally, dividing the summation of the values of the weighted fuzzy number by the summation of the average fuzzy number, the ultimate crisp value allocated to a specific pairwise comparison results. In this particular case, the resulting crisp value would be: 7.22 ÷ 1.23 = 5.87.To explain the need for sensitivity analysis when prioritizing risk factors, one might consider two schools of risk, risk as a subjective perception and risk as an objective construct with each requiring different risk management and mitigation strategies Zhang . For insRow sensitivity analysis (RSA) developed by Adams  is a calISM introduced by Warfield  is an inEffective supply chain risk assessment strategies, in general, comprise two parts  which is ranked the fifth most important key risk factor, with the importance weight of 0.6. However, these findings are also congruent with previous studies conducted in developing countries, in the realm of green building risks. In this regard, key risks identified in green building projects in china include quality and technical oriented risks such as failure in achieving the green building quality standard, health in built environment, and user behavior  but also the action and control factors (manageability and influence), including as to how risk factors are inter-reactive. This new approach gives professional managers a fully sound basis for prioritizing their interests and finite resources in risk management.The main purpose of this study was to conduct an integrated decision-making method to prioritize risk factors. In light of the importance of green residential megaprojects, its supply chain oriented risk factors were examined where twelve all-inclusive items were investigated through the ANP questionnaire. To bring more precision to the uncertain concept of risk management and judgmental decision making, the current paper proposed a novel and safe integration of ISM and Fuzzy logic to the ANP method. Furthermore, the row sensitivity analysis examined possible scenarios of the rank change in alternatives concerning change in the importance of the criteria. Some various conditions were examined and the most important alternatives and the stability of the results were discussed. The results indicate the instrumentality of the integrated methodology proposed. And although the resulting priorities are pertinent to the specified case under study, the practicality of the investigation in other cases is also supported, by providing the required material to reproduce the data analysis.Further examinations may consider examining the positive dependence and negative dependence of the risk factors on each other (Sarker et al. This investigation has some limitations, for example, judgmental decision-making relies on the precision and the degree of expertise the expert panel has acquired. The ability to process the data is also necessary, as is the availability of panel experts. Also, the large number of pair-wise comparisons makes the questionnaire tedious for the expert panelists.


Many concrete structures, such as bridges and wind turbine towers, fail mostly due to the fatigue rapture and bending, where the cracks are initiated and propagate under cyclic loading. Modeling the fracture process zone (FPZ) is essential to understanding the cracking behavior of heterogeneous, quasi-brittle materials such as concrete under monotonic and cyclic actions. The paper aims to present a numerical modeling approach for simulating crack growth using a scaled boundary finite element model (SBFEM). The cohesive traction law is explored to model the stress field under monotonic and cyclic loading conditions. In doing so, a new constitutive law is applied within the cohesive response. The cyclic damage accumulation during loading and unloading is formulated within the thermodynamic framework of the constitutive concrete model. We consider two common problems of three-point bending of a single-edge-notched concrete beam subjected to different loading conditions to validate the developed method. The simulation results show good agreement with experimental test measurements from the literature. The presented analysis can provide a further understanding of crack growth and damage accumulation within the cohesive response, and the SBFEM makes it possible to identify the fracture behavior of cyclic crack propagation in concrete members. Concrete structural elements very often fail due to fatigue fractures, in which repeated loading can lead to the growth of existing cracks ,2,3,4. TThe advanced studies on cyclic crack propagation are mostly empirical, wherein large number of data samples from experiments are used for fitting the relationship. The most commonly used approach to predict fatigue life and crack growth rate is the well-known Paris law ,6. This t cracks ,8. NeverSeveral modeling approaches for crack propagation under cyclic and fatigue loading are well documented in the literature ,10. The The second type of crack simulation model is the phase field model (PFM). The concept of the PFM approach is to regularize free energy of degradation, which effectively reduces material fracture resistance under fatigue loading . It was Additionally, discrete lattice models have many features of the discrete element method (DEM) to simulate the heterogeneous microstructure and crack propagation . The forMany models in the literature ,29,30,31The scaled boundary finite element method (SBFEM) is a very attractive approach to modeling crack nucleation and propagation under general loading conditions ,35,36,37In the present paper, we further extend the SBFEM for modeling cyclic-damage-induced cracks’ behavior within the SBFEM framework. The model considers the cumulative crack opening/sliding measure to dominate the damage mechanism at the subcritical loading levels. Similar approaches have been proposed in  for the The paper is organized as follows. The theoretical formulation of the cohesive crack model inside SBFEM is represented in D is the constitutive matrix ξ2{u( matrix [[E0]ξ2{u(equation  as(6)ξ[An eigenvalue decomposition of [Z] follows : (10)[Z]Equation  yields: The equivalent nodal forces on the boundary and the stiffness matrix of the domain are formulated, respectively, asK and load vector P.At the boundaries, the nodal displacements Meanwhile, substituting Equation  into EquHence, the stress field is formulated byThe fracture process zone in a quasi-brittle material can transfer the cohesive forces between the crack faces. This is attributed to the interlocking of the aggregate, in addition to the surface friction. The cohesive traction representing the crack faces is applied as side-face forces. The equilibrium condition (Equation ) in a poIn this work, the cohesive force on the crack faces duced by .The mesh generation of the domain in The crack cell is divided into two SBFEM cells to discretize the crack faces and to insert the interface elements into the SBFEM system. The local coordinates The shadow domain is generated as shown in The SBFEM is directly coupled with zero-thickness, four node-interface elements along the crack path d which aAlong the crack paths, the fracture process zone is characterized using softening laws of the thermodynamics; see The concept of the cohesive cyclic crack model, as depicted in d. In the local coordinate system, the stiffness matrix reads: k is the stiffness of the softening laws, A is the crack surface area, In the fracture process zone, cohesive tractions n matrix . The sti), as in .Linearly varying or constant distributed loads are approaches to representing a force over a particular distance. According to , when thSubstitution of Equation  into EquRearranging will give the nodal displacements for the side-face load mode M raised to the power of function In order to express the cohesive tractions as a power of function, the normal traction distribution j = 1, M) are used to generate M number of equations asL. The coefficients The tractions at the crack tip, the Gaussian points, and the crack mouth The nodal side-face load vector becomesThe displacement solution is thus expressed by two components: the modes of normal displacement due to external loading and the modes of side-face displacement due to cohesive tractions asOn the subdomain boundary, the nodal displacement Equation , and theThe nodal displacements Subsequently, Equation  is read The stress field can be calculated similarly to Equation  as34){{(34){σ(ξM) of displacement nodes and the same of stress modes are added to the displacement field and stress field, respectively.Comparing Equation  and EquaThe direction of crack propagation is then determined based on . In ordeThe SBFEM has the advantage of accurately representing the crack zone’s stress field without needing a more discretized mesh ,50. Thisr and r and lated byr=ξL(θ)wKIKII=limFrom Equation , when ξ→Equation  yields. A yield function similar to plasticity theory, which defines the boundary between elastic and inelastic domains, is introduced into the effective stress space as follows.S is the damage strength parameter, and c and r are exponential rate parameters. The evolution equations can be obtained by differentiating quation  under opening and shear displacement is presented in this section.c was used to control the dropped-down part of the crack opening c and r were applied for tuning the accumulation of the damage due to cyclic loading. The damage strength parameter S, however, could control the brittleness in the response. The model parameters for a common combination of concrete matrix C30/37 were identified using the parametric study reported in [K, S, r, and c were identified using a black line for the monotonic response and a blue line for the monotonic response.The described parameters of monotonic and cyclic response material behavior are plotted in orted in . The setThe cyclic loading curves of the crack opening versus cyclic loading can be compared with the corresponding curves obtained numerically for monotonic loading. The described model was implemented using zero-thickness interface elements inside the SBFEM framework in Equation ). For thThree-point bending (TPB) tests were studied to validate the numerical method in this study. The contributions of both traction modes, ormed by  have shoormed by , which iF. The TPB supported beam was tested symmetrically by displacement-controlled loading at the top edge. The typical two different loading scenarios are shown in Experimentally, the crack opening displacements and the mid span deflection of the tested beam were recorded, along with the applied force The softening curve parameters to model the fracture process zone are presented, and a range of values were applied based on the parametric study in The tracked points for the notched pattern and the initial mesh were defined as shown in The crack propagation due to increasing load with initial k region c. For the way in  under moe way in ,52: (50)Furthermore, in our analysis we explore the main dissipative mechanisms. For this purpose, the TPB beams were subjected to a few loading cycles with an incremental increase in the CMOD values. The obtained cyclic responses for both small and large beams are plotted in This is explained by knowing that the developed crack showed a rough surface that is not fully closed during the unloading of the specimen. This was confirmed for the cyclic behavior in the simulation of SBFEM and experiment tests. Additionally, the stiffness degradation and the growth of unclosed crack openings were characterized for both sizes.Plots of Since the goal of the present study was to apply the constitutive law with a cumulative damage feature within SBFEM, we considered only mode-I cyclic crack propagation in our analysis. Further studies with applications to mixed modes loading are planned for future publications, where more advanced constitutive cohesive zone models could be used, e.g., ,56.Cracks in concrete can occur when the tensile stresses imposed by actions exceed the tensile strength of the material. Furthermore, the cracks can also be initiated under repeated loads with stress levels below the tensile strength. In this work, the cyclic cohesive crack procedure-based SBFEM was implemented to study the crack propagation in concrete. The proposed model showed the ability to simulate the monotonic and cyclic behavior of a cohesive crack interface element, e.g., a concrete interface. It provided a realistic prediction of cyclic damage behavior for up to several load cycles. The output for the numerical simulation of monotonic loading analysis showed full agreement with experimental data from the literature. The results differed 5% for the maximum peak force. Regarding the nominal strength, the ratio of the numerical results to the experimental data under monotonic loading varied between 1.01 and 1.04 for small beams. The ratio was 0.98–1.02 for large beams.Additionally, the proposed procedure has been proved to be an efficient tool for estimating the damage level. The level of damage accumulation S. The simulations executed to study the effect of the loading sequence offered successful results and demonstrated the effect of damage accumulation for realistic predictions for concrete structures.The predicted load–CMOD responses in the validation examples were within the range measured in the cyclic and monotonic loading experiments. Testing results demonstrated that the most important factors for the overall simulation were the thermodynamic hardening modulus


Catheter ablation of ventricular tachycardia has demonstrated its important role in the treatment of ventricular tachycardia in patients with structural cardiomyopathy. Conventional mapping techniques used to define the critical isthmus, such as activation mapping and entrainment, are limited by the non-inducibility of the clinical tachycardia or its poor hemodynamic tolerance. To overcome these limitations, a voltage mapping strategy based on bipolar electrograms peak to peak analysis was developed, but a low specificity (30%) for VT isthmus has been described with this approach. Functional mapping strategy relies on the analysis of the characteristics of the electrograms but also their propagation patterns and their response to extra-stimulus or alternative pacing wavefronts to define the targets for ablation. With this review, we aim to summarize the different functional mapping strategies described to date to identify ventricular arrhythmic substrate in patients with structural heart disease. Patients with structural heart disease that experience ventricular tachycardia (VT) have poorer outcomes compared to those who do not have VT ,2. AiminThe objective of this review is to analyze the different strategies to identify and unmask the arrhythmogenic substrate apart from the findings of peak-to-peak voltage mapping, in order to improve VT ablation outcomes.We propose the definition of VT functional substrate mapping as a grouping term that uses not only the peak-to-peak voltage of the EGMs to analyze them but also their propagation patterns within the low-voltage areas and its response to either varying wavefronts of the activation or varying cycle lengths of pacing or extra-stimulation. Voltage channels can be easily identified in patients with VT through voltage maps; adjusting the thresholds but a low specificity (30%) for VT isthmus has been described with this approach. The presence of LPs inside the CCs increases the specificity for identifying critical VT termination sites (85%) . DespiteLooking in depth into the mechanism of re-entry, which is the main mechanism of VT in patients with heart disease, conduction delay preceding unidirectional block has been demonstrated as essential for its initiation and maintenance ,24 Figu.In their seminal paper, Jackson et al.  hypothesp < 0.001), but areas with DEEPs performed better than LPs at colocalizing within VT isthmus (ROC area under the curve of 0.86 vs. 0.79 with LPs). The ablation strategy consisted in ablation only of the DEEP regions and only expanded the ablation if the patient was still inducible (20%). Recurrence rates after DEEP-guided ablation were similar to what has been described in the literature (75% VT freedom at 6 months).These results were confirmed in the clinical setting by Porta-Sanchez et al.  with 20 Acosta et al.  describeDe Riva et al.  performeIn both Acosta’s and De Riva’s studies, the distribution of hidden substrate was analyzed and, when possible, compared not only with voltage maps but also cardiac magnetic resonance (CMR). Nearly 20–35% of these EGMs were located in healthy tissue (>1.5 mV bipolar peak to peak) as measured by mapping. This number clearly decreased when the analysis was made by CMR (8–9%), which emphasizes the possibility of a better definition of the VT substrate by CMR and functional substrate mapping as compared to the conventional voltage map. This is consistent with the study by Oduneye , in whicA better characterization of the EGM response after a close-coupled extra-stimuli was studied by Redfearn et al.  both in The PEFA strategy was tested with 10 ischemic patients, targeting type I and II EGMs for radiofrequency, obtaining longer procedures but a lower VT inducibility rate at the end of the procedure in the interventional group as compared to the derivation cohort.In an elegant study, focusing on a mechanistic and physiopathologically sound hypothesis, Srinivasan et al. designed an innovative strategy. It is based on the findings by Roelke et al.  that fouWith the idea of closely reproducing this mechanism, the Barts Sense Protocol was designed . A cohorConducting channels responsible for VT circuits are based mainly on anatomical features consisting of replacement of cardiomyocytes with fibrosis and persistence of viable cells inside the scar capable of slow conduction. However, the sole presence of scar is insufficient to produce the electroanatomical setting for re-entry. Several other factors, such as cellular coupling, gap junction distribution and function and fiber disarray, can lead to a nonuniform anisotropic conduction ,37; whetIn 2015, a new substrate-based ablation strategy called ILAM  was developed by Irie et al. . These lSubsequently, in 2019, Aziz et al.  presenteLate potentials showing decremental properties (DEEPs) seem to be more likely associated with VT isthmuses.A pace protocol based in ventricular extra-stimulus has demonstrated to be able to change the shape and duration of selected EGMs, especially in patients with small scars. Targeting those electrograms that delay from the far field signal could lead to less VT recurrence in the follow up.The direction of the wavefront also has an important impact in the arrhythmic substrate characterization and needs careful evaluation in some patients.The arrhythmic substrate is dynamic: its electric properties can change with different pacing settings and that help unmask regions that are critical for re-entry.The analysis of the timing of the electrograms, not absolute and individually, but relative to the duration of all the ventricular electrograms and their pattern of propagation, has led to the development of a method for the identification of deceleration zones. These DZs have shown a good correlation with VT isthmus.VT ablation remains a challenging procedure due to the high recurrence rate and the complex subset of patients experiencing such a life-threatening condition. Voltage maps have initially constituted an alternative to the difficulty of mapping VT due to hemodynamic instability allowing, with the classic thresholds of 0.5–1.5 mV, to characterize the scar and “visualize” the surviving myocardium without the need to induce VT. The low specificity of these voltage channels to accurately identify the VT isthmuses  has led VT functional substrate mapping strategies have let us increase the knowledge about the arrhythmic substrate, which in itself represents an important advance. Understanding the arrhythmic substrate as something not static but functional has been shown to be important to improve ablation results. Among the most outstanding findings, using different paced protocols and extra-stimulation, is the definition of new electrograms called DEEPs. These DEEPs have showed to have a greater specificity for identifying VT isthmus compared with conventional non-decremental LPs. The basis for pursuing those potentials with decremental conduction lies in how the ventricular tachycardias in scar-related patients are initiated ,24. MultSimilarly, the main mechanism responsible for generating this decremental conduction and inducing VT is the extrastimuli ,34, so pWith regards to the direction of LV activation, several studies agreed on the greater accuracy to identify LP and LAVAs with an RV and/or LV pacing protocol compared with sinus rhythm. More specifically, it seems that the maximal activation slowing is achieved pacing close to the site where the wavefront first interacts with the infarcted area .In this sense, one of the main messages behind functional VT mapping strategies is that by varying the speed and origin of the stimulation, we change the properties and characteristics of the substrate. Therefore, if we exclusively perform an electroanatomic map in sinus rhythm, without using extra-stimuli, we will have to assume a partial and not complete information about the substrate. A second important message comes from the perspective of understanding the behavior of electrograms not only by themselves but relating them to neighboring electrograms. DZs are defined as areas not only with delay  but deceleration. The ILAM has emerged as a widespread method due to automatic annotation, visual representation of areas of interest and, of course, the higher correlation between DZs and VT isthmus , allowinDespite the important advances shown with functional VT substrate mapping, some limitations must be addressed. First, none of the previous studies focused specifically on the behavior of intramural substrates during functional mapping strategies. This could also be due to the lack of pre-procedural CMR to define the intramural substrate. Undoubtedly, identifying the septal arrhythmic substrate during mapping from both RV and LV endocardium is of importance, and functional mapping of the area and its comparison with a stable rhythm can help define targets for RF . The rolThe substrate approach strategy is based on the correct identification of the arrhythmic substrate. The bipolar signal depends on the electrode size, interelectrode spacing, and angle of the incoming wavefront to the mapping catheter, so areas of low-amplitude EGMs as LPs or LAVAs cannot be detected with classical bipolar catheters. High-density catheters have been shown to facilitate the discrimination of LAVAs/LPs, providing a more detailed characterization of the arrhythmic substrate, which is even more important in low-voltage areas ,44. Interestingly, less VT recurrence has been reported using this type of catheter ,17, althLikewise, the functional substrate mapping can help us to unmask the hidden substrate both with extra-stimulus techniques and pacing from different locations, increasing the amount of potentially arrhythmic substrate. Furthermore, this strategy allows to better identify areas more specifically related with VT isthmus, such as DEEPs  or DZs . The fact that we can visualize a greater amount of arrhythmic substrate but that at the same time we have tools to better delimit which zones are associated with critical VT circuits has led to some controversy nowadays regarding the preferred ablation strategy.One possibility is based on performing limited ablation focused on identifying surrogates of the VT isthmus, either using activation mapping if possible, and/or targeting DZs or DEEPs . This could decrease the procedure and radiofrequency times at the expense of leaving an undetermined amount of arrhythmic substrate unablated, which could be responsible for events in the future. The other perspective relies on a larger ablation approach involving all of the arrhythmic substrate. Techniques such as scar homogenization based on the elimination of the entire substrate have demonstrated less VT inducibility at the end of the procedure and possibly a decrease in VT recurrence rate during follow up .Advancements in EAM systems and multielectrode catheters have allowed for a semi-automatization of the mapping process with different rhythms and thus have been instrumental in the description and analysis of such functional techniques. All of the most common mapping systems can be configured to allow for the creation in real time of several maps while the catheter is roving the chamber of interest or by replaying the movements and signals of the catheter afterwards and recreating a new map. Those features are present both in the CARTO v3 system (TM), Ensite X (TM) and Rhythmia HDX mapping systems (TM).A unified and standardized VT ablation strategy has not yet been defined with total reproducibility such as in other standard EP procedures. The lack of randomized studies, the low number of patients included in them, the evolution of the substrate, the difficulty in creating transmural lesions, and several other factors make it difficult to draw clear conclusions about the different mapping methods, so there currently exists a great variability between centers and operators who perform VT ablation procedures.A multicenter randomized study focused on performing the best possible analysis of the arrhythmic substrate  and then test a more limited or more extensive ablation strategy could lead to clarification of the best approach for VT ablation and eventually improve clinical outcomes.


Several cities around the world rely on urban rail transit systems composed of interconnected lines, serving massive numbers of passengers on a daily basis. Accessing the location of passengers is essential to ensure the efficient and safe operation and planning of these systems. However, passenger route choices between origin and destination pairs are variable, depending on the subjective perception of travel and waiting times, required transfers, convenience factors, and on-site vehicle arrivals. This work proposes a robust methodology to estimate passenger route choices based only on automated fare collection data, i.e. without privacy-invasive sensors and monitoring devices. Unlike previous approaches, our method does not require precise train timetable information or prior route choice models, and is robust to unforeseen operational events like malfunctions and delays. Train arrival times are inferred from passenger volume spikes at the exit gates, and the likelihood of eligible routes per passenger estimated based on the alignment between vehicle location and the passenger timings of entrance and exit. Applying this approach to automated fare collection data in Lisbon, we find that while in most cases passengers preferred the route with the least transfers, there were a significant number of cases where the shorter distance was preferred. Our findings are valuable for decision support among rail operators in various aspects such as passenger traffic bottleneck resolution, train allocation and scheduling, and placement of services. Public urban rail transit is a major mode of transportation in many cities around the world. The latest report by the International Association of Public Transport estimates that metro systems had a total global ridership of 53,768 million in 2017, with Asia-Pacific and Europe leading the numbers [Passenger route choices are not deterministic as they depend on the subjective perception of travel time, required transfers, convenience factors, and on-site train arrivals and waiting times, among others . This maIn this study, we model individual passenger routes and the overall passenger flow in a rail network based only on automated fare collection data containing passenger entrances and exits within the urban rail system. To accomplish this task, we present a computational approach that assesses the likelihood of each possible route choice by aligning card validation timestamps against real-time route scheduling. In the absence of vehicle geolocation data, the locations of the trains at different times can be estimated by analyzing passenger volume peaks at the exit station gates. We can then use this information together with an analysis of the trip durations to better infer the likelihood that a passenger took a specific route by analyzing the location and timings of his or her entry and exit from the urban rail system.In our approach, train arrival times are estimated by aligning passenger volume peaks at exit stations based on the theoretical velocity of the train along each line. Furthermore, our approach considers the variability of waiting times as a result of missing the next available train. It can be implemented without the use of complex and privacy-invasive sensors and monitoring devices and is adaptable to changes in the network not only because of unforeseen events like malfunctions and delays, but also changes in operational schedules and policies. This makes it robust to short-term changes in train dispatch times.In this paper, we apply the proposed approach on the automated fare collection dataset of the Lisbon Metro for the month of October 2019 and discuss the corresponding results. The paper is structured as follows. Section This section discusses relevant advances on the task of inferring passenger route choice behavior within urban rail systems and the position of our work among these contributions. Traditionally, passenger route preferences are obtained through surveys which are then modelled mathematically to provide a systematic view of the passenger flow in a network . In thisThe global rapid adoption of automated fare collection (AFC) systems triggered new opportunities. AFC data acquisition can address the key limitations of surveys, providing dynamic information on passenger behavior. Sun et al.  estimateNonetheless, some works have proposed approaches to infer passenger choices in the context of multiple-line rail systems. Kusakabe et al.  infers tWhile the above studies can consider multiple routes, they still present some limitations. First, they work under the assumption of well-defined train timetables as well as the punctuality of the trains. While in some major cities, such as Tokyo and Beijing, it is common to have precise train schedules that are followed on the dot, this is not always the case in many other cities , 4, 11. There are two studies that propose more complex models for the variability of waiting and transfer times. In the work of Sun and Xu , a generFinally, a few studies target the task of inferring passenger route choices with the help of mobile phone trajectories , 22. TheOur proposed method for inferring passenger route choices offers several advantages compared to previous approaches. First, it requires minimal information that is easily obtainable in most urban rail systems. Specifically, aside from the automated fare collection data, our approach does not require precise timetables that define arrival and departure times for each station. Furthermore, our approach also considers the variability of waiting times as a result of missing the next available train. The proposed approach can be implemented without the use of complex and privacy-invasive sensors and monitoring devices and is adaptable to changes in the network not only because of unforeseen events like malfunctions and delays, but also changes in operational schedules and policies. Table The objective of this work is to estimate the route choices of passengers in a mass transit system, in which the system is composed of a set of interconnected lines, with each line serviced periodically by vehicles passing through a series of stations. Passengers may enter and exit the system through any station and may take as vehicles as many times as they want while within the network. We define the route of a passenger as the path taken from the station of entry to the station of exit. We then formalize the task as follows: given the passengers’ time and location of entry and exit in the transit system, how can we predict the actual routes that were taken by each passenger?azul (blue), amarela (yellow), verde (green), and vermelha (red) with a total of 56 stations [In this work, we consider the Lisbon metropolitan system, also referred as Metro, as the guiding case study to assess passenger route choice estimators. The Metro is an urban rail rapid transit system in Lisbon, the capital city of Portugal. As of 2021, it consists of 4 lines: stations . As withAs the rapid transit system of a capital city, the Lisbon Metro serves a massive number of passengers. In 2019, the annual ridership of the Lisbon Metro reached 173 million people . SimilarIn this section, we present a two-step approach for estimating passenger route choices in urban rail transit systems. The approach is divided into two parts: (a) estimating the locations of the trains in the network, and (b) estimating the likelihood of each passenger’s route choice based on the train locations.The first step is to estimate the locations of each train in the network over time. To this end, peaks in the volume of passengers exiting the stations are identified based on automated fare collection data. For any given day, we can form a time series for each station by aggregating the number of exit records per station into 15 s intervals. We then perform a rolling average and rolling deviation on the time series to identify passenger exit peaks along a line to estimate the precise location of vehicles. We define a passenger volume spike as a peak in the time series that is at least one standard deviation higher than rolling mean. This scheme aims to ensure that only peaks deviating from typical behavior along a given period are considered and has previously been used similarly for robust peak detection in other studies , 6.Using the Lisbon Metro as an example, Fig. We then identify the travel time durations of each train through each line. This data can easily be obtained based on the urban rail system’s operational protocols or, in the absence of this data, could be estimated from averaging times of actual train operations. Given a line consisting of stations Using the Lisbon Metro’s green line as an example, Fig. t, the likelihood score S is the set of stations in the target time and closest function returns the time of the closest passenger volume peak (after shifting) that occurs after t, bounded by a maximum value of count function returns the total number of exits made within the range The next step is to align the passenger volume peak data for each station according to the projected passing of the train along the stations using the previously identified offsets. To do this, we perform a shift by subtracting the corresponding train arrival offset from each of the passenger volume peaks in each station. We then estimate the likelihood that a train started on the first station at a given time. To this end, we define a likelihood score based on the total distance from the closest passenger volume spikes. Given a starting time Linha Verde (green line) before and after shifting. Based on our assumption that the arrival of a train on a station implies a possible spike in passenger volume at the exit gates, we are able to draw a vertical line on the shifted plot and observe volume spikes close to that line. We can visually observe in the figure that this hypothesis holds true, particularly on the latter half of the line. This makes sense because people are more likely to get off at later stations according to the natural flow of the line direction. Figure t, showing the likelihood peaks at times where the passenger volume peaks are well-aligned, with the purple dots showing the peaks which represent the predicted times that the trains have started travelling from the first station in this direction.Illustrating, Fig. Now that the predicted starting times of the trains have been identified, actual train arrival times for each station can be easily inferred. To compute the train arrival times at a given station Before route choices are predicted, we first pair the entrance and exit records in the automated fare collection dataset. Given that each record contains the following information: (a) entrance or exit, (b) timestamp, (c) station, and (d) identifier, we can match each passenger’s entrance record with its corresponding exit record considering the card identifiers and trip precedencies. There may be some cases where an entrance or exit record is missing its corresponding pair in the dataset. These can occur due to operational anomalies . Understandably, route choice estimation for incomplete trips should be proceeded by well-established principles for boarding or alighting station inference . NeverthIn fact, after pairing the entrance and exit records in the Lisbon Metro, Fig. We define a route as a path that a passenger takes to get from an entry to an exit station. A route may contain one or more segments, which represent a single train ride on any given line. Given a passenger’s time and location of entry and a candidate route, the expected exit time of the passenger by following that route can be computed. To estimate the expected exit time along a route, travel can be simulated considering the train arrival times for the relevant stations.To accommodate for cases where a passenger misses the next available train , we introduce a parameter Given a set of estimated exit times In the Lisbon Metro dataset, consider for instance a passenger who entered through Alameda station at 12:59:15 and exited through Campo Grande station at 13:11:27. Two possible routes that this passenger could have taken are as follows: (a) green line from Alameda to Campo Grande and (b), red line from Alameda to Saldanha, followed by the yellow line from Saldanha to Campo Grande. As visualized in Fig. In Fig. To validate the approach, the introduced methodology was applied to the Lisbon Metro dataset. For simplicity, the reported results are conducted on a single randomly selected day for the purposes of this analysis: October 7, 2019, which contains 600,548 pairs of entrance-exit data. While the absence of ground-truth data on passenger preferences makes it infeasible to provide an absolute comparison, we make use of available knowledge to check the consistency of the results of the approach against background expectations.A key component of the proposed approach is the estimation of train dispatch times in the absence of precise timetables. However, in the case of Lisbon Metro, while precise timetables are not available, approximate waiting times for each of the four lines are made available to the public for different times of the day.It can be seen that estimated dispatch intervals mostly coincide with the theoretical intervals defined by the Lisbon Metro for each of the four lines. There are a few noticeable deviations towards the end of the day, which could be attributed to abnormal peak patterns due to sparse ridership. Nonetheless, the overall consistency of the estimated train dispatch intervals with the theoretical dispatch intervals shows the possibility of estimating train locations, without precise timetables, from passenger volume peaks.must have taken the undoubtedly shortest route. For these cases, we run the algorithm to validate whether the predicted exit times of the only available route are reasonably close to the actual exit times of the passengers. We used a To validate the prediction of passenger routes, we exploit the case where there is only one possible route from the entrance and exit station, and that route is without any transfers, i.e. station pairs on the same segment of the line without branching paths. In these cases, we assume that the passenger cafes, subway workers). Nonetheless, these cases are a minority and most passenger exit times are accurately predicted.Illustrating, Fig. Next, we look at cases where multiple route choices are involved. To do this, we first identify all pairs of stations within the rail network. For each pair In our analysis, we highlight two common criteria for passenger preference: (a) “least transfers” , and (b) “least stations” . There are a total of 49 stations across all lines in the metro, resulting in 2352 possible entrance-exit pairs. Out of these pairs, 636 are non-trivial entrance-exit pairs where the route with the least transfers is different from the route with the least stations.Among the 636 non-trivial station pairs, the preferred route is the one with least transfers in 562 (88.36%) of the pairs. On the other hand, the preferred route is the one with the least number of stations in 54 (8.49%) of the pairs. As for the remaining pairs, the preferred route was neither of the two. It is possible to visualize the preference of passengers for various pairs of stations.Figure mentclasspt{minimaFor the stations between the blue-green line, once again most passengers preferred routes with least transfers. However, a significant amount of passengers going to Anjos (AN), Intendente (IN), and Martim Moniz (MM) from the northern blue line stations tend to pick the route with the least stations. Interestingly, however, this was not case for the reverse direction, as also illustrated in Fig. Table Finally, examining the trivial pairs where the route with the least transfers is also the route with the least stations, that route is the preferred route choice in almost all cases as to be expected. However, there are cases where evidence suggests this is not the case. We present two cases of this in Fig. Overall, these results show that the proposed approach is able to make predictions of passenger route choices in urban rail transit systems that is consistent with background expectations, while at the same time revealing interesting phenomena on passenger behavior in certain instances.We highlight three main strengths of the proposed approach in comparison with other works on passenger route choice inference: (a) non-requirement of precise train timetables, (b) robustness to short-term changes, and (c) consideration of missed or skipped trains.First, the non-requirement of precise train timetables means that our approach can infer passenger route choices even without knowing the exact times the trains arrived at each station. This is important because not all urban rail systems around the world follow fixed schedules that are observed to the dot. In the context of our case study on the Lisbon’s metro, train schedules are not precise/fixed. Nonetheless, estimated waiting times between each train are defined for each line at different times of the day. Still, these intervals are only estimates and are generally not followed on the dot. One of the main contributions of our work is to infer the arrival times of trains in each station even in the absence of timetables, which is a required input in previous studies , 21, 23.To assess the importance of estimating train locations in the absence of precise timetables, we compared the proposed solution against one based on the theoretical waiting time intervals from the Lisbon metro website.t-test , satisfaction of safety norms especially in times of a pandemic, amenity and service placements, among others. The fine-grained location of passengers along a urban rail transit systems can also support vehicle scheduling and their re-capacitation along different periods, as well as guide complementary initiatives for the positive conditioning of route choices.Future directions on this study include supplementary ground-truth based validations against survey data, and the possibility of assessing the proposed approach on complementary case studies.


Patient safety and involvement of the patients in their safety engagement activities are considered the most important elements in the healthcare professions due to their impact on various individual and organizational outcomes. The study used responses of 456 patients. The simple random sampling (SRS) technique was used to collect data from the respondents. The researcher used individuals as the unit of analysis in this study. The results revealed that patient safety engagement had a positive significant effect on patient safety. When the mediating variable of self-efficacy was analyzed, it showed a significant mediated effect on patient safety. Therefore, it was concluded that self-efficacy mediated the relationship between patient safety engagement and patient safety. The findings of the current study convey that engagement of the patient in the practices for patient safety is predicted through the level of self-efficacy of the patient. The study discussed various implications for theory and practice. The study also discussed potential avenues for future research. In order to reduce medical mistakes, patient safety and patient participation in safety engagement activities are seen to be the most important aspects . The rolThe main objective of the study is to analyze the patient's safety engagement and patient safety by means of the patient's self-efficacy. The main aim of the research was to investigate the mediating effect of patients' self-efficacy on the relationship between patient safety engagement and patient safety in healthcare professionals. Therefore, the researcher used quantitative research as the research approach because valid measurement scales are available for the variables of interest in this study.The paper is organized as follows: Aspden et al.  defined Patient engagement refers to the act of participation of patients themselves and their families along with the healthcare provider for the amelioration of medical facilities and the healthcare safety . PatientAccording to Hall et al. , patientAccording to the studies of Duhn and Medves  and AbidSteps taken towards safety engagement in order to ensure the patients' safety depends upon three keen domains: engaging the patients for the detection of the adverse happenings, increasing the confidence of the patients by empowerment for the assurance of the medical care, and accenting the patient engagement as the significant way for the amelioration of the patients' safety . StudiesBandura  defined Previous studies reflected the self-efficacy of the patients as one of the causal and prime factors for the following medication programs without any interruption . An eminInvolvement or the engagement of the patient in the practices for patient safety can be predicted through the level of self-efficacy of the patient and capabilities to prevent the flaws and errors related to medical or health care . Most ofBased upon a critical review of the relevant literature, the researcher framed the following conceptual framework through which hypotheses were also developed.To achieve the research objectives, the current study would use the following model :On the basis of the conceptual framework, the following hypotheses were developed by the researcher to test them in this study:Patient safety engagement directly affects patient self-efficacy.Patient self-efficacy directly affects patient safety.Patient self-efficacy mediates the relationship between patient safety engagement and patient safety.The researcher used pragmatism as a research philosophy in the current study due to its applied nature in the current research. Pragmatism is a philosophical movement that comprises individuals who believe that an ideology or concept is true if it functions smoothly, that the significance of a notion may be discovered in the practical implications of recognizing it, and that unrealistic ideas should be avoided. It is characterized as a way of thinking about things that emphasizes a logical or practical solution. Pragmatism, as an example, involves solving issues logically and realistically. The aim of this research was to investigate the mediating effect of patients' self-efficacy on the relationship between patient safety engagement and patient safety in healthcare professionals. Therefore, the researcher used quantitative research as the research approach because valid measurement scales are available for the variables of interest to this study. Those measurement scales would help in getting a quantitative data set which would help the researcher to produce empirical results. Research on health and social care commonly uses quantitative research techniques. They employ objective measures in conjunction with statistical methodologies, mathematics, economic studies, or computational modeling to allow for a systematic, rigorous, empirical examination. Contrarily, qualitative health research involves the gathering and methodical analysis of nonquantitative data regarding people's experiences with health or sickness, and the healthcare system provides a number of strategies that can assist to reduce these risks. The researcher used survey design as an appropriate research strategy because it is directly related to the people who would be involved as the respondent of this study. Moreover, according to Fink ; it is bn sampling units from a population of N sampling units. In systematic sampling, all people are chosen at random, as opposed to simple random sampling, which requires that each component of the population be recognized and chosen separately. The researcher used individuals as the unit of analysis. As the researcher used the survey as the research strategy, there was no issue of ethical aspects related to human participants  that is necessarily required to be followed in experimental research. The collected data was managed in Statistical Package for Social Sciences (SPSS). For the purposes of group identification, forecasting numerical results, and descriptive statistics, SPSS analyzes data. For effective data management, this tool also features data processing, graphing, and direct marketing features. The main features of SPSS include the ability to create tables and charts with frequency counts or summary statistics over (groups of) cases and variables while using inferential statistics such as ANOVA, regression, and factor analysis. Also, it uses several different file formats for saving data and output. The SPSS files we will utilize in this study fall into three categories: output files (spv), syntax files (sps), and data files (sav). Various tests of descriptive statistics and inferential statistics would be used to find the answers to research questions and to testify the hypotheses. The researcher used measurement scales of self-efficacy (SE) of Elder et al. [The researcher targeted 550 patients admitted to hospitals in China. Among them, only 456 structured self-administered questionnaires were returned that were completely filled-in in all respects. According to Krejcie and Morgan , a totalr et al. , patientr et al. , and patThe data collected from 456 patients were analyzed with the help of SPSS. Cronbach's alpha measures internal consistency or how closely connected a group of things is. It is regarded as a gauge for the dependability of scales. It is not necessary for the measure to have a “high” value for alpha for it to be one-dimensional. The following reliability statistics  are presSPSS will initially delete all observations with one or more missing values across all variables provided for the current process when a statistical operation is performed. This is referred to as LISTWISE deletion because it is the default procedure. On the basis of the results provided in the tables given above, it was concluded that all the scales had the required level of reliability in the scales used for measuring the variables of interest in this study. Therefore, the researcher went for other analyses.Descriptive statistics are provided in a summary that details the data sample and its measurements and defines, illustrates, and summarizes the key characteristics of a dataset found in the particular research. Reliability analysis may be used to investigate the characteristics of measuring scales and their constituent parts. The reliability analysis approach also generates a number of commonly used scale reliability measures in addition to data on correlations between the scale's individual components. The results of the descriptive statistics of the data  collecteN (listwise) indicates the number of nonmissing values. The variable has N valid observations, which is the number of observations. The sum of N and the number of missing values equals the total number of observations. These showed that the responses were facing safety issues. However, they had an adequate level of self-efficacy and safety engagement. Moreover, the values of standard deviations and variance were good enough to show minor deviations.In M, serves as the mediator. Using regression analysis, a powerful statistical method, you may examine the correlation between two or more important variables. There are many different types of regression analysis, but at its heart, each one examines the impact of one or more independent variables on a dependent variable. The results of the analysis are provided in In order to estimate the effect of independent variables on the dependent variable and to test the hypotheses, the researcher applied mediated regression analysis by running Hay's Macro. Mediation analysis also assumes all of the basic assumptions of the general linear model, such as linearity, normality, error variance homogeneity, and error independence. It is extremely important to double-check these assumptions before doing a mediational study. For significance testing, it either employs the Sobel test or bootstrapping. As this study was aimed at the finding effect, regression analysis was run to test whether or not patient safety engagement significantly affected patient safety and whether patient self-efficacy mediated the relationship between patient safety engagement and patient safety. A proposed causal chain called mediation shows how one variable can impact another, which can then influence a third. The intervening variable, p value) was lower than the threshold value i.e., 0.05. Patient safety engagement (PSE) has a positive effect which is also significant as the significance value  was lower than the threshold value i.e., 0.05. Moreover, the t-value is also greater than 1.96 i.e., 18.9286. As the values of LLCI and ULCI are not zero and both are positive, it can be inferred that the effect of IV from the mediator is significant.Results provided in p value) was lower than the threshold value i.e., 0.05. Patient safety engagement (PSE) and self-efficacy (SE) have positive effects which are also significant as the significance value  was lower than the threshold value i.e., 0.05 for both the variables. Moreover, the t-values of both the variables are also greater than 1.96 with values of LLCI and ULCI being nonzero and positive. Therefore, it can be inferred that patient safety engagement (PSE) and self-efficacy (SE) have positive effects on patient safety (PS).Results provided in p value) was lesser than the threshold value i.e., 0.05. On the contrary, the indirect or mediated effect of patient safety engagement (PSE) on patient safety (PS) through self-efficacy (SE) as the mediator was significant as shown by the lower limits (BootLLCI) and upper limits (BootULCI) both of them being positive. Therefore, it was concluded that self-efficacy mediated the relationship between patient safety engagement and patient safety. Therefore, all the hypotheses developed by the researcher were accepted by rejecting the null hypotheses of this study.Results provided in The current study found significant positive effects of patient safety engagement on the patient safety of the responding patients. This finding is similar to the previous findings of the studies where it was found that patient safety engagement significantly and positively affected patient safety. The studies with similar findings included the WHO , Duhn anThe current study recommends healthcare professionals to utilize patient engagement activities in enhancing their safety. The managers, supervisors, and/or organizational leaders can use the findings to guide their contemporary work environments too. The current study also recommends the researcher to lead the research. This study observed various limitations due to limited time and limited financial resources. Those limitations may serve as the opportunities for future research studies. The current study used self-efficacy as the mediating variable that could possibly serve as a booster to enhance patient safety. However, some other variables might also be tested as potential mediators in this relationship such as self-regulation or psychological capital. Additionally, moderating variables may also be tested to clarify the findings of the current study. Future studies may also be conducted by using moderated-mediation or mediated-moderation models while testing and verifying the findings of the current study.