How shared autonomous vehicle services affect commuters’ value of travel time in Shanghai, China

During armada performance, capoeira player breaks the visual coupling with the opponent because of the turning movement. This study investigated if a phenomenon named “head marking” would characterize as a potential strategy for capoeira player deal with such a break in the informational coupling. The head marking refers to the act of, in turning movements, the head being the last part of the body to move, but the first to finish. Forty experienced volunteers, [male (n = 10) and female (n = 10) beginners, and male (n = 10) and female (n = 10) advanced capoeira players], with an average age of 24.0 ±5.0 years took part in this experiment. The head marking was analysed in relation to armada speed (slow and fast), opponent (with and without), attacking leg (preferred and non-preferred) and learning phase (beginner and advanced). The latter classification was based on the cordon graduations of the Brazilian Capoeira Confederation. Head movement time was smaller than armada movement time (758.8 ms vs. 1916.6 ms, respectively, p < 0.01). Head movement occurred within the armada movement, since it involved negative (-330.47 ms) and positive (806.66 ms) average values for the starting and ending of the head movement, respectively. It was observed that the armadas performed with the preferred lower member had greater average value of head movement time than those performed with non-preferred member (740.41 ms vs. 678.72 ms, respectively, p < 0.05). And, when armadas were performed against a virtual opponent, they involved greater head movement time than those performed without a virtual opponent (758.58 ms vs. 669.43 ms, respectively, p < 0.05). The findings of this study suggest that head movement had functioned as a head marking phenomenon as an armada’s critical component, which vary depending on performers’ lateral dominance and presence of an opponent. They also contribute to the comprehension of motor skill functioning and the elucidation of its underlying mechanisms.

People with advanced cancer often invest substantial amounts of time to receive palliative treatments. This has been labelled the 'time toxicity' of cancer treatment. However, stakeholder views on time toxicity are still being established. This study used mixed methods to explore Australian oncologists' perspectives on the time burdens of palliative systemic cancer treatments. Semi-structured qualitative interviews were conducted with a convenience sample of gastrointestinal oncologists recruited from one metropolitan and one regional centre, supplemented by online advertising through the Australian Gastrointestinal Trials Group. Themes emerging from initial interviews (n = 8) informed the development of an online survey disseminated to Australian oncologists via professional groups. Qualitative data were analysed using an inductive approach. Survey data were summarised descriptively. Fifteen oncologists were interviewed, 60% of whom were primarily based in major metropolitan areas. One overarching theme: the value of time, unified four subthemes: (1) contributors to 'time 'toxicity', (2) benefits and uncertainties, (3) time as a decision-modifier, and (4) proposed solutions. Surveyed oncologists (n = 108) expressed broad agreement with the thematic framework in interviews, affirming the importance of time for patients with advanced cancer and supporting strategies to reduce time burdens. However, responses acknowledged the subjectivity of time 'toxicity' to individual patients. This mixed-methods study establishes Australian oncologists' perspectives on the time toxicity of palliative systemic cancer treatments, identifying potential barriers and opportunities for including discussions of healthcare time into shared decision-making, and systems-level strategies for addressing unwanted healthcare contact time.

The optimization of braking working parameters was conducted by analyzing the influential factors: vehicle speed (80, 100, and 120 km/h), a quarter of the vehicle mass (200, 250, and 300 kg), and brake pressure (3, 4, and 5 MPa). The goal was to achieve the lowest temperature on the braking pad contact surface and reduce braking time. Experimental work was conducted on the test rig BRAKE DYNO 2020. By applying ANOVA analysis, it was found that vehicle speed accounts for 72% of the influence on brake pad temperature, followed by vehicle mass and braking pressure accounting for 20% and 8%, respectively. On the other hand, for the mean value of simulated vehicle braking time, the brake pressure had the biggest influence (66.78%), followed by vehicle speed (21.75%), and a quarter of the vehicle mass (10.90%). Both the Taguchi method and the regression model showed a good correlation with the experimental results.

Purpose This applied proposal aims to create a mechanism applicable to any company where the exact economic value of flexible work arrangements can be measured – that is, translating nonpecuniary benefits into something monetary which can be added to the financial salary. Design/methodology/approach This is a how-to method approach that helps companies to convert nonpecuniary benefits of flexible work arrangements into monetary terms. Findings Initially, the authors discover a way to translate the nonpecuniary benefits of flexible work arrangements into monetary rewards. Theoretically, these monetary rewards are symbolic, but in many cases they are not, due to the fact that free time for the employee could also eliminate needs of hiring third parties. In the practical example provided, we can see how flexible work arrangements can trigger higher pecuniary benefits. Research limitations/implications Further research will be needed to determine behavior in different industries, positions, etc. Practical implications A practical tool for managers to use when hiring and retaining talent. The vision of two forms of salary (financial salary + pecuniary benefits of the flexible work arrangements) allows employees to better realize the corporate efforts in work flexibility. Social implications What you cannot measure, you cannot control. The business community can benefit from measuring the flexible work arrangements using a system that adapts itself to the personal needs of each employee. This system tackles the hypercomplexity of the real value of the free time of people. It is a way to put down in a number the corporate efforts in work flexibility. Originality/value This practical approach helps HR managers to guide other departmental managers in designing flexible work initiatives. Actually, the benefits of these initiatives and efforts in flexibility are predominantly qualitative and not easy to measure. The proposed method translates and converts qualitative assumptions based on sometimes confusing adverbs (good, bad, effective, inefficient, etc.) into real numbers, which can be measured and controlled.

Venous thromboembolic (VTE) complications contribute substantially to perioperative morbidity and mortality. The decision for mechanical and/or chemo-prophylaxis is currently based on VTE risk assessment models since conventional laboratory assays of coagulation usually fail to detect changes indicating hypercoagulability. Rotational thromboelastometry is a novel assay of coagulation, that it could potentially be used in objectively selecting patients at risk for VTE, who should indisputably undergo prophylaxis. We evaluated the association of conventional and novel assays of coagulation and VTE risk. VTE risk was preoperatively assessed in 45 patients scheduled for endoscopic, open and laparoscopic urologic surgery, including transurethral resection of prostate, transurethral resection of bladder tumor, endoscopic vesical or ureteral stone lithotripsy, open prostatectomy, open cystectomy and urinary diversion, open or laparoscopic radical or partial nephrectomy, between March 2021 and October 2022, using three different risk assessment models (RAMs): the European Association of Urology (EAU) RAM, the American Urological Association (AUA) RAM, and the Caprini model. Patients under antiplatelet or anticoagulation agents were excluded. Patients' coagulation profile was determined by measuring PT, fibrinogen, aPTT, and rotational thromboelastometry analysis. For rotational thromboelastometry analysis, extrinsic rotational thromboelastometry and fibrinogen rotational thromboelastometry were examined in every patient. Statistical analysis was performed with ANOVA test and χ2 test. Mean values of all rotational thromboelastometry variables did not vary significantly among different EAU VTE categories. In extrinsic rotational thromboelastometry assessment, a significant difference was observed in the mean values of the Clotting time (CT) between the different risk groups based on AUA RAM. In the comparison between the risk groups defined based on the Caprini score, statistically significant differences were observed in the extrinsic rotational thromboelastometry clot formation time (CFT). In fibrinogen rotational thromboelastometry analysis, significant differences were identified in the clot amplitude after five minutes (A5) and maximum clot firmness (MCF) indices between the AUA risk groups, along with a significant difference in the mean clot formation rate (CFR) value between the risk groups defined based on the Caprini score. Rotational thromboelastometry can provide a detailed evaluation of the hemostatic status in patients undergoing urologic surgery that can be used as an adjunct to the VTE risk assessment models and thus, help to offer prophylaxis on a rather personalized basis. Future studies should assess the utility of thromboelastometry in identifying patients at high risk for VTE after major urological procedures.

ABSTRACTBackgroundSepsis is life‐threatening due to organ dysfunction from a dysregulated host response. Despite macrohemodynamic stabilisation, microcirculatory disturbances may persist. Capillary refill time (CRT) is a simple bedside indicator of microcirculatory perfusion, but its dynamic prognostic value over time is underexplored.AimTo observe CRT changes in sepsis patients and evaluate its predictive value at different time points.Study DesignThis prospective cohort study enrolled sepsis patients receiving bundle therapy at a single centre. Patients were grouped by 28‐day survival. Baseline data, CRT, lactate (Lac) and central venous pressure (CVP) were measured at eight time points (pre‐treatment to 72 h) compare inter‐group and intra‐group differences. Spearman's correlation assessed CRT‐Lac/CVP relationships. ROC analysis evaluated CRT's prognostic value.ResultsOf 86 patients (70 survived, 16 non‐survivors), significant inter‐group differences (p < 0.05) were found in age, SOFA score, lactate and vasoactive drug dosage. CRT and Lac differed significantly between groups at all time points (p < 0.05), while CVP differed at 3, 24 and 72 h. Intra‐group comparisons showed significant changes in all parameters over time (p < 0.01). CRT correlated negatively with CVP in survivors (r = −0.358, p < 0.001). In non‐survivors, CRT positively correlated with Lac and negatively with CVP (r = 0.416 and −0.553, both p < 0.001). ROC analysis indicated 3‐h post‐treatment CRT had the highest predictive value (AUC = 0.981, sensitivity 93.8%, specificity 97.1%). Spearman correlation analysis revealed a positive correlation between ΔCRT₃h and ΔLac₃h in both patient groups: ρ = 0.25, p = 0.035 in the survival group and ρ = 0.52, p < 0.001 in the non‐survival group.ConclusionsCRT is a valuable prognostic marker in sepsis, with 3‐h CRT showing the strongest predictive performance. Its monitoring may guide early treatment decisions.Relevance to Clinical PracticeThis study validates nurse‐measured capillary refill time (CRT) as a simple, early‐warning tool. A prolonged 3‐h CRT accurately identifies high‐risk septic patients, enabling nurses to prioritise care and guide timely resuscitation at the bedside.

Abstract One way to quantify the quality of a forecast is to estimate the forecast error doubling time—the longer the error doubling time, the better is the forecast. Lorenz in 1982 using the well-known logistic model obtained a point estimate of the error doubling time for the growth of root-mean-square (RMS) errors in the numerical model prediction of 500-hPa height by following divergence of the analog pairs over a 100-day period covering 1 December 1980–10 March 1981. While this approach to the point estimate of error doubling time gained widespread acceptance, little reflection reveals that the RMS error itself is subjected to non-Gaussian noise resulting from the errors in the initial conditions used by the numerical model to create the forecast of the 500-hPa height field. By postulating that the noise corrupting the RMS error follows the chi-squared distribution and combining it with the forward sensitivity method (FSM) for dynamic data assimilation, we develop a statistical approach to obtaining the distribution of error doubling time as opposed to a point estimate. Significance Statement Lorenz developed a method for estimating a single-point value of forecast error doubling time using data from ECMWF’s operational forecast model in 1980–81. The uniqueness of his method was the use of analog pairs, in particular the divergence of pairs, fitted to the logistic equation. The method was widely used by numerical weather prediction (NWP) researchers in the meteorology community, but it was found that the same data, the divergence of analog pairs, used with models other than the logistic equation, produced different single-point values of the error doubling time. Is there a single value for estimating the forecast error doubling time using Lorenz’s method? We have answered this question by considering two different approaches: a deterministic approach and a stochastic approach. Knowledge gained from numerical experiments with these two approaches are discussed along with their value to forecasting practice.

Traffic congestion is a persistent urban transportation problem that imposes substantial economic losses through travel delays, increased ‎fuel consumption, and reduced productivity. This study examines the relationship between traffic volume and economic loss resulting ‎from traffic delays along President Jose P. Laurel Highway, a major arterial corridor in Lipa City, Batangas. Using one week of peak-‎hour field observations, data were collected on vehicle volume, average delay per vehicle, and additional fuel consumption. Economic ‎losses were estimated using standard transportation economics approaches, including the Value of Time (VOT) method and fuel cost ‎valuation. Pearson correlation and simple linear regression analyses were employed to quantify the relationship between traffic volume ‎and congestion-related economic losses. The results reveal a strong and statistically significant positive relationship between traffic volume and economic loss, with delay duration identified as the primary contributor to congestion costs. Comparative analysis further ‎shows that PM peak periods generate higher marginal economic losses than AM peak periods, reflecting intensified end-of-day travel ‎demand. These findings demonstrate that traffic congestion along President Jose P. Laurel Highway is not merely an operational concern but a significant economic burden. The study provides empirical evidence to support targeted traffic management measures, infrastructure improvements, and demand management strategies aimed at reducing congestion-related economic losses in Lipa City‎.

Background In patients with alcohol-associated liver disease (ALD), heavy and prolonged alcohol consumption can trigger acute-on-chronic liver failure (ACLF), a condition associated with high early mortality and significant clinical challenges. Early identification of patients at risk is critical for improving outcomes. Aims We conducted a retrospective observational study of patients diagnosed with ALD between January 2000 and December 2024 to develop a predictive model for ACLF. Methods Key clinical indicators were selected using LASSO-regularized logistic regression (LR). The final LR model was visualized as a nomogram and compared with four additional machine learning algorithms. Model performance was evaluated using ten-fold cross-validation and area under the curve (AUC), while feature importance was assessed with Shapley Additive exPlanations values. Results Among 210 patients with ALD, LASSO identified four independent predictors of ACLF: total bilirubin (TBIL), folate, vitamin B12 (VitB12) and the difference from the normal value of prothrombin time (ΔPT). The LR model achieved an AUC of 0.970, indicating excellent predictive accuracy. Conclusion We developed a robust clinical prediction model combining LR and machine learning approaches. TBIL, folate, VitB12 and ΔPT are key prognostic markers that may enable early risk stratification and timely intervention, potentially reducing ACLF incidence in ALD patients.

The aim of this study was to assess the influence of milk’s rennet coagulation properties (RCPs) on cheese yield and cheese-making losses in the production of Parmigiano Reggiano PDO cheese. Higher contents of citric acid (181.10 vs. 172.13 vs. 166.47 mg/100 g) and phosphorus (95.02 vs. 91.14 vs. 88.78 mg/100 g) in milk with optimal and sub-optimal RCPs, compared to milk with poor RCPs, respectively, positively affect the acidity of the milk, lowering the pH values (6.68 vs. 6.70 vs. 6.72, respectively), which results in a faster reaction between chymosin and casein and consequently a reduced time of milk coagulation. The lower values of curd firming time and the higher values of curd firmness, strength to cut (68.97 vs. 64.43 vs. 44.38 g), and strength to compression (31.48 vs. 30.49 vs. 25.70 g) for milk with optimal and sub-optimal coagulation, compared to milk with poor coagulation, result in a higher stress resistance across the technological steps of the cheese-making process, leading to lower fat losses (14.23 vs. 15.48 vs. 16.72%) in the whey and a higher cheese yield (8.79 vs. 8.56 vs. 8.08 kg/100 kg).

Evidence on intranasal (IN) ketamine as an alternative to opioids for acute pain is limited. We compared the efficacy and safety of IN ketamine to intravenous (IV) morphine in emergency department (ED) patients. This triple-blinded, placebo-controlled, randomized trial included consenting adult patients with moderate-to-severe pain (≥70 mm on a visual analog scale[VAS]) who were given either 0.1 mg/kg IV morphine and IN placebo or 1 mg/kg IN ketamine and IV placebo and were monitored for vital signs, pain levels, and adverse events for 120 minutes. The primary outcome was the efficacy of intranasal ketamine compared with intravenous morphine in reducing pain, defined as achieving a ≥ 15-mm decrease in the VAS pain score. The secondary outcomes were adverse events (AEs) and overall patient's satisfaction. Sixty-eight participants (mean age 43.5 ± 12.2 years, 48 male) were randomized equally. Groups were similar at baseline in mean age, sex, and pre-treatment median pain levels. There were no significant differences between IV morphine and IN- ketamine groups in the median [Intra quartile range (IQR)] values of time to onset of significant pain reduction (10.0 [5.0-20.0] vs. 10.0 [5.0-15.0) minutes, P =0.92), maximal pain reduction (30.0 [10.0- 57.0] vs. 20.5 [4.2- 39.5] mm VAS, P =0.18) and time to maximal pain reduction (105.0 [63.7-120.0] vs. 90.0 [45.0-120.0] minutes, P = 0.35). There were no significant differences in frequency of adverse effects at 0, 60, and 120 minutes. This study did not demonstrate a statistically significant difference in efficacy or safety between IN ketamine and IV morphine for the management of acute pain in the emergency department (ED). Moreover, the findings indicate that IN ketamine may be a viable, and potentially superior, alternative to IV morphine.

The widespread adoption of Electric Vehicles (EVs) is critically dependent on the deployment of efficient charging infrastructure. However, existing facility location models typically treat charging duration as an exogenous parameter, thereby neglecting the traveler’s autonomy to make trade-offs between service time and energy needs based on their Value of Time (VoT). This study addresses this theoretical gap by developing a heterogeneous network design model that endogenizes both charging mode selection and continuous charging duration decisions. A bi-objective optimization framework is formulated to minimize the weighted sum of infrastructure capital expenditure and users’ generalized travel costs. To ensure computational tractability for large-scale networks, an exact linearization technique is applied to reformulate the resulting Mixed-Integer Non-Linear Program (MINLP) into a Mixed-Integer Linear Program (MILP). Application of the model to the Hubei Province highway network reveals a convex Pareto frontier between investment and service quality, providing quantifiable guidance for budget allocation. Empirical results demonstrate that the marginal return on infrastructure investment diminishes rapidly. Specifically, a marginal budget increase from the minimum baseline yields disproportionately large reductions in system-wide dwell time, whereas capital allocation beyond a saturation point yields diminishing returns, offering negligible service gains. Furthermore, sensitivity analysis indicates an asymmetry in technological impact: while extended EV battery ranges significantly reduce user dwell times, they do not proportionally lower the capital required for the foundational infrastructure backbone. These findings suggest that robust infrastructure planning must be decoupled from anticipations of future battery breakthroughs and instead focus on optimizing facility heterogeneity to match evolving traffic flow densities.

A new control algorithm is proposed for unstable linear systems with a time delay in the input channel in the presence of external bounded disturbances. The output signal of the plant is measurable, but not its derivatives. The Luenberger observer is used to estimate the state vector of the plant. A subpredictor is designed that predicts future values of the observer state, based on which a control signal is formed that ensures the stability of the closed-loop system. An auxiliary loop approach and an observer of derivatives are used to obtain an estimate of the external disturbance. Based on the disturbance estimate, a disturbance subpredictor is designed that performs multi-step prediction of these disturbances. Such a multi-step approach leads to the structure of the closed-loop system with a state time delay, where the new value of the delay is less than the original one by as many times as the number of subpredictors used. This approach allows to control of plants with a greater delay in the control channel than when using a single predictor. Using the Lagrange mean value theorem, a disturbance subpredictor is formed, where the future value of the disturbance estimate depends on its present value and a finite set of previous measurements. Unlike existing results, where the prediction is carried out by decomposing the disturbance using the Taylor formula, in this paper, to implement the future value of the disturbance, it is not necessary to estimate its derivatives, which improves the quality of regulation in the presence of interference in the measurement channel. The use of a disturbance subpredictor allows us to significantly reduce the disturbance prediction time compared to using one disturbance predictor by as many times as there are subpredictors. Using the Lyapunov-Krasovsky functional methods, sufficient conditions for the stability of the closed-loop system are obtained in the form of a solution to linear matrix inequalities. The use of linear matrix inequalities allows us to calculate the limiting value of the delay time at which the closed-loop system remains stable. The efficiency of the proposed approach is confirmed by the results of modeling in the MATLAB.

This study aimed to examine whether daily personal time—time spent free from external demands and available for self-directed activities—relates to better affective well-being and healthier cortisol patterns in midlife parents, and whether personality traits moderate these associations. A sample of 318 parents (Mage = 40.06 years, SD = 7.54; 45% men) with underage children (Mage of youngest child = 7.61 years, SD = 5.19) completed up to 8 consecutive days of daily diaries (mood, personal time, stress exposure) and up to 4 days of saliva sampling (4 times/day) for cortisol analysis. Multilevel modeling examined within-person links between personal time, positive and negative affect, and diurnal cortisol slopes, controlling for daily stress. Results showed that on days when they had an opportunity for time to themselves, parents experienced higher positive affect, lower negative affect, and steeper cortisol slopes, indicating better stress recovery. The reduction in negative affect with personal time was stronger for parents high in neuroticism and openness, and high neuroticism was also linked with a stronger association between personal time and cortisol slopes. Findings underscore the potential restorative value of daily time to oneself for midlife parents, particularly those high in neuroticism and openness. In the context of the high demands of parenting, personal time may serve as a valuable resource for emotional renewal, solitude, self-care, self-connection, and recovery from daily parenting stress.

The concept of RNA velocity has made it possible to extract dynamic information from single-cell RNA sequencing data snapshots, attracting considerable attention and inspiring various extensions. Nonetheless, existing approaches often lack uncertainty quantification and many adopt unrealistic assumptions or employ complex black-box models that are difficult to interpret. In this paper, we present a Bayesian hierarchical model to estimate RNA velocity, which uses a time-dependent transcription rate and non-trivial initial conditions. We discuss identifiability of the model parameters, including larger values of the latent time, which has not been done so far. Our approach allows for well-calibrated uncertainty quantification, through a novel algorithm that combines Markov chain Monte Carlo and consensus approaches for full Bayesian inference. The proposed method is validated in a comprehensive simulation study that covers various scenarios, and compared to several other widely embraced and commonly recognized approaches for RNA velocity on single-cell RNA sequencing data from mouse embryonic stem cells. Our method provides estimates of gene-shared latent time and velocity vectors with well-calibrated uncertainty, which align with the cell cycle phases of the cells.

The value of time.

The ActiGraph GT9X Link wearable accelerometer has been widely utilized for physical activity (PA) measurement but is no longer in production. The performance of the ActiGraph LEAP, regarded as its successor and released in 2023, remains unevaluated in comparison to other accelerometers. This study aimed to establish concurrent validity of the ActiGraph LEAP device through PA measurements and comparison with the GT9X Link. A total of 26 young adults (mean age = 21 ± 4 years) wore the ActiGraph LEAP and GT9X Link simultaneously for 7 consecutive days on their nondominant wrist. Monitor Independent Movement Summary units were utilized for calculation of daily sedentary time, light PA, and moderate to vigorous PA across valid days of wear (≥10 hr). Nonwear time was determined using a preexisting algorithm. Intraclass correlation coefficient, mean absolute percent error, equivalence tests (with GT9X Link as reference), and Bland-Altman plots assessed agreement between daily values of sedentary time, light PA, and moderate to vigorous PA recorded by each device across all valid days recorded among participants. A total of 149 days of data were compared between the two devices. Across all PA levels, acceptable-excellent agreement was found (mean absolute percent error = 3.86%-13.86% and intraclass correlation coefficient = .94-.99), and Bland-Altman plots showed that at least 90% of recorded data fell within the 95% limits of agreement. The findings suggest that sedentary time and PA measurements using Monitor Independent Movement Summary units from the ActiGraph LEAP compare well with the GT9X Link, indicating that the LEAP performs similarly to the GT9X Link.

To evaluate whether the outcome of IV-tPA Administration (ITA) time differs for each occluded vessel in acute ischemic stroke and to find prognostic predictors following ITA without endovascular treatment. We chose a cohort of only IV-tPA administered patients whose occluded vessel segments were confirmed by neuroimaging. ITA time, National Institute of Health Stroke Scale (NIHSS), Modified Rankin Score (mRS), Early Neurological Improvement (ENI), Alberta Stroke Program Early CT (ASPECT) scores, infarct volumes, and collateral status were recorded. Sixty-seven patients were included with 47 MCA (14 M1, 33 M2), 7 ACA, and 13 PCA occlusions. ROC analysis where time to ITA is the predictor showed poor discrimination (AUC values < 0.7) for prognosis. In PCA infarcts, ENI1 (NIHSS score improvement ≥ 4 points from baseline at 2 hours) was significantly associated (P = 0.045) with ITA time. Higher infarct volume was significantly associated with lower odds of good mRS (1 and 3 months)/ENI4 (≥20% improvement from baseline NIHSS score at 24 hours), good collateral status had a significantly favorable outcome in the MCA, M2 and PCA segments. For each unit increase in ASPECT, the odds of good mRS (0-2 vs. 3-6) in 3 months increased by 2.01 (95% CI = 1.09 to 3.94, P = 0.031). Although the small sample size of PCA and ACA segment occlusion precluded the cut-off values of ITA time, other factors such as age, collateral status, infarct volume, and ASPECT score remain crucial alongside ITA timing. Limitations in this study include the small and imbalanced sample size and the single-center retrospective design, which may limit the generalizability of the results.

Abstract Fused Deposition Modeling FDM is one of the most widely used additive manufacturing techniques due to its simplicity, cost effectiveness, and design flexibility. However, the quality and energy efficiency of FDM process remain challenges that affect the sustainability of this technology. This research aims to optimize FDM process parameters by analyzing the combined influence of four input parameters (extrusion temperature, infill overlap percentage, layer height, and printing speed) on three performance measures: surface roughness, energy consumption, and printing time. A Response Surface Methodology RSM approach based on Box-Benham design was adopted to design the experiments. Furthermore, desirability analysis and Grey Relational Analysis GRA were used to perform multi-objective optimization. Based on desirability analysis, the optimum values of surface roughness, energy consumption, and printing time were 4.5626 μm, 0.0223 kWh, and 13.8929 min respectively, at an extrusion temperature of 216.1616 °C, an infill overlap percentage of 0.20, a layer height of 0.1422 mm, and a printing speed of 180 mm s −1 . The optimum Grey relational Grade value derived from GRA was 0.7343 at an extrusion temperature of 210 °C, an infill overlap percentage of 0.20, a layer height of 0.12 mm, and a printing speed of 240 mm s −1 . A comparison between the RSM desirability results and the GRA results indicated that GRA achieved superior performance with lower predictive error of 3.7% compared to the overall average error of 17.29% for RSM