The development of batteries used in electric vehicles towards sustainable development poses challenges to designers and manufacturers. Although there has been research on the analysis of the environmental impact of batteries during their life cycle (LCA), there is still a lack of comparative analyses focusing on the first phase, i.e., the extraction and processing of materials. Therefore, the purpose of this research was to perform a detailed comparative analysis of popular electric vehicle batteries. The research method was based on the analysis of environmental burdens regarding the ecological footprint of the extraction and processing of materials in the life cycle of batteries for electric vehicles. Popular batteries were analyzed: lithium-ion (Li-Ion), lithium iron phosphate (LiFePO₄), and three-component lithium nickel cobalt manganese (NCM). The ecological footprint criteria were carbon dioxide emissions, land use (including modernization and land development) and nuclear energy emissions. This research was based on data from the GREET model and data from the Ecoinvent database in the OpenLCA programme. The results of the analysis showed that considering the environmental loads for the ecological footprint, the most advantageous from the environmental point of view in the extraction and processing of materials turned out to be a lithium iron phosphate battery. At the same time, key environmental loads occurring in the first phase of the LCA of these batteries were identified, e.g., the production of electricity using hard coal, the production of quicklime, the enrichment of phosphate rocks (wet), the production of phosphoric acid, and the uranium mine operation process. To reduce these environmental burdens, improvement actions are proposed, resulting from a synthesized review of the literature. The results of the analysis may be useful in the design stages of new batteries for electric vehicles and may constitute the basis for undertaking pro-environmental improvement actions toward the sustainable development of batteries already present on the market. Full article

The robust electronegativity of the [BO₃]³⁻ structure enables the extraction of electrons from adjacent metals, offering a strategy for modulating oxygen activation in propane oxidative dehydrogenation. Metals (Ni 1.91, Al 1.5, and Ca 1.0) with varying electronegativities were employed to engineer borate catalysts. Metals in borate lacked intrinsic catalytic activity for propane conversion; instead, they modulated [BO₃]³⁻ group reactivity through adjustments in electron density. Moderate metal electronegativity favored propane oxidative dehydrogenation to propylene, whereas excessively low electronegativity led to propane overoxidation to carbon dioxide. Aluminum, with moderate electronegativity, demonstrated optimal performance. Catalyst AlBOx-1000 achieved a propane conversion of 47.5%, with the highest propylene yield of 30.89% at 550 °C, and a total olefin yield of 51.51% with a 58.92% propane conversion at 575 °C. Furthermore, the stable borate structure prevents boron element loss in harsh conditions and holds promise for industrial-scale catalysis. Full article

Establishing artificial sand-fixing shrubs is a key measure to curb dune flow and drive changes in the soil stocks and cycling of carbon and nitrogen. But our understanding of these dynamics across years of sand-fixing afforestation and the factors influencing them remains inadequate, making it hard to accurately assess its capacity to sequester carbon. To fill that knowledge gap, this study investigated soil organic carbon (SOC) and soil total nitrogen (STN) stocks in Mu Us Desert under artificial sand-fixing shrub stands of different ages (10, 30, 50, and 70 years old) vis-à-vis a mobile sand dune, to determine whether Caragana korshinskii afforestation improved stock characteristics and whether SOC and STN stocks were correlated during the restoration processes. The results showed that the pattern observed is consistent with an increase over time in the stocks of both SOC and STN. At 10, 30, 50, and 70 years, these stocks were found to be 1.8, 2.3, 3.2, and 5.5 times higher for SOC, and 1.3, 1.6, 2.1, and 2.7 times higher for STN, respectively, than those of the control (mobile sand) dune. Stocks of SOC and STN mainly increased significantly in the 0–10 cm soil layer. The SOC stock was correlated positively with the STN stock as well as the C:N ratio. The slope of the regression for the C:N ratio against stand age was positive, increasing slightly faster with afforestation age. Additionally, our findings suggest that during the establishment of artificial stands of shrubs, the size of the STN stock did not expand as fast as the SOC stock, resulting in an asynchronous N supply and demand that likely limits the accumulation of soil organic matter. This research provides important evidence for the sustainable development of desertified ecosystems. Full article

Floods are devastating phenomena that occur almost all around the world and are responsible for significant losses, in terms of both human lives and economic damages. When floods occur, one of the challenges that emergency response agencies face is the identification of the flooded area so that access points and safe routes can be determined quickly. This study presents a flood detection methodology that combines transfer learning with vision transformers and satellite images from open datasets. Transformers are powerful models that have been successfully applied in Natural Language Processing (NLP). A variation of this model is the vision transformer (ViT), which can be applied to image classification tasks. The methodology is applied and evaluated for two types of satellite images: Synthetic Aperture Radar (SAR) images from Sentinel-1 and Multispectral Instrument (MSI) images from Sentinel-2. By using a pre-trained vision transformer and transfer learning, the model is fine-tuned on these two datasets to train the models to determine whether the images contain floods. It is found that the proposed methodology achieves an accuracy of 84.84% on the Sentinel-1 dataset and 83.14% on the Sentinel-2 dataset, revealing its insensitivity to the image type and applicability to a wide range of available visual data for flood detection. Moreover, this study shows that the proposed approach outperforms state-of-the-art CNN models by up to 15% on the SAR images and 9% on the MSI images. Overall, it is shown that the combination of transfer learning, vision transformers, and satellite images is a promising tool for flood risk management experts and emergency response agencies. Full article

Multisystem Inflammatory Syndrome in Children (MIS-C) is a potentially life-threatening complication of COVID-19. The pathophysiological mechanisms leading to severe disease are poorly understood. This study leveraged clinical samples from a well-characterized cohort of children hospitalized with COVID-19 or MIS-C to compare immune-mediated biomarkers. Our objective was to identify selected immune molecules that could explain, in part, why certain SARS-CoV-2-infected children developed MIS-C. We hypothesized that type-2 helper T cell-mediated inflammation can elicit autoantibodies, which may account for some of the differences observed between the moderate–severe COVID-19 (COVID⁺) and MIS-C cohort. We enumerated blood leukocytes and measured levels of selected serum cytokines, chemokines, antibodies to COVID-19 antigens, and autoantibodies in children presenting to an academic medical center in Connecticut, United States. The neutrophil/lymphocyte and eosinophil/lymphocyte ratios were significantly higher in those in the MIS-C versus COVID⁺ cohort. IgM and IgA, but not IgG antibodies to SARS-CoV-2 receptor binding domain were significantly higher in the MIS-C cohort than the COVID⁺ cohort. The serum levels of certain type-2 cytokines (interleukin (IL)-4, IL-5, IL-6, IL-8, IL-10, IL-13, and IL-33) were significantly higher in children with MIS-C compared to the COVID⁺ and SARS-CoV-2-negative cohorts. IgG autoantibodies to brain antigens and pentraxin were higher in children with MIS-C compared to SARS-CoV-19-negative controls, and children with MIS-C had higher levels of IgG anti-contactin-associated protein-like 2 (caspr2) compared to the COVID⁺ and SARS-CoV-19-negative controls. We speculate that autoimmune responses in certain COVID-19 patients may induce pathophysiological changes that lead to MIS-C. The triggers of autoimmunity and factors accounting for type-2 inflammation require further investigation. Full article

Monitoring the ratio of two correlated normal random variables is often used in many industrial manufacturing processes. At the same time, measurement errors inevitably exist in most processes, which have different effects on the performance of various charting schemes. This paper comprehensively analyses the impacts of measurement errors on the detection ability of the cumulative sum (CUSUM) charting schemes for the ratio of two correlated normal variables. A thorough numerical assessment is performed using the Monte Carlo simulation, and the results indicate that the measurement errors negatively impact the performance of the CUSUM scheme for the ratio of two correlated normal variables. Increasing the number of measurements per set is not a lucrative approach for minimizing the negative impact of measurement errors on the performance of the CUSUM charting scheme when monitoring the ratio of two correlated normal variables. We consider a food formulation as an example that illustrates the quality control problems involving the ratio of two correlated normal variables in an industry with a measurement error. The results are presented, along with some suggestions for further study. Full article

Background: The escalating prevalence of ESBL-producing Enterobacteriaceae in Qatar’s pediatric population, especially in community-onset febrile urinary tract infections (FUTIs), necessitates a comprehensive investigation into this concerning trend. Results: Over the course of one year, a total of 459 infants were diagnosed and subsequently treated for UTIs. Cases primarily occurred in infants aged over 60 days, predominantly non-Qatari females born from term pregnancies. Notably, E. coli and K. pneumoniae were the most frequently identified organisms, accounting for 79.7% and 9.8% in the ESBL group and 57.2% and 18.7% in the non-ESBL group, respectively. Interestingly, hydronephrosis emerged as the most prevalent urological anomaly detected in both ESBL (n = 10) and other organism (n = 19) groups. Methods: In this retrospective cohort study conducted in Qatar, we meticulously evaluated the prevalence of pediatric FUTIs. Our study focused on febrile infants aged less than 1 year, excluding those with urine samples not obtained through a catheter. Conclusions: E. coli and K. pneumoniae prevailed as the predominant causative agents in febrile children in Qatar, with hydronephrosis being identified as the most common urological anomaly. Moreover, our findings suggested that gentamicin served as a viable non-carbapenem option for hospitalized ESBL cases, while oral nitrofurantoin showed considerable promise for uncomplicated ESBL UTIs. Full article

African swine fever (ASF) is an acute, hemorrhagic, highly contagious disease in pigs caused by African swine fever virus (ASFV). Our previous study identified that the ASFV MGF300-2R protein functions as a virulence factor and found that MGF300-2R degrades IKKβ via selective autophagy. However, the E3 ubiquitin ligase responsible for IKKβ ubiquitination during autophagic degradation still remains unknown. In order to solve this problem, we first pulled down 328 proteins interacting with MGF300-2R through immunoprecipitation-mass spectrometry. Next, we analyzed and confirmed the interaction between the E3 ubiquitin ligase TRIM21 and MGF300-2R and demonstrated the catalytic role of TRIM21 in IKKβ ubiquitination. Finally, we indicated that the degradation of IKKβ by MGF300-2R was dependent on TRIM21. In summary, our results indicate TRIM21 is the E3 ubiquitin ligase involved in the degradation of IKKβ by MGF300-2R, thereby augmenting our understanding of the functions of MGF300-2R and offering insights into the rational design of live attenuated vaccines and antiviral strategies against ASF. Full article

The mapping of thermokarst landscapes and the assessment of their conditions are becoming increasingly important in light of a rising global temperature. Land cover maps provide a basis for quantifying changes in landscapes and identifying areas that are vulnerable to permafrost degradation. The study is devoted to assessing the current state of thermokarst terrain on Arga Island. We applied a random forests algorithm using the capabilities of the Google Earth Engine cloud platform for the supervised classification of the composite image. The analyzed composite consists of a Sentinel-2 image and a set of calculated indices. The study found that thermokarst-affected terrains occupy 35% of the total area, and stable terrains cover 29% at the time of image acquisition. The classifier has also mapped water bodies, slopes, and blowouts. The accuracy assessment revealed that the overall accuracy for all the different land cover classes was 98.34%. A set of other accuracy metrics also demonstrated a high level of performance. This study presents significant findings for assessing landscape changes in a region with unique environmental features. It also provides a potential basis for future interdisciplinary research and for predicting future thermokarst landscape changes in the Lena Delta area. Full article

Understanding the intricate dynamics of social media users’ information-sharing behaviours during crises is essential for effective public opinion management. While various scholarly efforts have attempted to uncover the factors influencing information sharing through different lenses, the underlying mechanisms remain elusive. Building upon the heuristic–systematic model (HSM) and construal level theory (CLT), this study explores the complex mechanisms that govern social media users’ information-sharing behaviours. The results indicate that both cognition and emotion play crucial roles in shaping users’ information-sharing behaviours, with systematic cues having the most significant impact on information-sharing behaviours. In terms of heuristic cues, positive emotions are more influential on information-sharing behaviours than primary cognition and negative emotions. Furthermore, spatial distance emerges as a key moderator, influencing individuals’ levels of engagement in information sharing. Emotion also acts as a mediator, connecting cognition to information sharing. This study provides insights into the sophisticated mechanisms of information sharing during crises, offering valuable implications for emergency management agencies to utilise social media for targeted public opinion guidance. Full article

In this paper, we present an efficient method for solving a class of higher order fractional differential equations with general boundary conditions. The convergence of the numerical method is proved and an error estimate is given. Finally, eight numerical examples, both linear and nonlinear, are presented to demonstrate the accuracy of our method. The proposed method introduces suitable base functions to calculate the approximate solutions and only requires us to deal with the linear or nonlinear systems. Thus, our method is convenient to implement. Furthermore, the numerical results show that the proposed method performs better compared to the existing ones. Full article

Introduction: To promote optimal healthcare delivery, safeguarding older adults from the risks associated with inappropriate medication use is paramount. Objective: This study aims to evaluate the effectiveness of implementing the Qatar Tool for Reducing Inappropriate Medication (QTRIM) in ambulatory older adults to enhance medication safety. Method: The QTRIM was developed by an expert consensus panel using the Beers Criteria and contained a list of potentially inappropriate medications (PIMs) based on the local formulary. Using quality improvement methodology, it was piloted and implemented in two outpatient pharmacy settings serving geriatric medicine and dermatology clinics at Rumailah Hospital, Qatar. Key performance indicators (KPIs) using implementation documentation as a process measure and the percentage reduction in PIM prescriptions as an outcome measure were assessed before and after QTRIM implementation. This study was conducted between July 2022 and September 2023. Results: In the outpatient department (OPD) geriatric pharmacy, the prescription rate of PIMs was reduced from an average of 1.2 ± 0.7 PIMs per 1000 orders in 2022 to an average of 0.8 ± 0.2 PIMs per 1000 orders in 2023. In the OPD geriatric pharmacy, the results showed a 66.6% reduction in tricyclic antidepressants (TCAs) (from 30 to 10), a reduction in first-generation antihistamines by 51.7% (29 to 14), and muscle relaxants by 33.3% (36 to 24). While in dermatology, the older adult prescription rate of PIMs was reduced from an average of 8 ± 3 PIMs per 1000 orders in 2022 to a rate of 5 ± 3 PIMs per 1000 orders in 2023; the most PIM reductions were (49.4%) in antihistamines (from 89 to 45), while muscle relaxants and TCAs showed a minimal reduction. Conclusions: Implementing QTRIM with pharmacy documentation monitoring markedly reduced the PIMs dispensed from two specialized outpatient pharmacies serving older adults. It may be a promising effective strategy to enhance medication safety in outpatient pharmacy settings. Full article

In this study, the friction factor of a turbulent pipe flow for dried rice malt extract solutions was experimentally reduced to that of a Newtonian fluid. The friction factor was measured for four types of solutions at different culture times and concentrations. The results indicate that the experimental data points of the test solutions diverged from the maximum drag reduction asymptote at and above Re√f ≅ 200~250 and aligned parallel to those of Newtonian fluids. This drag reduction phenomenon differed from that observed in artificial high-molecular-weight polymer solutions, called Type A drag reduction, in which the drag reduction level is dependent on the Reynolds number in the intermediate region. This is classified as a Type B drag reduction phenomenon in biopolymer solutions and fine solid particle suspensions. The order of drag reduction corresponded to approximately 5–50 ppm xanthan gum solutions, as reported previously. Furthermore, the velocity profile in a turbulent pipe flow was predicted using a semi-theoretical equation in which the friction factors were determined using the difference between the experimental results of the tested solutions and Newtonian fluids. The results indicate considerable thickening of the viscous sublayer in the turbulent pipe flow of the test solutions compared with that of Newtonian fluids. Full article

Photocatalytic technology, which is regarded as a green route to transform solar energy into chemical fuels, plays an important role in the fields of energy and environmental protection. An emerging S-scheme heterojunction with the tightly coupled interface, whose photocatalytic efficiency exceeds those of conventional type II and Z-scheme photocatalysts, has received much attention due to its rapid charge carrier separation and strong redox capacity. This review provides a systematic description of S-scheme heterojunction in the photocatalysis, including its development, reaction mechanisms, preparation, and characterization methods. In addition, S-scheme photocatalysts for CO₂ reduction are described in detail by categorizing them as 0D/1D, 0D/2D, 0D/3D, 2D/2D, and 2D/3D. Finally, some defects of S-scheme heterojunctions are pointed out, and the future development of S-scheme heterojunctions is proposed. Full article

In wine technology, the on-line measurement of redox potential is a fast, accurate, and reliable measurement that provides insight into the metabolism of Saccharomyces cerevisiae, its microbial activity, and the oxidation and reduction state of wine, as well as insight into its quality and stability. The significance of the redox potential measurement and control in wine technology as well as the maintenance and regulation of fermentation redox potential using temperature and carbon dioxide fluxes are discussed. Redox potential levels from Eh 100 to 180 mV are typical for non-oxidized wine that is bottling-ready, while levels of Eh 270 to 460 mV represent oxidized wines with typical failures. The relevance of redox potential measurement during the 2-year maturation of Blau Fränkisch wine in 225 L oak barrels at six levels at a temperature 15 °C is presented. The measurement of the redox potential, expressing heterogeneity in redox layers during wine maturation in oak barrels, is represented in various oxido-reductive fermentation zones. On the contrary, the end of the maturation process is indicated by the homogeneity of redox zones, where the matured wine shows no differences in redox measurement on all levels. Using redox potential as a key scale-up criteria ensures comparable and reproducible amounts of the final product even in geometrically non-similar fermenter systems. Full article

Simple and efficient sample pretreatment methods are important for analysis and detection of chemical warfare agents (CWAs) in environmental and biological samples. Despite many commercial materials or reagents that have been already applied in sample preparation, such as SPE columns, few materials with specificity have been utilized for purification or enrichment. In this study, ionic magnetic mesoporous nanomaterials such as poly(4-VB)@M-MSNs (magnetic mesoporous silicon nanoparticles modified by 4-vinyl benzene sulfonic acid) and Co²⁺@M-MSNs (magnetic mesoporous silicon nanoparticles modified by cobalt ions) with high absorptivity for ethanol amines (EAs, nitrogen mustard degradation products) and cyanide were successfully synthesized. The special nanomaterials were obtained by modification of magnetic mesoporous particles prepared based on co-precipitation using -SO₃H and Co²⁺. The materials were fully characterized in terms of their composition and structure. The results indicated that poly(4-VB)@M-MSNs or Co²⁺@M-MSNs had an unambiguous core-shell structure with a BET of 341.7 m²·g⁻¹ and a saturation magnetization intensity of 60.66 emu·g⁻¹ which indicated the good thermal stability. Poly(4-VB)@M-MSNs showed selective adsorption for EAs while the Co²⁺@M-MSNs were for cyanide, respectively. The adsorption capacity quickly reached the adsorption equilibrium within the 90 s. The saturated adsorption amounts were MDEA = 35.83 mg·g⁻¹, EDEA = 35.00 mg·g⁻¹, TEA = 17.90 mg·g⁻¹ and CN⁻= 31.48 mg·g⁻¹, respectively. Meanwhile, the adsorption capacities could be maintained at 50–70% after three adsorption–desorption cycles. The adsorption isotherms were confirmed as the Langmuir equation and the Freundlich equation, respectively, and the adsorption mechanism was determined by DFT calculation. The adsorbents were applied for enrichment of targets in actual samples, which showed great potential for the verification of chemical weapons and the destruction of toxic chemicals. Full article

The marine environment provides a rich source of distinct creatures containing potentially revolutionary bioactive chemicals. One of these organisms is Caulerpa racemosa, a type of green algae known as green seaweed, seagrapes, or green caviar. This organism stands out because it has great promise for use in medicine, especially in the study of cancer. Through the utilization of computational modeling (in silico) and cellular laboratory experiments (in vitro), the chemical components included in the green seaweed C. racemosa were effectively analyzed, uncovering its capability to treat non-small cell lung cancer (NSCLC). The study specifically emphasized blocking SRC, STAT3, PIK3CA, MAPK1, EGFR, and JAK1 using molecular docking and in vitro. These proteins play a crucial role in the EGFR Tyrosine Kinase Inhibitor Resistance pathway in NSCLC. The chemical Caulersin (C2) included in C. racemosa extract (CRE) has been identified as a potent and effective agent in fighting against non-small cell lung cancer (NSCLC), both in silico and in vitro. CRE and C2 showed a level of inhibition similar to that of osimertinib (positive control/NSCLC drug). Full article

The application of drones to assist with healthcare delivery has grown rapidly over the last decade. This industry is supported by a growing research field, and we have undertaken a systematic review of the published literature. Web-based searches returned 290 relevant manuscripts published between 2010 and 2024. We applied Topic Modelling to this corpus of literature, which examines word association and connectedness within the research papers. The modelling identified two emerging research themes with little connection between them: those who used drones to deliver time-critical medical items and those who used drones to deliver non-time-critical medical items. The former was in response to medical emergencies, while the latter was for enhancing resilience in the healthcare supply chain. The topics within these research themes exhibited notable differences. The delivery of time-critical medical items theme comprised the topics of ‘Emergency Response’, ‘Defibrillator and Organ Delivery’, and ‘Search and Rescue’, whilst non-time-critical delivery researched the topics of ‘Supply Chain Optimisation’ and ‘Cost-Effectiveness’, ‘Overcoming Remoteness’, and ‘Pandemic Response’. Research on ‘Engineering and Design Considerations’ and ‘Ethical and Social Considerations’ cut across both research themes. We undertook further analysis to assess research topic alignment and identify knowledge gaps. We found that efforts are needed to establish a more standardised terminology for better alignment across the two emerging research themes. Future studies should focus on evaluating the impact of drone delivery on patient health using systematic methods. Additionally, exploring the economic viability of drone-based health services and addressing regulatory barriers are crucial for efficient and effective drone deployment in healthcare delivery systems. Full article

Phenylalanine ammonia lyase (PAL) is a key enzyme regulating the biosynthesis of the compounds of the phenylpropanoid pathway. This study aimed to isolate and characterize PAL genes from Ferula pseudalliacea Rech.f. (Apiales: Apiaceae) to better understand the regulation of metabolite production. Three PAL gene isoforms (FpPAL1-3) were identified and cloned using the 3′-RACE technique and confirmed by sequencing. Bioinformatics analysis revealed important structural features, such as phosphorylation sites, physicochemical properties, and evolutionary relationships. Expression analysis by qPCR demonstrated the differential transcription profiles of each FpPAL isoform across roots, stems, leaves, flowers, and seeds. FpPAL1 showed the highest expression in stems, FpPAL2 in roots and flowers, and FpPAL3 in flowers. The presence of three isoforms of PAL in F. pseudalliacea, along with the diversity of PAL genes and their tissue-specific expression profiles, suggests that complex modes of regulation exist for phenylpropanoid biosynthesis in this important medicinal plant. The predicted interaction network revealed associations with key metabolic pathways, emphasizing the multifaceted roles of these PAL genes. In silico biochemical analyses revealed the hydrophilicity of the FpPAL isozyme; however, further analysis of substrate specificity and enzyme kinetics can clarify the specific role of each FpPAL isozyme. These comprehensive results increase the understanding of PAL genes in F. pseudalliacea, helping to characterize their contributions to secondary metabolite biosynthesis. Full article

Polymers have a wide range of applications depending on their composition, size, and architecture. Varying any of these three characteristics can greatly impact the resulting chemical, physical, and mechanical properties. While many techniques are available to determine polymer composition and size, determining the exact polymer architecture is more challenging. Herein, tandem mass spectrometry (MS/MS) and ion mobility mass spectrometry (IM-MS) methods are utilized to derive crucial architectural information about dithiol-yne comb polymers. Based on their unique fragmentation products and IM drift times, dithiol-yne oligomers with distinct architectures were successfully differentiated and characterized. Additionally, experimental collision cross-sections (Ω) derived via IM-MS were compared to theoretically extracted Ω values from molecular dynamics simulated structures to deduce the architectural motif of these comb oligomers. Overall, this work demonstrates the benefits of combining various mass spectrometry techniques in order to gain a complete understanding of a complex polymer mixture. Full article

Enhancing human–robot interaction has been a primary focus in robotic gait assistance, with a thorough understanding of human motion being crucial for personalizing gait assistance. Traditional gait trajectory references from Clinical Gait Analysis (CGA) face limitations due to their inability to account for individual variability. Recent advancements in gait pattern generators, integrating regression models and Artificial Neural Network (ANN) techniques, have aimed at providing more personalized and dynamically adaptable solutions. This article introduces a novel approach that expands regression and ANN applications beyond mere angular estimations to include three-dimensional spatial predictions. Unlike previous methods, our approach provides comprehensive spatial trajectories for hip, knee and ankle tailored to individual kinematics, significantly enhancing end-effector rehabilitation robotic devices. Our models achieve state-of-the-art accuracy: overall RMSE of 13.40 mm and a correlation coefficient of 0.92 for the regression model, and RMSE of 12.57 mm and a correlation of 0.99 for the Long Short-Term Memory (LSTM) model. These advancements underscore the potential of these models to offer more personalized gait trajectory assistance, improving human–robot interactions. Full article