The use of scaffolds, three-dimensional porous, biodegradable and biocompatible structures, that can be produced from natural polymers, synthetics, ceramics and metals is crucial in the tissue engineering field. Chitosan is a polysaccharide of natural origin, found in the exoskeleton of marine arthropods and in the cell wall of fungi, with enormous popularity in the production of three-dimensional materials for Tissue Engineering, in particular bone repair. This polymer has several advantages in the production of these structures in bone regeneration and repair: biodegradability, biocompatibility, non-toxicity and antimicrobial properties. This study aimed to prepare porous scaffolds, for bone repair of degenerative diseases in the spine with better performance and less secondary effects, based on chitosan and another biopolymer (sodium alginate) with the incorporation of calcium phosphates (hydroxyapatite and β-tricalcium phosphate), for tissue engineering application. The obtained scaffolds were object of a detailed characterization, namely with regard to their porosity through the ethanol method, degradation, positron annihilation spectroscopy (PAS), mechanical properties, scanning electronic microscope (SEM), thermal stability through thermogravimetric analysis (TGA), chemical composition through X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The results obtained showed that the different scaffolds presented pores able to support osteoid matrix growth. The crosslinking of scaffolds was also evaluated and resulted in pores with smaller dimensions and higher regularity in the chitosan-sodium alginate polymer without calcium phosphate scaffold. It was also possible to observe the effect of inorganics on mixed-matrix scaffolds, both morphologically and chemically. These scaffolds showed promising results in terms of mechanical and chemical properties, along with promising porosity for tissue regeneration applications. Full article

Inherited retinal degeneration (RD) constitutes a heterogeneous group of genetic retinal degenerative disorders. The molecular mechanisms underlying RD encompass a diverse spectrum of cellular signaling, with the unfolded protein response (UPR) identified as a common signaling pathway chronically activated in degenerating retinas. TRIB3 has been recognized as a key mediator of the PERK UPR arm, influencing various metabolic pathways, such as insulin signaling, lipid metabolism, and glucose homeostasis, by acting as an AKT pseudokinase that prevents the activation of the AKT → mTOR axis. This study aimed to develop a gene-independent approach targeting the UPR TRIB3 mediator previously tested by our group using a genetic approach in mice with RD. The goal was to validate a therapeutic approach targeting TRIB3 interactomes through the pharmacological targeting of EGFR-TRIB3 and delivering cell-penetrating peptides targeting TRIB3 → AKT. The study employed rd10 and P23H RHO mice, with afatinib treatment conducted in p15 rd10 mice through daily intraperitoneal injections. P15 P23H RHO mice received intraocular injections of cell-penetrating peptides twice at a 2-week interval. Our study revealed that both strategies successfully targeted TRIB3 interactomes, leading to an improvement in scotopic A- and B-wave ERG recordings. Additionally, the afatinib-treated mice manifested enhanced photopic ERG amplitudes accompanied by a delay in photoreceptor cell loss. The treated rd10 retinas also showed increased PDE6β and RHO staining, along with an elevation in total PDE activity in the retinas. Consequently, our study demonstrated the feasibility of a gene-independent strategy to target common signaling in degenerating retinas by employing a TRIB3-based therapeutic approach that delays retinal function and photoreceptor cell loss in two RD models. Full article

Cellulose is a biopolymer with numerous advantages that make it an ecological, economical, and high-performing choice for various applications. To fully exploit the potential of cellulose, it is often necessary to dissolve it, which poses a current challenge. The aqueous zinc oxide/sodium hydroxide (ZnO/NaOH/Water) system is a preferred solvent for its rapid dissolution, non-toxicity, low cost, and environmentally friendly nature. In this context, the behavior of cellulose chains in the aqueous solution of ZnO/NaOH and the impact of temperature on the solubility of this polymer were examined through a molecular dynamics simulation. The analysis of the root means square deviation (RMSD), interaction energy, hydrogen bond curves, and radial distribution function revealed that cellulose is insoluble in the ZnO/NaOH solvent at room temperature (T = 298 K). Decreasing the temperature in the range of 273 K to 268 K led to a geometric deformation of cellulose chains, accompanied by a decrease in the number of interchain hydrogen bonds over the simulation time, thus confirming the solubility of cellulose in this system between T = 273 K and T = 268 K. Full article

The required processes and steps for making bread include technological and innovative concepts. The current trend is the use of less toxic compounds and green methods. Besides lactic acid bacteria and yeast, other microorganisms with unique properties, such as enzymes, new aromas and flavors, exopolysaccharides, and vitamins, among other compounds with beneficial properties, could be added to bread manufacture, improving bread quality and health effects for the consumers. The preservation of microbial cultures and starters is crucial in bread-making. New encapsulation methods, cryoprotectants, spray-drying, fluidized bed drying, and vacuum drying are employed for microorganism cultures that will be used as starters or biological additives in fermentation. A development is observed in the antimicrobial methods used as bread preservatives, and studies with plant extracts and essential oils have been proposed and introduced, replacing chemical agents, such as propionate, within the clean-label bread formulations concept. Baking science is a growing research line that incorporates innovative methods, biological additives, new methods, and processes focusing on microbiological protection. Full article

This paper presents a numerical model for thermal energy storage systems’ design, development, and feasibility. The energy storage was composed of a tank that stores phase change material (AlSi12) and internal pipes with heat transfer fluid (Cerrolow 117), coupled to a power block to dispatch electrical energy on a small scale for off-grid industrial applications. Subsequently, the evolution of the temperature in charge/discharge cycles, temperature degradation, and storage efficiency was determined with the appropriate magnitudes and behavior through the resolution of a numerical model. In addition, for the proposed electric power generation plant for an off-grid pumping system in the mining industry of Chile, a numerical model was developed using the finite volumes method to simulate the thermocline performance. As a result, the temperature history reflects stable thermal behavior, low degradation, and high efficiency of approximately 92%, with a storage time increasing up to 13 [h] and 384.8 [kWh] capacity. Also, implementation was feasible on a small scale due to its compact, modular, and economically competitive characteristics in a concentrated solar power plant. Finally, the proposed design was proven to be an accurate and reliable alternative for small-scale off-grid mining applications. Full article

Evapotranspiration (ET) is a major component of the water budget in Bottomland Hardwood Forests (BHFs) and is driven by a complex intertwined suite of meteorological variables. The understanding of these interdependencies leading to seasonal variations in ET is crucial in better informing water resource management in the region. We used structural equation modeling and AIC modeling to analyze drivers of ET using Eddy covariance water flux data collected from a BHF located in the Russel Sage Wildlife Management Area (RSWMA). It consists of mature closed-canopy deciduous hardwood trees with an average canopy height of 27 m. A factor analysis was used to characterize the shared variance among drivers, and a path analysis was used to quantify the independent contributions of individual drivers. In our results, ET and net radiation (R_n) showed similar variability patterns with Vapor Pressure Deficit (VPD) and temperature in the spring, summer, and autumn seasons, while they differed in the winter season. The path analysis showed that R_n has the strongest influence on ET variations via direct and indirect pathways. In deciduous forests like BHFs, our results suggest that ET is more energy dependent during the growing season (spring and summer) and early non-growing season (autumn) and more temperature dependent during the winter season. Full article

Directed evolution is a pivotal strategy for new antibody discovery, which allowed the generation of high-affinity Fabs against gliadin from two antibody libraries in our previous studies. One of the libraries was exclusively derived from celiac patients’ mRNA (immune library) while the other was obtained through a protein engineering approach (semi-immune library). Recent advances in high-throughput DNA sequencing techniques are revolutionizing research across genomics, epigenomics, and transcriptomics. In the present work, an Oxford Nanopore in-lab sequencing device was used to comprehensively characterize the composition of the constructed libraries, both at the beginning and throughout the phage-mediated selection processes against gliadin. A customized analysis pipeline was used to select high-quality reads, annotate chain distribution, perform sequence analysis, and conduct statistical comparisons between the different selection rounds. Some immunological attributes of the most representative phage variants after the selection process were also determined. Sequencing results revealed the successful transfer of the celiac immune response features to the immune library and the antibodies derived from it, suggesting the crucial role of these features in guiding the selection of high-affinity recombinant Fabs against gliadin. In summary, high-throughput DNA sequencing has improved our understanding of the selection processes aimed at generating molecular binders against gliadin. Full article

Efficient triaging and referral assessments are critical in ensuring prompt medical intervention in the community healthcare (CHC) system. However, the existing triaging systems in many community health services are an intensive, time-consuming process and often lack accuracy, particularly for various symptoms which might represent heart failure or other health-threatening conditions. There is a noticeable limit of research papers describing AI technologies for triaging patients. This paper proposes a novel quantitative data-driven approach using machine learning (ML) modelling to improve the community clinical triaging process. Furthermore, this study aims to employ the feature selection process and machine learning power to reduce the triaging process’s waiting time and increase accuracy in clinical decision making. The model was trained on medical records from a dataset of patients with “Heart Failure”, which included demographics, past medical history, vital signs, medications, and clinical symptoms. A comparative study was conducted using a variety of machine learning algorithms, where XGBoost demonstrated the best performance among the other ML models. The triage levels of 2,35,982 patients achieved an accuracy of 99.94%, a precision of 0.9986, a recall of 0.9958, and an F1-score of 0.9972. The proposed diagnostic model can be implemented for the CHC decision system and be developed further for other medical conditions. Full article

Tetragonal ZrO₂, synthesized by the sol–gel method and dip-coating technique, was found to be photocatalytically active for the degradation of methylene blue. The ZrO₂ thin films were characterized by X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and UV-vis spectroscopy. The photocatalytic degradation of methylene blue was carried out with this material. We identified the tetragonal phase in ZrO₂ thin film at different annealing temperatures from 400 °C to 550 °C. The XRD study indicated that the films were monocrystalline in nature with preferred grain orientation along (011) plane and exhibited a tetragonal crystal structure. The crystallite size of the films increased with increasing annealing temperature. FTIR explained the bonding nature and confirmed the formation of the composite. UV-Vis showed the optical absorbance was high in the visible region and the optical band gap value increased with annealing temperature. The photocatalytic experimental results revealed that ZrO₂ thin films degraded MB by 20%, 24%, 29%, and 36%, with annealing temperatures of 400 °C at 550 °C for 10 h, respectively. Our results provide useful insights into the development of photocatalytic materials and degradation of methylene blue. Full article

Amyloid fibroproliferation leads to organ damage and is associated with a number of neurodegenerative diseases affecting populations worldwide. There are several ways to protect against fibril formation, including inhibition. A variety of organic compounds based on molecular recognition of amino acids within the protein have been proposed for the design of such inhibitors. However, the role of macrocyclic compounds, i.e., thiacalix[4]arenes, in inhibiting fibrillation is still almost unknown. In the present work, the use of water-soluble thiacalix[4]arene derivatives for the inhibition of hen egg-white lysozyme (HEWL) amyloid fibrillation is proposed for the first time. The binding of HEWL by the synthesized thiacalix[4]arenes (logKa = 5.05–5.13, 1:1 stoichiometry) leads to the formation of stable supramolecular systems capable of stabilizing the protein structure and protecting against fibrillation by 29–45%. The macrocycle conformation has little effect on protein binding strength, and the native HEWL secondary structure does not change via interaction. The synthesized compounds are non-toxic to the A549 cell line in the range of 0.5–250 µg/mL. The results obtained may be useful for further investigation of the anti-amyloidogenic role of thiacalix[4]arenes, and also open up future prospects for the creation of new ways to prevent neurodegenerative diseases. Full article

Soil microbes are crucial in shaping the root-associated microbial communities. In this study, we analyzed the effect of the soil–root niche gradient on the diversity, composition, and assembly of the bacterial community and co-occurrence network of two cotton varieties. The results revealed that the bacterial communities in cotton soil–root compartment niches exhibited a skewed species abundance distribution, dominated by abundant taxa showing a strong spatial specificity. The assembly processes of the rhizosphere bacterial communities were mainly driven by stochastic processes, dominated by the enrichment pattern and supplemented by the depletion pattern to recruit bacteria from the bulk soil, resulting in a more stable bacterial community. The assembly processes of the endosphere bacterial communities were determined by processes dominated by the depletion pattern and supplemented by the enrichment pattern to recruit species from the rhizosphere, resulting in a decrease in the stability and complexity of the community co-occurrence network. The compartment niche shaped the diversity of the bacterial communities, and the cotton variety genotype was an important source of diversity in bacterial communities within the compartment niche. We suggest that the moderate taxa contribute to significantly more changes in the diversity of the bacterial community than the rare and abundant taxa during the succession of bacterial communities in the cotton root–soil continuum. Full article

Selective laser melting (SLM) technology is a promising additive manufacturing technology. However, due to the numerous influencing factors in this complex process, a reliable real-time method is needed to monitor the forming process of SLM. The molten pool is the smallest forming unit in the SLM process, the consistency of which can effectively reflect the quality of the printing process. By using a coaxial optical path structure and a compound amplifier circuit, high-speed acquisition of molten pool radiation can be realized. Next, single factor analysis and orthogonal experimentation were used to investigate the influence levels of key process parameters on the radiation of molten pool. In addition, numerical simulation was carried out with the same parameter setting schemes, the results of which are consistent with those in radiation detection experiments. It is shown that the laser power has the greatest effect on the radiation of the molten pool, while the scanning speed and the hatch spacing have little effect on the radiation. Finally, the positioning experiment involving the small hole structure was carried out, and the experimental results showed that the device could accurately locate the position coordinates of the given hole structure. Full article

In indoor visible light communication (VLC), the received signals are subject to severe interference due to factors such as high-brightness backgrounds, long-distance transmissions, and indoor obstructions. This results in an increase in misclassification for modulation format recognition. We propose a novel model called VLCMnet. Within this model, a temporal convolutional network and a long short-term memory (TCN-LSTM) module are utilized for direct channel equalization, effectively enhancing the quality of the constellation diagrams for modulated signals. A multi-mixed attention network (MMAnet) module integrates single- and mixed-attention mechanisms within a convolutional neural network (CNN) framework specifically for constellation image classification. This allows the model to capture fine-grained spatial structure features and channel features within constellation diagrams, particularly those associated with high-order modulation signals. Experimental results obtained demonstrate that, compared to a CNN model without attention mechanisms, the proposed model increases the recognition accuracy by 19.2%. Under severe channel distortion conditions, our proposed model exhibits robustness and maintains a high level of accuracy. Full article

Background/Objectives: Lower extremity amputations (LEAs) are a burdensome complication of peripheral artery disease (PAD) and/or arterial embolism and thrombosis (AET). We assessed the trends in PAD- and/or AET-related LEAs in Romania. Methods: This retrospective study (2015–2019) analyzed data on minor and major LEAs in hospitalized patients recorded in the National School for Public Health, Management, and Health Education database. The absolute numbers and incidences of LEAs were analyzed by diagnosis type, year, age, sex, and amputation level. Results: Of 38,590 vascular disease-related amputations recorded nationwide, 36,162 were in PAD and 2428 in AET patients. The average LEA incidence in the general population was 34.73 (minimum: 31.96 in 2015; maximum: 36.57 in 2019). The average incidence of major amputations, amputations above the knee, hip amputations, amputations below the knee, and minor amputations was 16.21 (15.62 in 2015; 16.84 in 2018), 13.76 (13.33 in 2015; 14.28 in 2018), 0.29 (0.22 in 2017; 0.35 in 2019), 2.15 (2.00 in 2015; 2.28 in 2019), and 18.52 (16.34 in 2015; 20.12 in 2019), respectively. Yearly PAD- and/or AET-related amputations were significantly higher in men versus women. The overall number of LEAs increased with age, particularly in patients ≥ 70 years. The increase in the total number of amputations was mainly due to a constant rise in minor amputations for both groups, regardless of gender. Conclusions: PAD- and/or AET-related LEAs in Romania increased from 2015 to 2019, with men having a greater incidence than women. Raising awareness and effective management strategies are needed to prevent LEAs. Full article

Moiré patterns caused by aliasing between the camera’s sensor and the monitor can severely degrade image quality. Image demoiréing is a multi-task image restoration method that includes texture and color restoration. This paper proposes a new multibranch wavelet-based image demoiréing network (MBWDN) for moiré pattern removal. Moiré images are separated into sub-band images using wavelet decomposition, and demoiréing can be achieved using the different learning strategies of two networks: moiré removal network (MRN) and detail-enhanced moiré removal network (DMRN). MRN removes moiré patterns from low-frequency images while preserving the structure of smooth areas. DMRN simultaneously removes high-frequency moiré patterns and enhances fine details in images. Wavelet decomposition is used to replace traditional upsampling, and max pooling effectively increases the receptive field of the network without losing the spatial information. Through decomposing the moiré image into different levels using wavelet transform, the feature learning results of each branch can be fully preserved and fed into the next branch; therefore, possible distortions in the recovered image are avoided. Thanks to the separation of high- and low-frequency images during feature training, the proposed two networks achieve impressive moiré removal effects. Based on extensive experiments conducted using public datasets, the proposed method shows good demoiréing validity both quantitatively and qualitatively when compared with the state-of-the-art approaches. Full article

Myelodysplastic syndrome/neoplasm (MDS) comprises a group of heterogeneous hematopoietic disorders that present with genetic mutations and/or cytogenetic changes and, in the advanced stage, exhibit wide-ranging gene hypermethylation. Patients with higher-risk MDS are typically treated with repeated cycles of hypomethylating agents, such as azacitidine. However, some patients fail to respond to this therapy, and fewer than 50% show hematologic improvement. In this context, we focused on the potential use of epigenetic data in clinical management to aid in diagnostic and therapeutic decision-making. First, we used the F-36P MDS cell line to establish an azacitidine-resistant F-36P cell line. We performed expression profiling of azacitidine-resistant and parental F-36P cells and used biological and bioinformatics approaches to analyze candidate azacitidine-resistance-related genes and pathways. Eighty candidate genes were identified and found to encode proteins previously linked to cancer, chronic myeloid leukemia, and transcriptional misregulation in cancer. Interestingly, 24 of the candidate genes had promoter methylation patterns that were inversely correlated with azacitidine resistance, suggesting that DNA methylation status may contribute to azacitidine resistance. In particular, the DNA methylation status and/or mRNA expression levels of the four genes (AMER1, HSPA2, NCX1, and TNFRSF10C) may contribute to the clinical effects of azacitidine in MDS. Our study provides information on azacitidine resistance diagnostic genes in MDS patients, which can be of great help in monitoring the effectiveness of treatment in progressing azacitidine treatment for newly diagnosed MDS patients. Full article

Due to the favorable features obtained through the incorporation of fluorine atom(s), fluorinated drugs are a group with emerging pharmaceutical importance. As their commercial availability is still very limited, to expand the range of possible candidates, new fluorinated tryptophan analogs were synthesized. Control of enantiopurity during the synthesis procedure requires that highly efficient enantioseparation methods be available. In this work, the enantioseparation of seven fluorinated tryptophans and tryptophan was studied and compared systematically to (i) develop analytical methods for enantioselective separations and (ii) explore the chromatographic features of the fluorotrytophans. For enantioresolution, macrocyclic glycopeptide-based selectors linked to core-shell particles were utilized, applying liquid chromatography-based methods. Application of the polar-ionic mode resulted in asymmetric and broadened peaks, while reversed-phase conditions, together with mobile-phase additives, resulted in baseline separation for all studied fluorinated tryptophans. The marked differences observed between the methanol and acetonitrile-containing eluent systems can be explained by the different solvation abilities of the bulk solvents of the applied mobile phases. Among the studied chiral selectors, teicoplanin and teicoplanin aglycone were found to work effectively. Under optimized conditions, baseline separations were achieved within 6 min. Ionic interactions were semi-quantitatively characterized and found to not influence enantiorecognition. Interestingly, fluorination of the analytes does not lead to marked changes in the chromatographic characteristics of the methanol-containing eluents, while larger differences were noticed when the polar but aprotic acetonitrile was applied. Experiments conducted on the influence of the separation temperature indicated that the separations are enthalpically driven, with only one exception. Enantiomeric elution order was found to be constant on both teicoplanin and teicoplanin aglycone-based chiral stationary phases (L < D) under all applied chromatographic conditions. Full article

Ginkgo biloba L. leaves are rich in secondary metabolites with important medicinal values; to increase their contents, foliar spraying of micronutrients is a potential strategy. Zinc, a multifunctional element, has a significant impact on the content of secondary metabolites in other plants, but relevant research into ginkgo is still lacking. In our study, different spraying time and concentration strategies were used to investigate the effects of zinc sulfate (ZnSO₄) on physiological indicators and secondary metabolites of 2-year-old ginkgo. The results demonstrated that ZnSO₄ could increase the contents of hydrogen peroxide, abscisic acid, and free amino acids in ginkgo leaves. It also enhances the antioxidant enzyme activity of ginkgo leaves, decreases the content of plant auxin, and ultimately facilitates the accumulation of ginkgo terpene lactones (TTL). Spraying ZnSO₄ in June resulted in a more significant increase in the contents of TTL and flavonoids compared to spraying in August. After spraying 12 mmol/L ZnSO₄ in June, the contents of TTL and flavonoids in ginkgo leaves were significantly elevated by 35.95% and 24.30%, respectively, compared to those in the CK (p < 0.05). The contents of ginkgolide A, B, and C were notably increased by 45.93%, 46.56%, and 74.29%, respectively, compared to those in the CK (p < 0.05). Therefore, our study suggests that the optimal timing for spraying ZnSO₄ on ginkgo is in June, with a recommended concentration of 12 mmol/L. Our study provides a theoretical basis for the accumulation of secondary metabolites in ginkgo and guides the production of its leaf-utilization plantations. Full article

Global warming, climate change and the energy crisis are trending topics around the world, especially within the energy sector. The rising cost of energy, greenhouse gas (GHG) emissions and global temperatures stem from the over-reliance on fossil fuel as the major energy resource. These challenges have highlighted the need for alternative energy resources and urgent intervention strategies like energy consumption reduction and improving energy efficiency. The heating, ventilation, and air-conditioning (HVAC) system in a building accounts for about 70% of energy consumption, and a decision to reduce energy consumption may impact the indoor environmental quality (IEQ) of the building. It is important to adequately balance the tradeoff between IEQ and energy management. Artificial intelligence (AI)-based solutions are being explored for improving building energy performance without compromising IEQ. This paper systematically reviews recent studies on AI and machine learning (ML) for building energy management and IEQ by exploring common use areas, the methods or algorithms applied and the results obtained. The overall purpose of this research is to add to the existing body of work and to highlight energy-related AI applications in buildings and the related gaps. The result shows five common application areas: thermal comfort and indoor air quality (IAQ) control; energy management and energy consumption prediction; indoor temperature prediction; anomaly detection; and HVAC controls. Gaps involving policy, real-life scenario applications, and insufficient study of the visual and acoustic comfort areas are also identified. Very few studies take into consideration the need to follow IEQ standards in the selection process and positioning of sensors in AI applications for IEQ in buildings. This study reveals a need for more systematically summarized research. Full article

This study focuses on recycling Shammi corn stalks in the cement industries, further avoiding air and soil pollution caused by their improper disposal. This crop residue was thermally treated at 700 °C for 2 h under an oxygen-rich environment to produce Shammi corn stalk ash (SCSA). This SCSA was used as a cement replacement material (2–10%, w/w), whereas the control sample included only cement. The compressive strength values for the 4% (w/w) replacement ratio at 2-, 7-, and 28-day ages were greater than those for the control by 26.5%, 15.8%, and 11.4%, respectively. This 4% (w/w) also maintained a better flexural strength than other mixtures, with proper initial and final setting times (135 and 190 min), workability (18.5 cm), and water consistency (27.5%). These mechanical/physical properties were integrated with socio-enviro-economic data collected from experts through a pairwise comparison questionnaire, forming the inputs of a multi-criteria decision-making (MCDM) model. Recycling SCSA in the cement-manufacturing process attained positive scores in the achievement of the three pillars of sustainable development, revealing an overall score greater than the control. Hence, the study outcomes could be essential in developing green concrete, cement blocks, and mortar, based on the sustainable development goals (SDGs) agenda. Full article

The development of floating photovoltaic systems (FPV) for coastal and offshore locations requires a solid understanding of a design’s hydrodynamic performance through reliable methods. This study aims to extend insights into the hydrodynamic behavior of a superficial multi-body FPV system in mild and harsh wave conditions through basin tests at scale 1:10, with specific interest in the performance of hinges that interconnect the PV panels. Particular effort is put into correctly scaling the elasticity of the flexible hinges that interconnect the PV modules. Tests of a 5 × 3 FPV matrix are performed, with and without shelter, by external floating breakwater (FBW). The results show that the PV modules move horizontally in the same phase when the wave length exceeds the length of the FPV system, but shorter waves result in relative motions between modules and, for harsh seas, in hinge buckling. Relative motions suggest that axial loads are highest for the hinges that connect the center modules in the system and for normal wave incidence, while shear loads are highest on the outward hinges and for oblique incidence. The FBW reduces hinge loads as it attenuates the high-frequency wave energy that largely drives relative motions between PV modules. Full article

Performance adaptation is an effective way to improve the accuracy of gas turbine performance models. Although current performance adaptation methods, such as those using genetic algorithms or evolutionary computation to modify component characteristic maps, are useful for finding good solutions, they are essentially searching methods and suffer from long computation time. This paper presents a novel approach that can achieve good performance adaptation with low time complexity and without using any searching method. In this method, the actual component performance parameters are first estimated using engine measurements at different operating conditions. For each operating condition, some scaling factors are introduced and calculated to indicate the difference between the actual and predicted component performance parameters. Afterward, an interpolating algorithm is adopted to synthesize the scaling factors for modifying all major component maps. The adapted component maps are then able to make the engine model match all the gas path measurements and achieve the required accuracy of the engine performance model. The proposed approach has been tested with a model high-bypass turbofan engine using simulated data. The results show that the proposed performance adaptation approach can effectively improve the model’s accuracy. Specifically, the prediction errors can be reduced from about 9% to about 0.6%. In addition, this approach has much less computational complexity compared to other optimization-based counterparts. Full article