Chickpea has significant benefits as an adjuvant treatment for type 2 diabetes mellitus (T2DM). The properties of chickpea resistant starches (RSs) and their abilities to reduce T2DM symptoms and control intestinal flora were investigated. The RS content in citrate-esterified starch (CCS; 74.18%) was greater than that in pullulanase-modified starch (enzymatically debranched starch (EDS); 38.87%). Compared with those of native chickpea starch, there were noticeable changes in the granular structure and morphology of the two modified starches. The CCS showed surface cracking and aggregation. The EDS particles exhibited irregular layered structures. The expansion force of the modified starches decreased. The CCS and EDS could successfully lower blood glucose, regulate lipid metabolism, lower the levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C), reduce the expressions of interleukin-6 (IL-6) and interleuki n-10 (IL-10), and decrease diabetes-related liver damage. Moreover, the CCS and EDS altered the intestinal flora makeup in mice with T2DM. The abundance of Bacteroidota increased. Both types of chickpea RSs exhibited significant hypoglycaemic and hypolipidaemic effects, contributing to the reduction in inflammatory levels and the improvement in gut microbiota balance. Full article

In the study of biological systems, nonlinear models are commonly employed, although exact solutions are often unattainable. Therefore, it is imperative to develop techniques that offer approximate solutions. This study utilizes the Elzaki residual power series method (ERPSM) to analyze the fractional nonlinear smoking model concerning the Caputo derivative. The outcomes of the proposed technique exhibit good agreement with the Laplace decomposition method, demonstrating that our technique is an excellent alternative to various series solution methods. Our approach utilizes the simple limit principle at zero, making it the easiest way to extract series solutions, while variational iteration, Adomian decomposition, and homotopy perturbation methods require integration. Moreover, our technique is also superior to the residual method by eliminating the need for derivatives, as fractional integration and differentiation are particularly challenging in fractional contexts. Significantly, our technique is simpler than other series solution techniques by not relying on Adomian’s and He’s polynomials, thereby offering a more efficient way of solving nonlinear problems. Full article

In this article, rotor designs utilizing assisted-poles are investigated for a high-torque density spoke-type permanent magnet synchronous machine (PMSM) with fractional slot concentrated winding (FSCW) to explore the rich air-gap magnetic field harmonics and torque generation mechanism. Due to their higher average torque output, spoke-type PMSMs with FSCW are increasingly used in high-torque density applications. However, slot harmonics generate torque ripples that are difficult to eliminate in FSCW spoke-type PMSMs. Removing slot harmonics from the stator or winding results in a large drop in torque since their winding factors are identical to those of the main harmonic. Therefore, rotor designs having assisted-poles (symmetrical and asymmetrical) are investigated in this work to mitigate slot harmonics and minimize torque ripples. Firstly, the air-gap flux density is analyzed for the machines having assisted-poles, and a model of interaction between the stator and rotor-MMF harmonics is created and validated through Finite element analysis (FEA) to analyze the torque production mechanism. In addition, an analytical relationship between the assisted-poles’ dimensions and the generated torque harmonics is proposed. Furthermore, a generalized torque ripple reduction concept for the FSCW spoke-type PMSM having asymmetrically designed assisted-poles is presented. The proposed design and optimization method are validated through analytical calculations and FEA simulations, and a brief comparative analysis is presented for the analyzed machine prototypes. It has been established that the machine designed by applying the proposed asymmetrical assisted-poles can achieve a reduction in torque ripples while also significantly lowering cogging torque in comparison to the conventional spoke-type PMSMs and other spoke-type PMSMs with rotor having symmetrical assisted-poles. Full article

One of the fundamental problems in the field of technological studies is to clarify the drivers and dynamics of technological evolution for sustaining industrial and economic change. This study confronts the problem by analyzing the converging technologies to explain effects on the evolutionary dynamics over time. This paper focuses on technological interaction between artificial intelligence and quantum technologies using a technometric model of technological evolution based on scientific and technological information (publications and patents). Findings show that quantum technology has a growth rate of 1.07, artificial intelligence technology has a rate of growth of 1.37, whereas the technological interaction of converging quantum and artificial intelligence technologies has an accelerated rate of growth of 1.58, higher than trends of these technologies taken individually. These findings suggest that technological interaction is one of the fundamental determinants in the rapid evolution of path-breaking technologies and disruptive innovations. The deductive implications of results about the effects of converging technologies are: (a) accelerated evolutionary growth; (b) a disproportionate (allometric) growth of patents driven by publications supporting a fast technological evolution. Our results support policy and managerial implications for the decision making of policymakers, technology analysts, and R&D managers that can direct R&D investments towards fruitful inter-relationships between radical technologies to foster scientific and technological change with positive societal and economic impacts. Full article

The advection–dispersion equation has been widely used to analyze the intermediate field mixing of pollutants in natural streams. The dispersion coefficient, manipulating the dispersion term of the advection–dispersion equation, is a crucial parameter in predicting the transport distance and contaminated area in the water body. In this study, the transverse dispersion coefficient was estimated using machine learning regression methods applied to oversampled datasets. Previous research datasets used for this estimation were biased toward width-to-depth ratio (W/H) values ≤ 50, potentially leading to inaccuracies in estimating the transverse dispersion coefficient for datasets with W/H > 50. To address this issue, four oversampling techniques were employed to augment the dataset with W/H > 50, thereby mitigating the dataset’s imbalance. The estimation results obtained from data resampling with nonlinear regression method demonstrated improved prediction accuracy compared to the pre-oversampling results. Notably, the combination of adaptive synthetic sampling (ADASYN) and eXtreme Gradient Boosting regression (XGBoost) exhibited improved accuracy compared to other combinations of oversampling techniques and nonlinear regression methods. Through the combined ADASYN–XGBoost approach, it is possible to enhance the transverse dispersion coefficient estimation performance using only two variables, W/H and bed friction effects (U/U^*), without adding channel sinuosity; this represents the effects of secondary currents. Full article

Background: Oral mucositis is a common and distressing side effect of head and neck oncology treatment. Photobiomodulation therapy can be utilized to prevent and treat oral mucositis. Its impact on salivary cytokines has yet to be thoroughly investigated. This is the first systematic review aiming to evaluate the effect of photobiomodulation on salivary cytokines in patients undergoing anticancer treatment. Methods: Numerous data resources, from the Web of Science, Embase, ScienceDirect, PubMed, Cochrane Library, and Scopus were sought. Articles published up until February 2024 were included if they met the following inclusion criteria: clinical trials reporting the effect on salivary cytokines in patients undergoing anticancer therapy. The methodological quality was assessed using several appraisal tools. Results: Four studies were deemed eligible for inclusion. All the studies were conducted in Brazil and used an InGaAlP diode laser with a wavelength of 660 nm. The included studies had a relatively low risk of bias. The head and neck cancer patients’ salivary cytokines that were assessed by the studies, along with photobiomodulation therapy, included IL-12p70, TNF-α, IL-6, IL-8, IL-10, CXCL8, and IL-1β. The results varied among the studies. Conclusions: Our results show that photobiomodulation demonstrated positive results for reducing the severity of OM in all the included studies. Among the examined salivary cytokines, IL-6 is the most relevant cytokine for oral mucositis development and severity. A variation in the cytokine levels between the studies was noted due to differences in the type of anticancer treatment and saliva sampling. Full article

Uncontrollable bleeding is recognized as the leading cause of preventable death among trauma patients. Early transfusion of blood products, especially plasma replacing crystalloid and colloid solutions, has been shown to increase survival of severely injured patients. However, the requirements for cold storage and thawing processes prior to transfusion present significant logistical challenges in prehospital and remote areas, resulting in a considerable delay in receiving thawed or liquid plasma, even in hospitals. In contrast, freeze- or spray-dried plasma, which can be massively produced, stockpiled, and stored at room temperature, is easily carried and can be reconstituted for transfusion in minutes, provides a promising alternative. Drawn from history, this paper provides a review of different forms of dried plasma with a focus on in vitro characterization of hemostatic properties, to assess the effects of the drying process, storage conditions in dry form and after reconstitution, their distinct safety and/or efficacy profiles currently in different phases of development, and to discuss the current expectations of these products in the context of recent preclinical and clinical trials. Future research directions are presented as well. Full article

A fully diagnostic MRI glioma protocol is key to monitoring therapy assessment but is time-consuming and especially challenging in critically ill and uncooperative patients. Artificial intelligence demonstrated promise in reducing scan time and improving image quality simultaneously. The purpose of this study was to investigate the diagnostic performance, the impact on acquisition acceleration, and the image quality of a deep learning optimized glioma protocol of the brain. Thirty-three patients with histologically confirmed glioblastoma underwent standardized brain tumor imaging according to the glioma consensus recommendations on a 3-Tesla MRI scanner. Conventional and deep learning-reconstructed (DLR) fluid-attenuated inversion recovery, and T2- and T1-weighted contrast-enhanced Turbo spin echo images with an improved in-plane resolution, i.e., super-resolution, were acquired. Two experienced neuroradiologists independently evaluated the image datasets for subjective image quality, diagnostic confidence, tumor conspicuity, noise levels, artifacts, and sharpness. In addition, the tumor volume was measured in the image datasets according to Response Assessment in Neuro-Oncology (RANO) 2.0, as well as compared between both imaging techniques, and various clinical–pathological parameters were determined. The average time saving of DLR sequences was 30% per MRI sequence. Simultaneously, DLR sequences showed superior overall image quality (all p < 0.001), improved tumor conspicuity and image sharpness (all p < 0.001, respectively), and less image noise (all p < 0.001), while maintaining diagnostic confidence (all p > 0.05), compared to conventional images. Regarding RANO 2.0, the volume of non-enhancing non-target lesions (p = 0.963), enhancing target lesions (p = 0.993), and enhancing non-target lesions (p = 0.951) did not differ between reconstruction types. The feasibility of the deep learning-optimized glioma protocol was demonstrated with a 30% reduction in acquisition time on average and an increased in-plane resolution. The evaluated DLR sequences improved subjective image quality and maintained diagnostic accuracy in tumor detection and tumor classification according to RANO 2.0. Full article

This paper examines the extent to which it is possible to replace conventional light commercial vehicles in the heating, ventilation and air conditioning and plumbing trade with battery electric vehicles with an unchanged usage profile. GPS trackers are used to record the position data of 22 craft vehicles with combustion engines from eleven companies over the duration of one working week. Within this paper, various assumptions (battery capacity and average consumption) are made for battery electric vehicles and the charging power on the company premises. The potential of battery electric vehicles is evaluated based on the assumption that they are charged only on company premises. Using the collected data and the assumptions made, theoretical state of charge curves are calculated for the vehicles. The driving profiles of the individual vehicles differ greatly, and the suitability of battery electric vehicles should be considered individually. Battery capacity, vehicle energy consumption and charging power at the company have a substantial influence on the suitability of battery electric vehicles. Furthermore, there are differences between vehicles that can charge on the company premises at night and those that cannot or can only do so on some days. Full article

This study aimed to assess the antioxidant capacity of lemon flavonoid extract Eriomin^® (LE) and its impact on cholesterol metabolism in the context of healthy aging. We orally treated 24-month-old male Wistar rats with an LE (40 mg/kg) suspended in 0.3 mL of sunflower oil. At the same time, control groups received an equal volume of sunflower oil (CON) or remained untreated (ICON) daily for 4 weeks. We examined LE’s effects on superoxide dismutase and catalase- and glutathione-related enzyme activities, the concentration of lipid peroxides and protein carbonyls, total oxidant status (TOS) and antioxidant status (TAS), and oxidative stress index (OSI) in the liver, jejunum, and ileum. We also measured total cholesterol, its biosynthetic precursors (lanosterol, lathosterol, desmosterol), its degradation products (bile acid precursors) in the serum, liver, jejunum, and ileum, and serum phytosterols (intestinal absorption markers). LE reduced TOS, TAS, and OSI (p < 0.05) compared with control values, indicating its consistent antioxidant action in all examined organs. LE lowered hepatic desmosterol (p < 0.05) while also reducing 7α- and 24-hydroxycholesterol levels in the liver and ileum (p < 0.01). Serum cholesterol, hepatic gene expression, and the immunostaining intensity of CYP7A1 were unchanged. In conclusion, LE exerted non-enzymatic antioxidant effects and reduced cholesterol degradation, reducing its biosynthesis products, thereby maintaining serum cholesterol levels. Full article

In system processing, video inevitably suffers from distortion, which leads to quality degradation and affects the user experience. Therefore, it is of great importance to design an accurate and effective objective video quality assessment (VQA) method. In this paper, by considering the multi-dimensional characteristics for video and visual perceptual mechanism, a two-stream convolutional network for VQA is proposed based on spatial–temporal analysis, named TSCNN-VQA. Specifically, for feature extraction, TSCNN-VQA first extracts spatial and temporal features by two different convolutional neural network branches, respectively. After that, the spatial–temporal joint feature fusion is constructed to obtain the joint spatial–temporal features. Meanwhile, the TSCNN-VQA also integrates an attention module to guarantee that the process conforms to the mechanism that the visual system perceives video information. Finally, the overall quality is obtained by non-linear regression. The experimental results in both the LIVE and CSIQ VQA datasets show that the performance indicators obtained by TSCNN-VQA are higher than those of existing VQA methods, which demonstrates that TSCNN-VQA can accurately evaluate video quality and has better consistency with the human visual system. Full article

Homogeneous waiting group (HWG) criteria are central to the patient referral process, guiding primary care physicians and hospitalists in directing patient care to specialists. This cross-sectional observational study, conducted in South Tyrol, Italy, in 2023, aimed to assess the implementation and impact of HWG criteria on healthcare from the perspective of general practitioners and hospital physicians. A questionnaire was developed to gain knowledge about referral practices as perceived by general practitioners and specialists. The survey included 313 participants (82 general practitioners and 231 hospital physicians) and was designed to capture a range of factors influencing the application of HWG criteria, including communication and collaboration practices. The results showed moderate levels of familiarity with HWG criteria and opinions about the need for criteria refinement among hospitalists, indicating that further education and refinement of these criteria are warranted. Both general practitioners and hospital physicians expressed dissatisfaction with the current specialist referral system, highlighting the significant gaps in effective communication and collaboration. The survey also demonstrated the influence of patient demands and waiting times on referral practices, and the need for streamlined and accessible specialist care. This study highlights the need for improvement and adaptation of HWG criteria to better meet the needs of healthcare providers and patients in South Tyrol. By addressing the identified gaps in communication, collaboration, and education related to the HWG system, the efficiency, effectiveness, and patient-centeredness of the referral process can be improved, ultimately leading to better health outcomes. Full article

In this paper, the authors briefly review some closed-form formulas of the Gauss hypergeometric function at specific arguments, alternatively prove four of these formulas, newly extend a closed-form formula of the Gauss hypergeometric function at some specific arguments, successfully apply a special case of the newly extended closed-form formula to derive an alternative form for the Maclaurin power series expansion of the Wilf function, and discover two novel increasing rational approximations to a quarter of the circular constant. Full article

While numerous studies have explored the correlation between the built environment and ride-hailing demand, few have assessed their nonlinear interplay. Utilizing ride-hailing order data and multi-source built environment data from Nanjing, China, this paper uses the machine learning method, eXtreme Gradient Boosting (XGBoost), combined with Shapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs) to investigate the impact of built environment factors on ride-hailing travel demand, including their nonlinear and threshold effects. The findings reveal that dining facilities have the most significant impact, with a contribution rate of 30.75%, on predicting ride-hailing travel demand. Additionally, financial, corporate, and medical facilities also exert considerable influence. The built environment factors need to reach a certain threshold or within a certain range to maximize the impact of ride-hailing travel demand. Population density, land use mix, and distance to the subway station collectively influence ride-hailing demand. The results are helpful for TNCs to allocate network ride-hailing resources reasonably and effectively. Full article

The mechanical properties and microstructure of the cemented paste backfill (CPB) in dry–wet cycle environments are particularly critical in backfill mining. In this study, coal gangue, fly ash, cement, glass fiber, and nano-SiO₂ were used to prepare CPB, and dry–wet cycle tests on CPB specimens with different curing ages were conducted. The compressive, tensile, and shear strength of CPB specimens with different curing ages under different dry–wet cycles were analyzed, and the microstructural damage of the specimens was observed by scanning electron microscopy (SEM). The results show that compared with the specimens without dry–wet cycles, the uniaxial compressive strength, tensile strength, and shear strength of the specimens with a curing age of 7 d after seven dry–wet cycles were the smallest, being reduced by 40.22%, 58.25%, and 66.8%, respectively. After seven dry–wet cycles, the compressive, tensile, and shear strength of the specimens with the curing age of 28 d decreased slightly. The SEM results show that with the increasing number of dry–wet cycles, the internal structure of the specimen becomes more and more loose and fragile, and the damage degree of the structural skeleton gradually increases, leading to the poor mechanical properties of CPB specimens. The number of cracks and pores on the specimen surface is relatively limited after a curing age of 28 d, while the occurrence of internal structural damage within the specimen remains insignificant. Therefore, the dry–wet cycle has an important influence on the both mechanical properties and microstructure of CPB. This study provides a reference for the treatment of coal-based solid waste and facilitates the understanding of the mechanical properties of backfill materials under dry–wet cycling conditions. Full article

Even though the role of ecosystem services is known, the identification and assessment of water-related services is usually absent or often less represented as an ecosystem service. Progress in water quality indicator definition and compliance with regulations has been made; however, the relationship between water quality degradation and benefits to individuals and ecosystems remains little recognized. Here, we present an assessment of water quality and identification of ecosystem services in south-east Mexico. This study was performed within the geohydrological reserve zone of the Ring of Sinkholes, Yucatán Peninsula. Thirteen ecosystem services provided by the aquifer were identified. Water quality was evaluated in sinkholes based on national and international norms, considering different sinkhole uses. Results show a dynamic system, without saltwater intrusion and good to excellent water quality. The research demonstrates the relationship between ecosystem services and water quality, showing pressure in services related to uses for aquatic life protection and to a lesser extent those related to consumption. Current productive activities showed no pressure at this time. Principal Component Analysis (PCA) and Analysis of Variance (ANOVA) exhibited a significant difference in parameters and campaigns, but not between sinkholes. A long-lasting monitoring program for water quality is necessary to accurately evaluate the status of ecosystem services provided by the aquifer. Moreover, it is necessary to assess aquifers as ecosystems with economic, ecologic and socio-cultural importance. Effective water governance requires a balance of interests between all parties, within a legal and institutional framework. Full article

Beta-amylases (BAMs, EC 3.2.1.2), belonging to a multigene family, play a pivotal role in starch breakdown and are also involved in hormonal and stress responses, notably to cold stress. Pomegranate trees (Punica granatum L.) are adapted to warm climates and are sensitive to cold temperatures. In this study, we analyzed eight PgBAM genes from the pomegranate genome dataset. These members unevenly distributed across chromosomes and were categorized into four groups based on their orthologous members. The motif composition was highly consistent among most members. In contrast, exon numbers and arrangements were conserved within groups or subgroups, whereas significant diversity was observed between different groups. A syntenic analysis revealed that three PgBAM members (PgBAM1/4/5) showed a total of 11 syntenic relationships with the BAM members from Arabidopsis, kiwifruit, and Chinese white pear, respectively. Promoter binding motif prediction suggested potential roles for PgBAMs’ genes in light, stress, hormones, and development signaling. Gene expression indicated that PgBAM4 was predominantly expressed in leaves, PgBAM7 in flowers, and PgBAM8 in roots and leaves and during fruit ripening, particularly in pericarp development. A transcriptome analysis identified the starch and sucrose metabolism pathway (map00500) as a key factor in the cold stress response of cold-sensitive cultivar ‘Tunisia’ seedlings. PgBAM4 exhibited remarkable expression and was closely associated with the cold-responsive BAM genes, characterized by a closer phylogenetic relationship, conserved catalytic residues, and similar secondary and tertiary structures. Moreover, the differences in soluble sugar levels and PgBAM4 expression were closely associated with the varying cold stress resistance observed between ‘Tunisia’ and ‘Sanbai’ seedlings. Furthermore, yeast one-hybrid assays confirmed that PgCBF7, a critical transcription factor for enhancing freezing tolerance, binds to the promoter region of PgBAM4. Our findings provide a systematic overview of the PgBAM gene family and shed new light on the regulatory mechanisms underlying cold stress tolerance in pomegranate. Full article

Background: During and after the COVID-19 pandemic, there was a suspicion of varying rates of respiratory tract infections (RTIs), particularly pneumonia (PN). Methods: This research evaluated epidemiological indicators of community-acquired pneumonia (CAP) and hospital-acquired pneumonia (HAP) in the COVID-19 pandemic and post-pandemic period, including pathogens, ventilator-associated pneumonia (VAP), selected risk factors, and PN mortality. Results: At 1740 patients, throughout the 22,774 patient-days (Pt-D) and 18,039 ventilation days (Vt-D), there were 681 PN cases (39.14%): CAP 336 (19.31%) and HAP 345 (19.83%). CAP caused by SARS-CoV-2 was diagnosed in 257/336 (76.49%) patients. The clinical manifestations of PNs were CAP with 336/681 (49.34%), VAP with 232/681 (34.07%), and non-ventilator HAP (NV-HAP) with 113/681 cases (16.59%). The incidence rate of CAP/1000 Pt-D has been over 3 times higher in the pandemic period of 2020–2021 (20.25) than in the post-pandemic period of 2022 (5.86), p = 0.000. Similarly, higher incidence rates of VAP/1000 Pt-D were found in the pandemic period (p = 0.050). For NV-HAP, this difference was not statistically significant (p = 0.585). VAP occurred more frequently in the group of patients with PN in the course of COVID-19 compared to patients without COVID-19 (52/234 [22.2%] vs. 180/1506 [11.95%]); (p = 0.000). The most common CAP pathogen (during the pandemic) was SARS CoV-2 234/291 (80.4%), followed by MSSA/MRSA 8/291 (2.75%), whereas the most common VAP/NV-HAP pathogen was Acinetobacter baumannii XDR/MDR. The highest PN mortality was found in the patients with CAP caused by SARS-CoV-2 159/257 (61.87%). Conclusions: Pneumonias were diagnosed in nearly 40% of Intensive Care Unit (ICU) patients. Surveillance of pneumonias during the specific observation period was beneficial in the epidemiological and microbiological analysis of the ICU patients. Full article

In this paper, we propose a global ionospheric total electron content (TEC) maps (GIM) prediction model based on deep learning methods that is both straightforward and practical, meeting the requirements of various applications. The proposed model utilizes an encoder-decoder structure with a Convolution Long Short-Term Memory (ConvLSTM) network and has a spatial resolution of 5° longitude and 2.5° latitude, with a time resolution of 1 h. We utilized the Center for Orbit Determination in Europe (CODE) GIM dataset for 18 years from 2002 to 2019, without requiring any other external input parameters, to train the ConvLSTM models for forecasting GIM 1, 2, and 3 days in advance. Using the CODE GIM data from 1 January 2020 to 31 December 2023 as the test dataset, the performance evaluation results show that the average root mean square errors (RMSE) for 1, 2 and 3 days of forecasts are 2.81 TECU, 3.16 TECU, and 3.41 TECU, respectively. These results show improved performance compared to the IRI-Plas model and CODE’s 1-day forecast product c1pg, and comparable to CODE’s 2-day forecast c2pg. The model’s predictions get worse as the intensity of the storm increases, and the prediction error of the model increases with the lead time. Full article

Ferroelectric domain engineering has wide applications in optical and electronic industries. Compared with traditional electric field poling, femtosecond laser poling has many advantages, such as higher fabrication resolution, 3D engineering applicability, and lower costs of production. In this review, the recent research progress on ferroelectric domain engineering with femtosecond laser pulses is presented. We show the latest results, including complex domain structures fabricated in various kinds of ferroelectric crystals, and discuss the influence of laser poling parameters and conditions on the morphologies of inverted domains and their physical mechanisms. The technical challenges to overcome in future are also briefly discussed. Full article

The stability of offshore floating wind turbine foundation platforms is a fundamental requirement for the efficiency and safety of wind power generation systems. This paper proposes a novel small-diameter float-type semi-submersible platform to improve system stability. To evaluate the superior motion stability of the proposed floating platform, a comprehensive frequency–domain response analysis and experimental study were conducted in comparison with the OC4-DeepCwind platform developed by the National Renewable Energy Laboratory (NREL). The respective comparison of the frequency–domain response analysis and the experimental results demonstrated that the proposed floating wind turbine platform shows better hydrodynamic characteristics and resonance avoidance capability. This not only reduces the Response Amplitude Operators (RAOs), but also enhances the system stability, namely, effectively avoiding the regions of concentrated wave loading and low-frequency ranges. Furthermore, the proposed small-diameter semi-submersible platform has the potential to reduce manufacturing costs, providing valuable insights for the manufacturing of offshore floating wind turbine systems. Full article