Failure State Research Articles

Study on precursor features of coal and rock loading failure based on difference network

In order to reveal the spatio-temporal precursor features of coal and rock loading failure, and accurately identify the critical state of coal and rock failure, the development of coal and rock loading failure is regarded as the spatio-temporal evolution dynamical process of the complex network system, the spatio-temporal evolution dynamical characteristics of coal and rock dynamic disasters are analyzed. The precursor features indicators I(t) and Ia(t) of the coal and rock failure based on the difference network are proposed, Brazilian splitting experiments of different types of coal and rock are carried out. Combined with the damage theory, the load model of coal and rock damage characterization based Ia(t) is established. The results show that when the coal-rock system is in the warning critical period, the damage is accelerated, with high potential energy, low rebound and weak robustness, which is reflected in the acoustic emission (AE) and electromagnetic radiation (EMR) data at different spatial monitoring points. When the coal-rock system is in the stable stage, the structure of the correlation network at adjacent moment is similar, and the number of edges in the difference network is small. While when coal or rock is about to fracture, the correlation network at adjacent moment has great structure differences, and there are many edges in the difference network. I(t) and Ia(t) synthesize the signal characteristics of different spatial monitoring points, and reflect the spatio-temporal evolution process and damage state of coal and rock. The damage characterization load based on Ia(t) is in good agreement with the measured load, and the correlation coefficients between the measured load and the calculated load based on Ia(t) of most rock samples are more than 0.80. The research results can be used as the precursor features of coal and rock failure, and have certain significance for the early warning of coal and rock dynamic disasters.

Study on the calculation method of the maximum number of bonded steel plates at the bottom of reinforced concrete beams

Purpose When the reinforced concrete beams are reinforced by bonding steel plates to the bottom, excessive use of steel plates will make the reinforced concrete beams become super-reinforced beams, and there are security risks in the actual use of super-reinforced beams. In order to avoid the occurrence of this situation, the purpose of this paper is to study the calculation method of the maximum number of bonded steel plates to reinforce reinforced concrete beams.Design/methodology/approach First of all, when establishing the limit failure state of the reinforced member, this paper comprehensively considers the role of the tensile steel bar and steel plate and takes the load effect before reinforcement as the negative contribution of the maximum number of bonded steel plates that can be used for reinforcement. Through the definition of the equivalent tensile strength, equivalent elastic modulus and equivalent yield strain of the tensile steel bar and steel plate, a method to determine the relative limit compression zone height of the reinforced member is obtained. Second, based on the maximum ratio of (reinforcement + steel plate), the relative limit compression zone height and the equivalent tensile strength of the tensile steel bar and steel plate of the reinforced member, the calculation method of the maximum number of bonded steel plates is derived. Then, the static load test of the test beam is carried out and the corresponding numerical model is established, and the reliability of the numerical model is verified by comparison. Finally, the accuracy of the calculation method of the maximum number of bonded steel plates is proved by the numerical model.Findings The numerical simulation results show that when the steel plate width is 800 mm and the thickness is 1–4 mm, the reinforced concrete beam has a delayed yield platform when it reaches the limit state, and the failure mode conforms to the basic stress characteristics of the balanced-reinforced beam. When the steel plate thickness is 5–8 mm, the sudden failure occurs without obvious warning when the reinforced concrete beam reaches the limit state. The failure mode conforms to the basic mechanical characteristics of the super-reinforced beam failure, and the bending moment of the beam failure depends only on the compressive strength of the concrete. The results of the calculation and analysis show that the maximum number of bonded steel plates for reinforced concrete beams in this experiment is 3,487 mm2. When the width of the steel plate is 800 mm, the maximum thickness of the steel plate can be 4.36 mm. That is, when the thickness of the steel plate, the reinforced concrete beam is still the balanced-reinforced beam. When the thickness of the steel plate, the reinforced concrete beam will become a super-reinforced beam after reinforcement. The calculation results are in good agreement with the numerical simulation results, which proves the accuracy of the calculation method.Originality/value This paper presents a method for calculating the maximum number of steel plates attached to the bottom of reinforced concrete beams. First, based on the experimental research, the failure mode of reinforced concrete beams with different number of steel plates is simulated by the numerical model, and then the result of the calculation method is compared with the result of the numerical simulation to ensure the accuracy of the calculation method of the maximum number of bonded steel plates. And the study does not require a large number of experimental samples, which has a certain economy. The research result can be used to control the number of steel plates in similar reinforcement designs.

Identifying and prioritizing measures to reduce the failure of the implementation of health system policies based on the technique of analyzing failure states and their effects and fuzzy TOPSIS

Inroduction: policy implementation is the actions that are taken by government or private sector individuals with the aim of realizing the goals of the policy.Many experts have listed many factors in explaining the factors affecting policy implementation and the problems of policy implementation, and most of them believe that the problems of policy implementation are different with the conditions of each society. Several measures lead to the reduction of failure in the implementation of health system policies/ The purpose of this research is to identify and rank these factors.
 Materials and methods: This research was applied and in terms of strategy, it was a survey. The research community consisted of 21 health managers of the country, who were selected through non-random and purposeful sampling. The tools of data collection are interviews and questionnaires, and the FMEA technique and the combined approach of AHP and Fuzzy TOPSIS were used to analyze the data.
 Results: The results of the research showed that the experts have a total of 10 dimensions in the spectrum of failure reduction measures, including cultural factors, communication, structure, implementation method, management, support, manpower.policy implementers, society, policy formulation and environment and 50 components. They proposed important measures effective in reducing the failure of the implementation of health system policies.
 Conclusion: What was stated in this research as the measures to reduce the failure in the implementation of these policies will help the managers and actors of the health system policy field to prevent the occurrence of problems in the path of successful implementation of the health system policies by knowing the factors that reduce the failure of the implementation of the health system policies. get healthy.

Effects of Staggered Plates on the Uplift Failure State and Bearing Capacity of NT-CEP Pile Groups

Plate position is an important parameter of a New Type Concrete Expanded-Plate (NT-CEP) pile. In this study, two small-scale test models and two, four, six, and nine finite element models were established using a visual small-scale model of half-section piles, an undisturbed soil pull-out test, and the ANSYS finite element software R19.0. The NT-CEP pile groups were studied with the plates set at staggered positions. This study mainly analyzes the displacement contours, stress curves, and load-displacement curves under the action of vertical tension and determines the influence of staggered plate positions on the performance and bearing capacity of the NT-CEP pile group, which provides theoretical support for its application in practical engineering. The bearing plate positions affect the performance of the pile group. The stress distribution in each pile in the pile group is uneven when plate positions are staggered, and the pile with the lower plate position bears a greater force. This has a great influence on the bearing capacity of the NT-CEP pile group. If allowed, the plates can be first set at the same position. If appropriate, the plates can be set in staggered positions; however, a reasonable distance between the upper and lower plates should be considered.

AutoML‐based predictive framework for predictive analysis in adsorption cooling and desalination systems

AbstractAdsorption cooling and desalination systems have a distinct advantage over other systems that use low‐grade waste heat near ambient temperature. Since improving their performance, including reliability and failure prediction, is challenging, developing an efficient diagnostic system is of great practical significance. The paper introduces artificial intelligence (AI) and an automated machine learning approach (AutoML) in a real‐life application for a computational diagnostic system of existing adsorption cooling and desalination facilities. A total of 1769 simulated data points containing data indicating a failure status are applied to develop a comprehensive AI‐based Diagnostic (AID) system covering a wide range of 42 input parameters. The paper introduces a conditional monitoring system for adsorption cooling and desalination systems. The novelty of the presented study mainly consists of two aspects. First, the intelligent system predicts the health or failure states of various components in a complex three‐bed adsorption chiller installation using the extensive input data sets of 42 different operating parameters. The developed AID expert tool, based on selecting the best from 42 models generated by the DataRobot platform, was validated on the complex, existing three‐bed adsorption chiller. The AID system correctly identified healthy and failure states in various installation components. The developed expert system is very efficient (AUC = 0.988, RMSE = 0.20, LogLoss = 0.14) in predicting emergency states. The proposed method constitutes a quick and easy technique for failure prediction and represents a complementary tool compared to the other condition monitoring methods.

Influence of Plate Position on Uplift Failure State and Bearing Capacity of NT-CEP Pile Groups

The previous research results of the research group demonstrated that the plate position is the main factor affecting the uplift bearing capacity of the new type of concrete expanded plate pile (NT-CEP pile) group and the failure state of the soil around the pile. In this study, the visual half-section pile small-scale model of undisturbed soil tension test and ANSYS Finite Element Software comparative analysis two-pile small-scale test model and two-, four-, six-, and nine-pile models, which included the corner, side, and middle piles, were developed. The effect of the plate position on the displacement, stress, and bearing mechanism of the NT-CEP pile group under vertical tension was determined, which further improved the design concept of the NT-CEP pile group and provided strong theoretical support for its widespread application.

Rock slope stability assessment based on the critical failure state curve for the generalized Hoek‒Brown criterion

Rock slope stability assessment based on the critical failure state curve for the generalized Hoek‒Brown criterion

Experimental Study on Wooden Pin Reinforcement of the Typical Mortise-Tenon Joints of Ancient Timber Frames

ABSTRACT The ancient timber frames is the precious architectural heritage of China. The seismic performance of mortise tenon joints (MTJ) directly affects the seismic performance of the ancient timber frames. This study presents a method that utilizes wooden pins to reinforce MTJs, enhancing the seismic performance of timber frame structures. The quasi-static test and finite element model were carried out to study the mechanical properties of the MTJ reinforced by the wood pins. From the failure state of the MTJs, it is found that the main deformation is the slip deformation between mortise and tenon. The mutual friction between the mortise and the tenon has a certain energy dissipation and shock absorption effect. The deformation state, stress distribution, stiffness degradation curve, etc. of the MTJ were obtained by finite element model of the MTJ. Additionally, the study confirms that reinforced MTJ can help restrict displacement changes within the wooden frame. The results show the bearing capacity of MJT reinforced with wooden pins is approximately 11.3% higher compared to that of MTJ without reinforcement. The reinforcement of wood pins effectively controls the horizontal displacement of the wooden frame, which is reduced by about 50%–62% compared with the unreinforced wooden frame. The locating the wooden pin-reinforced MTJs in the outer columns and middle layer columns reduces structural displacement, which is 31.53% in X derection, 5% in Y derection, 25.86% in Z derection.

MANAGEMENT OF ARDS IN DROWNING PATIENT IN INTENSIVE CARE UNIT

Acute Respiratory Distress Syndrome (ARDS) occured in drowning patients in both fresh or salt water. This is a consequence of aspiration of fluid into the lungs. This condition can be made worse by the possibility of hypothermia, arrhythmia, or neurological impacts as a result of anoxia. A male, 16 years old, 60 kg without comorbid was drowned in a well, came on referral from a another hospital, he was admitted to the ward for 2 days. The patient arrived in emergency room and the patient is in respiratory failure state and ARDS. This patient was given intubation in the emergency room, after this patient is stable he was transfered to ICU. In the ICU, the patient was given mechanical ventilation therapy on 4th day and then he was given weaning gradually, on 7th day the patient was given extubation. In general, treatment outcome of drowned patient really depends on how effective and fast the maangement of the respiratory distress in the incident location and until taken to hospital. Mechanical ventilation therapy follows the general ARDS management pattern, using PEEP and lung protection strategies. Monitoring and caution is needed during the weaning process to prevent recurrence of pulmonary edema and re-intubation.

Shock fatigue damage failure boundary study of BGA solder joints based on shock response spectrum

Multiple shock damage failure of ball grid array (BGA) solder joints is one of the important reasons for reusable spacecraft mission failure. Shock fatigue damage failure boundary of BGA solder joints is proposed based on shock response spectrum (SRS), which can be used to assess the damage failure state. Weibull distribution is employed to characterize the shock fatigue life for a specified SRS. A Bayesian estimation method based on the Bootstrap approach is proposed to estimate Weibull distribution parameters. By using the time-domain load synthesized method based on wavelet and the experimentally validated shock fatigue life model, the shock fatigue life data of BGA solder joints corresponding to different SRS are extended. The variation patterns of the scale and shape parameters with the SRS parameters is analyzed. Then the shock fatigue damage failure boundary based on SRS is determined for a given design life and reliability. The results show that the critical SRS amplitude increase with the rise of the inflection point frequency and the low-frequency slope, respectively. The developed method is expected to provide references for the environment-adaptive design of BGA solder joints in reusable spacecraft.

EAPRAD: A MAC protocol for Enhancing Access Probability and Reducing Access Delay in VANETs

Vehicular Ad Hoc Networks (VANETs) present challenges in terms of access collision and merge collision, leading to increased access delay in end-to-end vehicle communication. How to address these issues remains an unsolved problem. In this paper, we propose EAPRAD (Enhancing Access Probability and Reducing Access Delay), a novel MAC (Media Access Control) protocol based on a Markov model. Our protocol defines the number of vehicle accessing time slot failures, with different failure states forming a partial Markov chain. The highest failure status vehicle is prioritized to access the time slot, effectively resolving the problem of indefinite time slot reservations during the back-off phase. Furthermore, after acquiring the time slot, vehicles may still experience package collision, particularly when vehicles traveling in opposite directions share the same frequency band. To address this, our protocol introduces a new MAC frame structure that partitions available frequency band resources based on distinct driving directions, eliminating merge collision in opposite directions. For vehicles traveling in the same direction, intermediate nodes are utilized to proactively anticipate and prevent package collision. To model the state transition of access collision probability and merge, we develop a Continuous Time Markov Chain (CTMC) analytical model. Simulation results demonstrate that EAPRAD reduces end-to-end delay and beacon lost rate (BLR), thereby improving overall network performance in VANETs.

Bearing Fault Diagnosis Method Based on Multi-Domain Feature Selection and the Fuzzy Broad Learning System

In recent years, the Broad Learning System (BLS) has been acknowledged for its potential to revolutionize traditional artificial intelligence methods due to its short training time, strong interpretability, and simple structure. In the evolution of BLS, Prof. C. L. Philip Chen’s team introduced the Fuzzy Broad Learning System (FBLS) by replacing the feature nodes of BLS with fuzzy subsystems, thereby further reducing the training time. However, the traditional FBLS, with its straightforward structure, falls short in achieving higher fault diagnosis accuracy when handling raw vibration signals. This paper presents a bearing fault diagnosis approach employing multi-domain feature selection and the fuzzy broad learning system (MS-FBLS), aiming to enhance the diagnostic accuracy of FBLS through multi-domain feature selection. Primarily, a set of 49 features spanning time domain, frequency domain, time-frequency domain, and entropy values is extracted from the original vibrational signals. This combination builds a 49-dimensional multidomain feature set that exploits the information behind the input data as much as possible, thus compensating for the lack of feature extraction capability in FBLS. Afterward, the Random Forest algorithm assesses the significance of all features, leading to a reordering of the multidomain feature set based on their respective importance levels. Ultimately, the reorganized multidomain feature set is then fed into the FBLS, enabling the identification of various failure states within the bearing. The experimental validation conducted on the rolling bearing fault simulation test bed showcased that, in comparison to the traditional FBLS, the MS-FBLS method not only elevates diagnostic accuracy by 23.46%, but also substantially enhances diagnostic speed. These results serve as comprehensive evidence affirming the effectiveness of the method.

Bedding Slope Destabilization under Rainfall: A Case Study of Zhuquedong Slope in Hunan Province, China

The soft interlayer and rock structure play a significant role in controlling the deformation of the bedding slope, and it is necessary to consider the phenomenon of the sudden change of local response in these key parts under rainfall conditions, and then to clarify the mechanism of rainfall infiltration and damage mechanism of such slopes. In this paper, a large red-layered flat-dipping bedding landslide was selected as the research object, and numerical calculations based on the Van Genuchten model for saturated–unsaturated flow were performed in order to investigate the hydrological response and distribution patterns of water within the slope during rainfall. Moreover, stability analysis was performed based on the seepage field results and secondary development of FLAC3D, and the landslide evolution process was simulated and reproduced using the constitutive model of double-variables and the strength reduction method (SRM). The results showed that the effects of heavy rainfall on the water distribution and stability of the highway slope are significant, while the effects on the natural slope are not significant. There are three phases of the slope destabilization: flexure and uplift state, deformation exacerbation state and shear failure state. The slope destabilization mechanism is a typical “sliding-bending-shearing” type. The results of the study can provide a theoretical basis for the study of the seepage, stability analysis and destabilization mechanism of bedding slopes.

Improvement of the Cracking Moment-Based Asphalt Mixture Splitting Test Method and Splitting Strength Research

The asphalt mixture splitting test is one of the most important methods for measuring asphalt’s tensile properties. To characterize the limitations of the traditional splitting test and the influence of the specimen size and loading conditions on the accuracy of the test, the factors affecting the strength of the splitting test were analyzed to reveal the splitting failure state and establish a unified representation model between the splitting and direct tensile tests. Initially, the moment of specimen cracking was taken as a key indicator, combined with image processing technology, to establish a set of criteria to judge the splitting test. Subsequently, standardized splitting tests were conducted and compared to tests of different specimen sizes and loading methods. Based on the octahedral strength theory, the stress points before and after the improved test were compared to the existing failure criteria. Direct tensile and splitting tests were conducted at different rates, and a unified strength–rate function model was established, realizing the unified representation of direct tensile and splitting tests. The research results indicate that the standardized splitting test is prone to the phenomenon wherein the specimen end face cracks before the center, affecting the accuracy of the test and potentially leading to redundant material strength evaluations. Using a loading method with a “35 mm specimen thickness” and a “0.3 mm rubber gasket + 12.7 mm arc-shaped batten” can essentially achieve the test hypothesis of “cracking at the center first”, resulting in less discrete outcomes and closer alignment to the three-dimensional stress failure state. The tensile and splitting strengths are both power function relationships with the rate as the independent variable, establishing a unified function model of the tensile and failure strengths. The research provides a more reliable testing method and calculation model for asphalt pavement structure design, and it also provides an effective basis for the improvement of splitting tests on materials such as concrete and rock.

Optimization of Structural Steel Used in Concrete-Encased Steel Composite Columns via Topology Optimization

Concrete-encased steel composite columns are preferred for their exceptional ductility and strength, particularly in high-rise buildings. This research aims to enhance both the strength and ductility of these composite columns by increasing the height of the steel profile. Typically, hexagonal or circular openings, referred to as castellated elements, are incorporated into the steel profile to achieve this height increase. This study employed a topology optimization method to identify the ideal opening shape for the steel profile in concrete-encased steel composite columns. The analysis revealed a sinusoidal-like opening shape, which was then refined for manufacturing. The optimal opening shape was used to increase the height of the existing steel profile, and nonlinear analyses were conducted to evaluate the effectiveness of this new optimized steel profile in concrete-encased steel composite columns. Two concrete-encased steel composite columns were designed: one with the optimal steel profile and the other with a standard steel I profile. ANSYS APDL 19.0 software was used to simulate an experiment based on an existing concrete-encased steel column to validate the nonlinear analysis. The verification analysis demonstrated a remarkable similarity between the experimental and numerical load–displacement graphs, indicating that the numerical analysis was reliable. In the analysis of the composite columns, both axial and lateral forces were applied in the nonlinear analyses. The axial force was applied at 15% of the column’s capacity, while the lateral force was applied until the composite column reached a state of failure. The results of the nonlinear analyses allowed for a comparison of load–displacement curves and the performance of the composite columns. In comparison to the standard steel I profile, the steel profile with the optimal opening shape increased load-carrying capacity by approximately 19% and energy absorption capacity by approximately 24%.

A novel score to predict left ventricular recovery in peripartum cardiomyopathy derived from the ESC EORP Peripartum Cardiomyopathy Registry.

There are no established clinical tools to predict left ventricular (LV) recovery in women with peripartum cardiomyopathy (PPCM). Using data from women enrolled in the ESC EORP PPCM Registry, the aim was to derive a prognostic model to predict LV recovery at 6 months and develop the 'ESC EORP PPCM Recovery Score'-a tool for clinicians to estimate the probability of LV recovery. From 2012 to 2018, 752 women from 51 countries were enrolled. Eligibility included (i) a peripartum state, (ii) signs or symptoms of heart failure, (iii) LV ejection fraction (LVEF) ≤ 45%, and (iv) exclusion of alternative causes of heart failure. The model was derived using data from participants in the Registry and internally validated using bootstrap methods. The outcome was LV recovery (LVEF ≥50%) at six months. An integer score was created. Overall, 465 women had a 6-month echocardiogram. LV recovery occurred in 216 (46.5%). The final model included baseline LVEF, baseline LV end diastolic diameter, human development index (a summary measure of a country's social and economic development), duration of symptoms, QRS duration and pre-eclampsia. The model was well-calibrated and had good discriminatory ability (C-statistic 0.79, 95% confidence interval [CI] 0.74-0.83). The model was internally validated (optimism-corrected C-statistic 0.78, 95% CI 0.73-0.82). A model which accurately predicts LV recovery at 6 months in women with PPCM was derived. The corresponding ESC EORP PPCM Recovery Score can be easily applied in clinical practice to predict the probability of LV recovery for an individual in order to guide tailored counselling and treatment.

Modifying RL Policies with Imagined Actions: How Predictable Policies Can Enable Users to Perform Novel Tasks

It is crucial that users are empowered to use the functionalities of a robot to creatively solve problems on the fly. A user who has access to a Reinforcement Learning (RL) based robot may want to use the robot's autonomy and their knowledge of its behavior to complete new tasks. One way is for the user to take control of some of the robot's action space through teleoperation while the RL policy simultaneously controls the rest. However, an out-of-the-box RL policy may not readily facilitate this. For example, a user's control may bring the robot into a failure state from the policy's perspective, causing it to act in a way the user is not familiar with, hindering the success of the user's desired task. In this work, we formalize this problem and present Imaginary Out-of-Distribution Actions, IODA, an initial algorithm for addressing that problem and empowering user's to leverage their expectation of a robot's behavior to accomplish new tasks.

Chronic organ damage: Understanding fibrosis

Chronic organ damage: Understanding fibrosis Fibrosis was once considered irreversible, resulting from chronic organ damage; Ken-Ichi Kobayashi from Notre Dame Seishin University tells us why the possibility of treatment to reverse the disease is gaining attention. Organ fibrosis is a common phenomenon observed in various organ failure states resulting from disease and aging. The most common examples are renal fibrosis in chronic kidney disease, liver fibrosis in cirrhosis, lung fibrosis in idiopathic pulmonary fibrosis, and pancreatic fibrosis in chronic pancreatitis. The total number of patients with organ fibrosis in Japan is nearly 20 million, and it is no exaggeration to say that it is a ‘national disease.’ Until recently, fibrosis was considered to be the end result of chronic organ damage and an irreversible condition with a poor prognosis. In recent years, however, fibrosis has begun to be recognized as a reversible process, and the possibility of treatment is gaining attention. It is also becoming clear that fibrosis is caused by complex cellular and inter-organic networks rather than by specific organs, and therefore, common pathological mechanisms are thought to exist even in various types of fibrosis. However, the common pathological mechanism of fibrosis, especially fibrosis-attracting factors, is still an enigma.

Automated Software Process Discovery and Real-Time Monitoring

Process monitoring is the concept based on managing the state of a business processes executed in an enterprise software. The named status and execution time are two important parameters to infer the state of a process in real-time. An execution of the process end to end is called as process instance. This paper covers monitoring process instances in real-time based on the data metric generated from event logs, where data metrics of a Business Process Models (BPM) – a Weighted Directed Acyclic Graph (WDAG) represents process model with its heuristics such as complete execution time of process, execution time between steps/activities and the status. Firstly, the process model is discovered either by manually or automatically from the events that are recorded from the logs using unsupervised learning techniques and heuristics of different steps of a process are modeled using statistical methods. Both process model and its heuristics are deployed to help process engineers to understand the path of executions of a business process, its state and performance in real-time. Path of executions involves most successful path, longest and shortest paths, error state if the process instances abruptly ends in between, state of failure etc., On the performance front the range of time taken to complete the process, for each step, most and least time consuming, identifying the steps taking more time than usual etc., Process engineers/users are notified if abnormalities are observed. KEY WORDS Process Mining, Process Monitoring, BPM, PM4PY, Standard Deviation (SD)

Post Cardiac Arrest Care in the Cardiac Intensive Care Unit.

Cardiac arrests constitute a leading cause of mortality in the adult population and cardiologists are often tasked with the management of patients following cardiac arrest either as a consultant or primary provider in the cardiac intensive care unit. Familiarity with evidence-based practice for post-cardiac arrest care is a requisite for optimizing outcomes in this highly morbid group. This review will highlight important concepts necessary to managing these patients. Emerging evidence has further elucidated optimal care of post-arrest patients including timing for routine coronary angiography, utility of therapeutic hypothermia, permissive hypercapnia, and empiric aspiration pneumonia treatment. The complicated state of multi-organ failure following cardiac arrest needs to be carefully optimized by the clinician to prevent further neurologic injury and promote systemic recovery. Future studies should be aimed at understanding if these findings extend to specific patient populations, especially those at the highest risk for poor outcomes.