Multiple Conditions Research Articles

Entangled Illnesses: Embodied Experiences of Managing Multimorbidity.

Multimorbidity, meaning multiple long-term conditions impacting a person's health, has become a rising societal and public health issue. The article contributes to the sociological study of chronic illness and multimorbidity by analysing how the blurriness of illnesses and entanglement of symptoms in multimorbidity is experienced and negotiated by people with coexisting chronic conditions. Drawing on qualitative interviews with people who live with endometriosis, fibromyalgia or hormonal migraine in Finland, we show how people with multiple chronic conditions distinguish between evolving symptoms based on past embodied experiences to make decisions about how to best manage their health. We argue that coexisting illnesses become entangled in ambiguous and open-ended ways, which, if left unaddressed, complicates treatment. Our analysis of illness experiences is aligned with the growing body of literature that argues that the single-disease model underlying healthcare systems fails to address the needs of patients living with multiple chronic conditions. Our emphasis on evolving entanglements between illnesses and the blurriness of conditions makes visible crucial discrepancies between lived illness and existing biomedical models and healthcare structures.

CTNet: Improving the non-stationary predictive ability of remaining useful life of aero-engine under multiple time-varying operating conditions

Remaining useful life (RUL) estimation has been widely studied in prognostics and health management. Multiple time-varying operating conditions explicitly influence the measured performance parameters of the aero-engine, which results in non-stationarity and impedes the predictive ability of deep learning models. Previous data-driven studies primarily ignore the causality between operating condition descriptors and measured performance parameters, which is inconsistent with practical aero-engine engineering applications. To address this issue, we propose a causality Transformer network (CTNet), which improves the prediction stability of non-stationary series under multiple operating conditions. First, a novel graph structure is used to capture the connectivity relationship between operating condition descriptors and measured sensor nodes. Then the causality attention is proposed to inject additional causality information into the self-attention module without affecting the similarity computations of query and key values within the window. The causality attention can generate distinguishable attention for operating conditions, which properly release the predictive potential for non-stationary series. Extensive experiments are performed on public datasets (CMAPSS, N-CMAPSS), showing that CTNet outperforms existing state-of-the-art methods. We have also conducted experiments on the real-world quick access recorder (QAR) data, which validates the performance of the proposed model in perceiving time-varying operating conditions.

Metal coordination bond and rough interface enhanced triboelectric nanogenerator aiming for multiple complex conditions

Triboelectric nanogenerator (TENG) is widely used in the fields of sustainable green energy harvesting, self-powered motion parameter and tactile sensing, However, it still fails to meet the requirements under various complex conditions, such as low temperatures, self healing after destruction, punching, long-term placement, soaking in acid or alkali solution, scorch, continuous work. Herein, based on metal coordination, Zr4+ ions are introduced to enhance the first network k-carrageenan (k-CG) for achieving double enhancement in mechanics and electricity of the gel electrode layer, poly (N-hydroxyl acrylamide)/k-CG (PKZ) double network organic conductive gel enhanced by multiple hydrogen bonds and metal coordination bond is designed, and the gel exhibits high tensile strength, high conductivity, fast self-recovery, excellent self-repairing and low-temperature resistance. Based on simple sandpaper templates with different mesh numbers Ecoflex film with rough surfaces is designed for efficient triboelectric contact interface, and TENG with PKZ double network organic conductive gel as electrode layer is constructed, and possesses excellent resistant to multiple complex conditions. With high short-circuit current, open-circuit voltage and output power, the TENG is capable of powering electronic devices, and it can also be sensitive and stable sensing in writing recognition, real-time monitoring of motion parameters involving acceleration, speed and distance. The TENG is stable and reliable for sustainable green energy harvesting, motion parameter and tactile sensing in multiple complex environments. Thus, we provide novel ideas for designing energy harvesting and sensing for future wearable electronics under multiple complex conditions.

Anthropometric and Sociodemographic Correlates of Dental Caries and Gingival Health in Children With Special Healthcare Needs at a Saudi Tertiary Care Hospital.

To evaluate the impact of anthropometric and sociodemographic factors on dental caries and gingival health among children with special healthcare needs (SHCN). This cross-sectional study involved 108 children, aged 4-14 years, with congenital heart disease, childhood cancer, bleeding disorders, various syndromes, and multiple conditions. Caregivers completed a sociodemographic questionnaire, and children underwent dental examinations to assess caries, gingival health, and oral hygiene. Anthropometric measures-weight, height, and body mass index (BMI)-were obtained and categorized into percentiles (<10, 10-90, >90) using age- and gender-specific growth charts. Dental caries was highly prevalent (93.5%), with a mean dmft/DMFT value of 7.70 (SD ± 5.22). The mean gingival index was 0.43 (SD ± 0.52). Total dmft/DMFT values were significantly higher in children ≤6 years and those with fathers of lower educational levels. Poor oral hygiene was a strong predictor of adverse outcomes for both caries and gingival health. Higher gingival indices correlated with children in the >90th weight percentile. The findings highlight the need for comprehensive oral health interventions that integrate meticulous oral hygiene, paternal education, and holistic growth monitoring beyond BMI. The results support implementing a 3-month recall program for professional dental care, combined with individualized oral hygiene instruction for caregivers. This approach is particularly crucial for the younger age group (≤6 years) where targeted early intervention could significantly reduce caries risk.

The polarity of high-definition transcranial direct current stimulation affects the planning and execution of movement sequences.

Noninvasive brain stimulation of the primary motor cortex has been shown to alter therapeutic outcomes in stroke and other neurological conditions, but the precise mechanisms remain poorly understood. Determining the impact of such neurostimulation on the neural processing supporting motor control is a critical step toward further harnessing its therapeutic potential in multiple neurological conditions affecting the motor system. Herein, we leverage the excellent spatio-temporal precision of magnetoencephalographic (MEG) imaging to identify the spectral, spatial, and temporal effects of high-definition transcranial direct current stimulation (HD-tDCS) on the neural responses supporting motor control. Participants (N = 67) completed three HD-tDCS visits (anode, cathode, sham), with each involving 20 minutes of left primary motor cortex stimulation and performance of a simple/complex motor sequencing task during MEG. Whole-brain statistical analyses of beta oscillatory responses revealed stimulation-by-task interaction effects in the left primary motor cortex, right occipitotemporal, and the right dorsolateral prefrontal cortices. Broadly, anodal stimulation induced significantly stronger beta oscillatory responses in these regions during simple movement sequences, while neural responses to complex sequences were not affected by stimulation. En masse, these data suggest that the beta oscillations serving motor planning (i.e., pre-movement) are particularly sensitive to the polarity of noninvasive stimulation and that the impact varies based on the difficulty of the movement sequence.

Intersecting Structural and Psychosocial Conditions: Investigating Injection Drug Use and HIV Among Transgender Women.

Transgender women continue to face a significant burden of health disparities with HIV infection as a critical public health concern. Substance use is higher among transgender women than among cisgender women. However, little is known about transgender women who inject drugs and risk for HIV in the United States. The objectives were to explore HIV prevalence, injection-related behaviors, and HIV prevention and care outcomes among transgender women who inject drugs and to compare transgender women with a general sample of persons who inject drugs. Participants from the National HIV Behavioral Surveillance were recruited through respondent-driven sampling, interviewed, and tested for HIV infection in 2019-2020. Log-linked Poisson regression models were used to test for associations between injection drug use and selected characteristics. Among 1561 transgender women, 7% injected drugs in the past 12 months. HIV prevalence was higher among transgender women who inject (adjusted prevalence ratio = 1.5, 95% confidence interval: 1.2 to 1.8) than among those who do not. Multiple psychosocial conditions were associated with injection drug use. Among transgender women with HIV, those who inject were less likely to take antiretroviral therapy (adjusted prevalence ratio = 0.8, 95% confidence interval: 0.7 to 1.0) than those who do not. Methamphetamine was the most commonly injected drug (67%); most accessed a syringe services program (66%). Transgender women who inject have substantial challenges related to health outcomes including high HIV prevalence and exposure to psychosocial conditions, such as homelessness, incarceration, and exchange sex, that may exacerbate risks associated with injection drug use. This population may benefit from increased access to nonjudgmental and culturally competent harm reduction services.

Aeroelastic flutter correlation analysis and structure optimization of wind turbine blades under multiple operating conditions based on aerodynamic damping

Aeroelastic flutter correlation analysis and structure optimization of wind turbine blades under multiple operating conditions based on aerodynamic damping

Behavior of simple closed ecological systems; lower nutrient concentrations allow longer persistence of grazer populations.

We expect to develop self-sustaining extraterrestrial colonies, and they will approach being closed ecological systems. Using simple closed ecosystems containing Daphnia magna, three species of algae, and microbes, we tested multiple conditions to study long-term organism survival, which is only possible with adequate nutrient recycling. Closed and open systems behaved differently from one another at high nitrate concentrations; in closed systems, the animals were dead by day 14; in open systems, the Daphnia populations persisted beyond 273 days. Daphnia deaths were associated with increased pH and O2 caused by greater algal photosynthesis and the lack of exchange with the atmosphere. Replicate variability that used small Daphnia suggested that inadequate grazing capability allowed algae to create conditions unfavorable to Daphnia survival. Over months, algal and Daphnia abundance decreased, presumably because of inadequate nutrient recycling; these populations increased temporarily after the addition of nutrients. The addition of natural lake organisms did not increase the nutrient-recycling capabilities of the systems. Understanding the mechanisms of closed systems will be useful in implementing biological processes in managing life support systems.

Dual data fusion fault diagnosis of transmission system based on entropy weighted multi-representation DS evidence theory and GCN

Power transmission reliability of drivelines guarantees fast maneuverability of heavy vehicles. During health monitoring, multi-sensor data fusion technology has been widely used in the improvement of fault diagnosis accuracy of long-link multi-structure drivelines. However, in multi-sensor fusion and joint fault diagnosis scenarios where multiple conditions coexist, it is still challenging to fuse multi-sensor data and extract generalized fault intrinsic features for any combination of operating conditions under multi-sensor monitoring. In this paper, a dual fusion graph convolutional network (DFGCN) is proposed for multi-sensor-multi-condition fault diagnosis of the transmission system. First, considering the data structure and the correlation of different sensors, DFGCN constructs multi-sensor intrinsic links synchronously from the data and feature levels by using multi-branch parallel GCN. Second, considering the susceptibility to over-confidence when the feature space of multi-condition data is inconsistent, an entropy-weighted multi-representation Dempster-Shafer (EWMR-DS) evidence theory fusion strategy is designed to extract the condition-shared features by increasing the label space diversity. Finally, an end-to-end lightweight diagnosis framework is scalable to multi-sensor and multi-working conditions in engineering practice, and the dual information fusion improves the fusion efficiency of fine-grained features with distributional differences. Using experimental datasets collected from two typical transmission fault test benches, the effectiveness of the proposed DFGCN method in multi-sensor-multi-condition scenarios is verified. The results indicate that DFGCN achieves an average diagnostic accuracy of more than 99.7% and superior noise resistance under different degrees of environmental noise.

Characterization of Optokinetic Nystagmus in Healthy Participants With a Novel Oculography Device.

To develop a proof-of-concept smart-phone-based eye-tracking algorithm to assess non-pathologic optokinetic (OKN) nystagmus in healthy participants. Current videonystagmography (VNG) is typically restricted to in-office use, and advances in portable vestibular diagnostics would yield immense public health benefits. Prospective cohort study. Tertiary academic medical center. Healthy participants (n = 39) without dizziness or vertigo were recruited. A smart-phone attached to a custom head stabilization device illuminated by a white LED circuit was used to record nystagmus induced with a 30 frames per second OKN stimulus over a 60-second period. A centroid tracking algorithm was created to detect slow-phase velocity (SPV) of horizontal nystagmus in a diverse subject cohort in a variety of lighting conditions. Nystagmus recordings were compared to those obtained with a standard VNG system. Non-pathologic nystagmus from an OKN stimulus was measured across multiple lighting conditions, with high signal-to-noise ratios (SNR) and mean SPV 22.13 ± 5.26°/s. Nystagmus SPV was not significantly different between the device and standard VNG system (t = -0.5, P = .6). Lighting conditions produced SNRs of 57.30 (ideal), 50.59 (backlit), 51.33 (side-lit), 49.28 (dark), 54.52 (outdoor lighting). We demonstrate the feasibility of a novel portable oculography system in the detection of non-pathologic nystagmus in healthy subjects. Future applications of this system include: (1) to obtain real-time measurements of nystagmus during an acute vertigo attack; (2) to test patients unable or unwilling to present to a specialized vestibular laboratory; (3) to efficiently repeat testing overtime; (4) to improve accessibility of vestibular testing.

Topical review: family psychosocial risk screening and social determinants of health assessment.

Social-ecological factors are highly congruent with social determinants of health (SDOH): Economic Stability; Educational Access/Quality; Healthcare Access/Quality; Neighborhood/Built Environment; and Social/Community Context. In this topical review, the correspondence of social-ecological theory with SDOH and assessment approaches is reviewed. The Psychosocial Assessment Tool (PAT) is used to show how existing tools may facilitate SDOH screening. SDOH are defined, and their link to pediatric health outcomes is presented, followed by a review of the social-ecological model. Feasible, valid, and actionable approaches to assessment of social ecology and SDOH are presented with a focus on the PAT, a brief caregiver report screener based on social-ecological theory, validated in English, Spanish, and in multiple conditions and adapted/translated internationally. Multidisciplinary healthcare providers (n = 25) completed an online survey, indicating whether each PAT item fit into SDOH categories. Despite different approaches to assessing SDOH, there are few feasible and evidence-based approaches. Most PAT items (78%) were consistent with one of the SDOH categories by the majority of raters. PAT items corresponded to all five SDOH categories. Some items about child behavior and family were not categorized as an SDOH, reflecting the broader context of screening with the PAT. The assessment of SDOH is a priority, but approaches to assessment and linking outcomes to intervention remain underdeveloped. As an evidence-based screener in pediatric healthcare, based on social-ecological and public health models, the PAT may provide a means of identifying relevant SDOH in pediatric practice.

Facet-controlled electrosynthesis of nanoparticles by combinatorial screening in scanning electrochemical cell microscopy.

Controlled synthesis of faceted nanoparticles on surfaces without explicit use of ligands has gained attention due to their promising applications in electrocatalysis and chemical sensing. Electrodeposition is a desirable method; however, precise control over their size, spatial distribution, and morphology requires extensive optimization. Here, we report the spatially resolved synthesis of shape-controlled Pt nanoparticles and fast screening of synthesis conditions in scanning electrochemical cell microscopy (SECCM) with pulse potentials. The screening is performed on isolated ∼μm2 areas in SECCM, enabling multiple experimental conditions to be evaluated in a single mapping experiment. The screening reveals that the formation of (100) facets in Pt nanoparticles is sensitive to the upper and lower potential limits of the square-wave potential pulse. The facet selectivity is attributed to a facet-dependent migration effect influenced by the concurrent hydrogen evolution reaction during Pt deposition. Moreover, the density and size of nanoparticles can be controlled. This approach offers a pathway toward automated synthesis and characterization of faceted metallic nanoparticles, providing opportunities for advancements in electrocatalysis and sensor development.

Assessing the role of genotype by environment interaction as determinants of maize grain yield and lodging resistance

BackgroundThe development of superior summer maize hybrids with high-yield potential and essential agronomic traits, such as resistance to lodging, is crucial for ensuring the sustainability of maize cultivation. However, the task of identifying and breeding genotypes that exhibit exceptional performance and stability across multiple environment conditions, while considering a wide range of traits, is challenging. Given the backdrop of global climate change, understanding which climate variables and soil properties most significantly impact environmental similarity is essential for selecting hybrids with improved adaptability to regions with diverse climatic and soil conditions. This study aimed to integrate envirotyping techniques (ETs) with a multi-trait selection approach to carry out a comprehensive evaluation of maize genotypes for performance and stability.ResultsThe grain yields of 13 maize hybrids, along with their four critical agronomic parameters, were assessed in the Huang-Huai-Hai Plain of China across 40 locations in eight provinces. By considering 20 years of climatic factors and soil covariates, these 40 locations were divided into six mega-environments (MEs) based on similar long-term weather patterns and soil characteristics. Additive main effects and multiplicative interaction (AMMI) analyses revealed that genotype (G), environment (E), and the GxE interaction had significant effects on all agronomic parameters (P < 0.001). The mean performance and stability of the genotypes in each mega-environment were assessed, allowing for the identification of superior hybrids using the multi-trait stability index (MTSI). In two of the MEs (ME2 and ME3), only two hybrids, HY321 and HY9112, were selected concurrently.ConclusionOverall, this study provides valuable insights into the effects of ETs on maize hybrids and enhances our understanding of GxE interactions in multi-environment trials. This understanding is essential for improving maize cultivation practices and breeding program in diverse environments.

Numerical Analysis of Heat Transfer and Flow Characteristics of Jeffrey Nanofluid Over Stretched Surfaces With MHD and Slip Effects

ABSTRACTThis study employs the Jeffrey fluid model to investigate stress relaxation in non‐Newtonian fluids, offering a more precise representation than conventional viscous models. It explores the influence of multiple slip conditions and magnetohydrodynamics (MHD) on Jeffrey fluid flow and heat transfer across irregular surfaces. Additionally, the impact of thermal radiation and internal heat sources on heat transfer is examined, essential for a comprehensive understanding of the system's thermal dynamics. Using the Buongiorno model, the diffusion and thermophoresis of nanoparticles within the flow are analyzed. Nonlinear coupled governing equations covering flow dynamics, heat transfer, and nanoparticle transport are transformed into ordinary differential equations (ODEs) through similarity transformations and solved numerically using the Runge–Kutta fourth‐order (RK4) method combined with shooting techniques. Results indicate significant effects of physical parameters on temperature, velocity, and mass profiles: a 20% decrease in temperature profiles with an increase in the dimensionless thermal slip coefficient from 0.1 to 0.5 and a 15% reduction in velocity profiles from a 0.1 unit increase in the magnetic parameter . The study also quantifies mass and heat transfer rates to elucidate their impacts. These findings have profound implications for engineering applications involving non‐Newtonian and nanofluids in complex geometrical configurations.

MATRIX: a platform for cultivation profiling and bioactive discovery in natural product research

The MATRIX protocol presents a novel miniaturized 24-well plate approach for microbial cultivation profiling, enabling the efficient and parallel assessment of microbial metabolite production. This method integrates a media MATRIX within a microbioreactor to facilitate the creation of diverse growth conditions for microbial cultivation. The 24-well format supports the simultaneous study of multiple microbial strains and conditions, allowing the discovery of novel bioactive compounds. By employing a variety of media compositions and cultivations, MATRIX enhances the understanding of microbial metabolic pathways and interactions. This protocol provides a robust platform for natural product discovery, microbial ecology studies, and drug development, showcasing its potential to uncover new natural products and other valuable bioactives. The MATRIX approach offers a resource-efficient platform for microbial biodiscovery, contributing significantly to natural product research and drug development.

Multi-Year Multi-Indication Agreements for Supporting Patient Access to Oncology Medicines with Multiple Indications: An Experimental Approach or Here to Stay?

Over the past decade, an increasing number of oncology medicines with indications for multiple cancer types have been delivering benefits to patients. To ensure these products reach patients, pricing and reimbursement systems have had to adapt to address the value assessment, time-to-access, affordability, and budget uncertainty challenges this creates. Multi-year multi-indication (MYMI) agreements are made between payers and manufacturers and aim to ensure that patients have access to effective treatments for multiple conditions over time; this includes future indications of the treatment. MYMI agreements were first introduced as a solution in several European countries in 2017, offering a range of potential benefits. MYMI agreements have since demonstrated evidence of success in mitigating many of the challenges associated with assessing and reimbursing multi-indication products, time-to-patient access, and budget impact. The purpose of this article is to discuss the recent progress made with MYMI implementation across countries and provide a view on whether it is delivering for patients, healthcare systems, and innovators. We find that MYMI is not a one-size-fits-all solution but a model that needs to be adapted to the unique needs and characteristics of different healthcare systems. The intended benefits of MYMI to patients (speed and breadth of access to new indications) appear to have been realised in practice in some countries but not all. However, the administrative burden associated with MYMI implementation in some countries risks jeopardising the intended efficiency benefits. Payers and policymakers can also benefit from improved budget predictability and sustainability.

Semi-Synthesis of Dimeric Cannabidiol Derivatives and Evaluation of their Affinity at Neurological Targets.

Cannabidiol (CBD) is a natural product associated with a wide range of biological and therapeutic activities. Despite the widespread cultural acceptance of CBD as a medicinal agent, much remains to be determined regarding its precise mechanism(s) of action in treating multiple conditions. CBD has been shown to promiscuously interact with several neurological targets with varying affinities. To expand the chemical space of phytocannabinoids and develop novel chemical compounds, we have designed and synthesized a series of CBD and Δ8-THC homodimers, and CBD/Δ8-THC heterodimers. The capacity of the dimers to interact with a panel of CNS targets was explored along with the capacity to activate CB1 receptors, as measured by a GIRK channel activation assay. In the panel screen, the dimers were shown to be generally more active toward 5-HT2B and sigma 2 receptors with a range of Ki values from 0.6 to 8.7 μM. These findings provide early evidence that this new class of dimers can serve as novel chemical entities to explore receptor function and the potential for these dimers to have bivalent, bitopic, or dual mechanisms of action.

Efficacy and Safety of Dupilumab Across Different Th2-Type-Mediated Diseases: A Real-Life Preliminary Experience

Background: Dupilumab, a fully human monoclonal antibody targeting the interleukin (IL)-4/IL-13 pathway, is able to dampen T helper (Th)2-mediated inflammation in several conditions characterized by this particular type of phlogosis. The aim of this study was to review the efficacy and safety of dupilumab treatment in conditions underpinned by Th2-type inflammation in a cohort of real-world patients referred to our outpatient clinic. Methods: Data from all patients with atopic dermatitis, chronic rhinosinusitis with nasal polyps, asthma, and other Th2-type-mediated inflammatory conditions treated with dupilumab were retrospectively reviewed. Results: Twenty-two patients were included in the study: 14 with atopic dermatitis, 5 with chronic rhinosinusitis with nasal polyps, 2 with asthma, and 1 with prurigo nodularis; some of the patients had more than one atopic condition. A complete response was observed in 13 out of 22 patients (59.1%); when partial responses were included in the analysis, the overall response rate was 86.4%. No adverse events were recorded, either locally or systemically. Total IgE levels dropped in all patients, in some cases reaching values close to those typically observed in nonatopic subjects. When eosinophilia was present at baseline, this also normalized during dupilumab treatment. Conclusions: Dupilumab was safe and effective across multiple conditions driven by Th2-type chronic inflammation; effective interference with the Th2-type pathway was inferred by the progressive reduction in serum total IgE levels, which reached the normal range in a fraction of patients, and by the reduction in peripheral blood eosinophil counts. Further studies in different Th2-mediated diseases are warranted.

The Multimorbidity Questionnaire (MMQ1): English translation and validation of a Danish patient reported outcome measure for quality of life in people with multiple long-term conditions in a cross-sectional survey.

MMQ1 is a Danish-language patient-reported outcome measure (PROM) for quality of life (QOL) in people with multiple long-term conditions (MLTC). It measures needs-based QOL across six scales: Physical ability, Concerns and worries, Limitations in daily life, Social life, Personal finances and Self-image. There is currently no such measure available in English. This study aimed to translate and validate MMQ1 for use in the United Kingdom. Translation used a two-panel method (expert panel: n = 5; and lay panel: n = 6). Content validity was assessed via cognitive interviews (n = 6). A postal survey of 2,753 patients with MLTC recruited through eight GP practices in Scotland included EQ-5D-5L and ICE-CAP as comparator measures alongside MMQ1. Classical test theory psychometric analysis of survey responses followed the International Society for Quality of Life Research minimum reporting standards. Translation resulted in an English-language MMQ1 with good face validity. Cognitive interviews established good content validity. 597 survey responses were received (response rate 22%). Good internal consistency reliability and concurrent validity were demonstrated. Confirmatory factor analysis showed acceptable fit to the six-scales of MMQ1. Five of the six scales also demonstrated good discriminative ability for detecting clinically meaningful differences in QOL. However, inter-item and inter-scale correlations suggested item redundancy and scale overlap. The English-language MMQ1 demonstrated adequate psychometric properties using classical test theory. Further validation using Rasch analysis is planned, and may help optimise and abbreviate the measure. This PROM has the potential to improve the measurement of QOL in MLTC research, including trials.

Transient fluctuation prediction and control of tracked vehicle electric drive engine-generator set based on LSSVM

To address the challenges of delayed control responses and suboptimal performance due to the absence of predictive capabilities for pre-power chain speed fluctuations in the electromechanical composite transmission system of armored vehicles, a transient fluctuation prediction and control method based on the Least Squares Support Vector Machine (LSSVM) is proposed for the engine-generator set within the system. This approach leverages real-world generator data collected from actual vehicles as the training dataset to establish a data-driven model. A specific LSSVM training model is developed, with experimental data serving as the test set. Within the model's predictive framework, transient fluctuations of critical engine-generator parameters are generated in real-time under test conditions. Simulations are conducted on a test platform for the electromechanical composite transmission system, evaluating both single-generator operation and a variety of driving conditions. Comparative analysis is performed to assess the operational factors influencing system performance under single and multiple conditions, as well as the control effects of transient power chain fluctuation prediction. Under multiple-condition scenarios, the system demonstrates faster dynamic recovery in response to significant load disturbances, with voltage peak fluctuations remaining within 5 %, which meets engineering application standards. This validates the model's adaptability and generalization capability for broader use cases.