Search Results (31)

The incorporation of digital music into the reform of education has become one of the primary methods to improve educational outcomes, increase creativity, and innovate the practices in the classroom. This combination, together with the close industry–academia cooperation, presents the possibilities to integrate educational strategies in accordance with the technological and creative demands of the contemporary world. Nevertheless, uncertainty, reluctance, symmetry, and subjectivity in expert ratings are significant problems to cope with when considering multi-criteria decision-making (MCDM). To resolve them, this paper suggests a Picture Fuzzy Faire Un Choix Adequat (PF-FUCA) decision support model, where fifteen options will be rated by seven criteria, depending on the contribution of four professional decision-makers. These findings indicate that the PF-FUCA framework is effective and superior to the current PF-MCDM models, as illustrated by sensitivity and comparison analysis. The identified best strategies based on the framework are blockchain-based music copyright education and integrated music–STEM platforms that, when combined, offer a viable policy instrument to policymakers, educators, and industry stakeholders. Full article

In the current digital landscape, where platforms process AI-generated content and intelligent network traffic on a large scale, it is the duty of such platforms to continuously measure the reliability, trustworthiness, and security of various data streams. Driven by this practical challenge, this research develops an effective decision-support mechanism in intelligent decision-making in big-data AI-generated content and network systems. The decision problem has considered several uncertainties, including content authenticity, processing efficiency, user trust, cybersecurity, system scalability, privacy protection, and cost of computing. The multidimensional uncertainty of AI-generated information and trends in network behavior are challenging to capture in traditional crisp and fuzzy decision-making models. To fill that gap, a new Picture Fuzzy Faire Un Choix Adequat (PF-FUCA) methodology is proposed, based on multi-perspective expert assessment and better computational aggregation to improve the accuracy of rankings, symmetry, and uncertainty treatment. A case scenario comprising fifteen different alternative intelligent decision strategies and seven evaluation criteria are examined under the evaluation of four decision-makers. The PF-FUCA model successfully prioritizes the best strategies to control AI-based content and network activities to generate a stable and realistic ranking. The comparative and sensitivity analysis show higher robustness, accuracy, and flexibility levels than the existing MCDM techniques. The results indicate that PF-FUCA is specifically beneficial in settings where a large amount of data has to flow, a high uncertainty rate exists, and the variables of decision are dynamic. The research introduces a scalable and credible methodological conception that can be used to facilitate high levels of intelligent computing applications to content governance and network optimization. Full article

The global automotive industry faces significant challenges with respect to its supply chain, particularly component scarcity and the increasing complexity of modern vehicles, which have severely impacted the production of high-tech harnesses. This study addresses the issues faced by a leading automotive harness manufacturing company in Ciudad Obregón, Mexico (an international company that requested confidentiality), which has suffered considerable economic losses (over USD 2870) and production downtime due to component scarcity and delivery delays in component deliveries, affecting “Crew Grande” harness production. This proposal aims to develop a technological solution with a graphical interface to support decision-making in the face of this scarcity. The methodology employed system dynamics to model the supply chain’s complexity, using software such as Stella^® Architect for Forrester diagrams and equations and Vensim^® PLE for causal diagrams. The model was validated with a relative error, confirming its reliability. Multicriteria decision-making (MCDM) was performed using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Faire Un Choix Adequate (FUCA) methods to evaluate 15 scenarios (normal, pessimistic, and optimistic), identifying the four most favorable scenarios for optimizing operational performance. The results demonstrate these solutions’ potential to mitigate losses, improve operational efficiency, and strengthen the company’s position against market and demand fluctuations, especially for its main client, Ford Motor Company, using a graphical user interface (GUI) to support analysis and decision-making. Full article

Fucose-containing glycoproteins and glycolipids broadly occur in humans as well as in many other species and are essential for a wide range of physiological processes, such as cell adhesion, fertilization, and tumor development. In humans, the cellular degradation of various fucosylated glycoconjugates depends on the FUCA1-encoded lysosomal tissue α-L-fucosidase (FUCA1). The crucial role of FUCA1 is reflected by the severe lysosomal storage disease fucosidosis, which causes a massive accumulation of fucosylated glycans, glycolipids, and α(1,6)-fucosylated glycoasparagines. Therefore, it is reasonable to assume that FUCA1 is predominantly responsible for the degradation of fucosylated glycoconjugates, although a second, functionally uncharacterized α-L-fucosidase, the plasma α-L-fucosidase (FUCA2), is known. To investigate the impact of both fucosidases in more detail, we generated two different monoclonal antibodies as useful tools for the detection of human and murine FUCA1 and utilized a FUCA2-specific antibody to demonstrate that FUCA2 is a bona fide lysosomal protein that is sorted in a mannose 6-phosphate (M6P)-dependent manner. We then compared FUCA1 and FUCA2 upon ectopic expression and evaluated their enzyme activity profiles under various conditions. Untagged and differently tagged versions of FUCA1 exhibited α-L-fucosidase activity, while various FUCA2 derivatives, even after affinity purification, did not show any fucosidase activity against commonly used pseudo-substrates. Our findings suggest that FUCA1 and not FUCA2 is exclusively responsible for the lysosomal de-fucosylation of glycoconjugates. Full article

Background/Objectives: Instrumental Activities of Daily Living (IADL) are the key indicators of the autonomy and functional ability in older adults with neurocognitive disorders (NCDs). However, the specific predictors of IADL performance across the NCD spectrum remains insufficiently characterized. This study aimed to identify the cognitive, motor, and caregiver-related determinants of the IADL in individuals with minor and major NCDs. Methods: A cross-sectional study was conducted involving 117 participants referred from a university-based dementia clinic. Standardized tools were administered to evaluate their IADL performance (Lawton IADL Scale), cognition [Addenbrooke’s Cognitive Examination III (ACE-III)], Functional Cognitive Assessment Scale (FUCAS)], motor functions, balance, and mobility [Tinetti Test, Timed Up and Go (TUG)], emotional status [Geriatric Depression Scale (GDS)], neuropsychiatric symptoms [Neuropsychiatric Inventory (NPI)], and caregiver burden [Zarit Burden Interview (ZBI)]. Multiple regression analyses were performed to identify the significant predictors of IADL performance. Results: In the total sample (n = 117), the IADL performance was significantly predicted via ACE-III, FUCAS, and Tinetti-balance (adjusted R² = 0.729). In the minor NCD group (n = 41), the significant predictors included sex, FUCAS, GDS, Tinetti-balance, and TUG (adjusted R² = 0.725). In the major NCD group (n = 76), ACE-III, FUCAS, and Tinetti-balance remained the significant predictors (adjusted R² = 0.634). Female sex and a worse profile on the other variables were associated with lower IADL scores. Conclusions: Global cognitive decline, executive dysfunction in everyday problem-solving situations, and balance impairment are the key determinants of IADL performance across both minor and major NCDs. Female sex and depressive symptoms further predicted the IADL performance in the minor NCD group. These findings highlight the need for multidisciplinary assessment and intervention strategies to promote health and autonomy and preserve the functional independence in older adults with NCDs. Full article

Fucosidosis is a rare lysosomal storage disease caused by α-L-fucosidase deficiency following a mutation in the FUCA1 gene. This enzyme is responsible for breaking down fucose-containing glycoproteins, glycolipids, and oligosaccharides within the lysosome. Mutations in FUCA1 result in either reduced enzyme activity or complete loss of function, leading to the accumulation of fucose-rich substrates in lysosomes. Lysosomes become engorged with undigested substrates, which leads to secondary storage defects affecting other metabolic pathways. The central nervous system is particularly vulnerable, with lysosomal dysfunction causing microglial activation, inflammation, and neuronal loss, leading to the neurodegenerative symptoms of fucosidosis. Neuroinflammation contributes to secondary damage, including neuronal apoptosis, axonal degeneration, and synaptic dysfunction, exacerbating the disease process. Chronic neuroinflammation impairs synaptic plasticity and neuronal survival, leading to progressive intellectual disability, learning difficulties, and loss of previously acquired skills. Inflammatory cytokines and lysosomal burden in motor neurons and associated pathways contribute to ataxia, spasticity, and hypotonia, which are common motor symptoms in fucosidosis. Elevated neuroinflammatory markers can increase neuronal excitability, leading to the frequent occurrence of epilepsy in affected individuals. So, fucosidosis is characterized by rapid mental and motor loss, along with growth retardation, coarse facial features, hepatosplenomegaly, telangiectasis or angiokeratomas, epilepsy, inguinal hernia, and dysostosis multiplex. Patients usually die at an early age. Treatment of fucosidosis is a great challenge, and there is currently no definitive effective treatment. Hematopoietic cell transplantation studies are ongoing in the treatment of fucosidosis. However, early diagnosis of this disease and treatment can be effective. In addition, the body’s immune system decreases due to chemotherapy applied after transplantation, leaving the body vulnerable to microbes and infections, and the risk of death is high with this treatment. In another treatment method, gene therapy, the use of retroviral vectors, is promising due to their easy integration, high cell efficiency, and safety. In another treatment approach, enzyme replacement therapy, preclinical studies are ongoing for fucosidosis, but the blood–brain barrier is a major obstacle in lysosomal storage diseases affecting the central nervous system. Early diagnosis is important in fucosidosis, a rare disease, due to the delay in the diagnosis of patients identified so far and the rapid progression of the disease. In addition, enzyme replacement therapy, which carries fewer risks, is promising. Full article

This study examines the Logistics Performance Index (LPI) rankings developed by the World Bank from a methodological perspective and proposes an alternative decision support framework. LPI serves as an interactive tool that helps countries identify challenges, innovative solutions, and opportunities in their trade and logistics sectors. In this study, the efficiency of logistics operations in 118 countries was evaluated using an integrated multi-criteria decision-making (MCDM) model objectively weighted by the Entropy method. Countries were ranked using the MCRAT, SAW, TOPSIS, and FUCA methods. According to the findings, large datasets provide more robust insights for sensitivity analyses, and wider weighting coefficient combinations make the data more meaningful. In addition, it is suggested to use low-compensation methods instead of classical additive methods for LPI. Unlike other studies in literature, this research applied an innovative sensitivity analysis to test the robustness of the model and comprehensively examined the effects of weighting techniques based on over 2500 different MCDM results. The findings suggest that the FUCA method should be recommended to decision-makers for calculating LPI rankings due to its simplicity, practicality, low compensatory power, and low sensitivity. This study offers methodological improvements when evaluating logistics performance and provides significant contributions to decision-making processes. The findings are expected to provide a valuable resource for policymakers and businesses in understanding a country’s position in global competition, as well as serving as a reference for researchers evaluating the logistics performance of countries. Full article

Background: Olive leaves are a significant source of biophenols, which have a beneficial impact on cognitive performance. Objective: To examine, for the first time, in humans the effect of the daily consumption of a beverage containing olive leaf extract (OLE) versus a Mediterranean diet (MeDi) on patients diagnosed with mild Alzheimer’s Disease (AD), in addition to their regular treatment. Methods: A randomized clinical trial compared OLE’s effects on cognitive and functional performance in 55 mild AD patients. Each participant was randomly assigned to two groups: (1) Group 1 was given olive leaves for making a daily beverage and MeDi instructions through monthly diet programs; (2) Group 2 received only the MeDi instructions. After six months, all participants underwent a second neuropsychological evaluation. Results: Group 1 participants had statistically significantly higher MMSE scores compared to Group 2 with a p-value of 0.0135. Specifically, the mean MMSE difference in patients receiving OLE was close to 0, indicating no memory deterioration, whereas in controls it was −4.1, indicative of cognitive decline. The remaining neuropsychological assessments (FRSSD, FUCAS, ADAS-Cog, CDR, GDS, and NPI) revealed better results in the OLE group, except for GDS, which showed no change, but without statistically significant differences between the two groups. Full article

The role of oxidative stress in health and homeostasis has generated interest in the scientific community due to its association with cardiovascular and neurodegenerative diseases, cancer, and other diseases. Therefore, extensive research seeks to identify new exogenous antioxidant compounds for supplementation. Polysaccharides are recognized for their antioxidant properties. However, polysaccharide chemical modifications are often necessary to enhance these properties. Therefore, dextran was conjugated with gallic acid (Dex-Gal) and later combined with fucoidan A (FucA) to formulate blends aimed at achieving superior antioxidant activity compared to individual polysaccharides. A factorial design was employed to combine FucA and Dex-Gal in different proportions, resulting in five blends (BLD1, BLD2, BLD3, BLD4, and BLD5). An analysis of surface graphs from in vitro antioxidant tests, including total antioxidant capacity (TAC), reducing power, and hydroxyl radical scavenging, guided the selection of BLD4 as the optimal formulation. Tests on 3T3 fibroblasts under various conditions of oxidative stress induced by hydrogen peroxide revealed that BLD4 provided enhanced protection compared to its isolated components. The BLD4 formulation, resulting from the combination of Dex-Gal and FucA, showed promise as an antioxidant strategy, outperforming its individual components and suggesting its potential as a supplement to mitigate oxidative stress in adverse health conditions. Full article

From the most ancient RNAs, which followed an RNY pattern and folded into small hairpins, modern RNA molecules evolved by two different pathways, dubbed Extended Genetic Code 1 and 2, finally conforming to the current standard genetic code. Herein, we describe the evolutionary path of the RNAome based on these evolutionary routes. In general, all the RNA molecules analysed contain portions encoded by both genetic codes, but crucial features seem to be better recovered by Extended 2 triplets. In particular, the whole Peptidyl Transferase Centre, anti-Shine–Dalgarno motif, and a characteristic quadruplet of the RNA moiety of RNAse-P are clearly unveiled. Differences between bacteria and archaea are also detected; in most cases, the biological sequences are more stable than their controls. We then describe an evolutionary trajectory of the RNAome formation, based on two complementary evolutionary routes: one leading to the formation of essentials, while the other complemented the molecules, with the cooperative assembly of their constituents giving rise to modern RNAs. Full article

The structural design of prestressed arched trusses presents a complex challenge due to the need to balance multiple conflicting objectives such as structural performance, weight, and constructability. This complexity is further compounded by the interdependent nature of the structural elements, which necessitates a comprehensive optimization approach. Addressing this challenge is crucial for advancing construction practices and improving the efficiency and safety of structural designs. The integration of advanced optimization algorithms and decision-making techniques offers a promising avenue for enhancing the design process of prestressed arched trusses. This study proposes the use of three advanced multi-objective optimization algorithms: NSGA-III, CTAEA, and SMS-EMOA, to optimize the structural design of prestressed arched trusses. The performance of these algorithms was evaluated using generational distance and inverted generational distance metrics. Additionally, the non-dominated optimal designs generated by these algorithms were assessed and ranked using multiple multi-criteria decision-making techniques, including SAW, FUCA, TOPSIS, PROMETHEE, and VIKOR. This approach allowed for a robust comparison of the algorithms and provided insights into their effectiveness in balancing the different design objectives. The results of the study indicated that NSGA-III exhibited superior performance with a GD value of 0.215, reflecting a closer proximity of its solutions to the Pareto front, and an IGD value of 0.329, indicating a well-distributed set of solutions across the Pareto front. In comparison, CTAEA and SMS-EMOA showed higher GD values of 0.326 and 0.436, respectively, suggesting less convergence to the Pareto front. However, SMS-EMOA demonstrated a balanced performance in terms of constructability and structural weight, with an IGD value of 0.434. The statistical significance of these differences was confirmed by the Kruskal–Wallis test, with p-values of $2.50\times {10}^{-15}$ for GD and $5.15\times {10}^{-06}$ for IGD. These findings underscore the advantages and limitations of each algorithm, providing valuable insights for future applications in structural optimization. Full article

Cancer is a difficult-to-cure disease with high worldwide incidence and mortality, in large part due to drug resistance and disease relapse. Glycosylation, which is a common modification of cellular biomolecules, was discovered decades ago and has been of interest in cancer research due to its ability to influence cellular function and to promote carcinogenesis. A variety of glycosylation types and structures regulate the function of biomolecules and are potential targets for investigating and treating cancer. The link between glycosylation and carcinogenesis has been more recently revealed by the role of p53 in energy metabolism, including the p53 target gene alpha-L-fucosidase 1 (FUCA1), which plays an essential role in fucosylation. In this review, we summarize roles of glycan structures and glycosylation-related enzymes to cancer development. The interplay between glycosylation and tumor microenvironmental factors is also discussed, together with involvement of glycosylation in well-characterized cancer-promoting mechanisms, such as the epidermal growth factor receptor (EGFR), phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) and p53-mediated pathways. Glycan structures also modulate cell–matrix interactions, cell–cell adhesion as well as cell migration and settlement, dysfunction of which can contribute to cancer. Thus, further investigation of the mechanistic relationships among glycosylation, related enzymes and cancer progression may provide insights into potential novel cancer treatments. Full article

The advancement toward sustainable infrastructure presents complex multi-objective optimization (MOO) challenges. This paper expands the current understanding of design frameworks that balance cost, environmental impacts, social factors, and structural integrity. Integrating MOO with multi-criteria decision-making (MCDM), the study targets enhancements in life cycle sustainability for complex engineering projects using precast modular road frames. Three advanced evolutionary algorithms—NSGA-II, NSGA-III, and RVEA—are optimized and deployed to address sustainability objectives under performance constraints. The efficacy of these algorithms is gauged through a comparative analysis, and a robust MCDM approach is applied to nine non-dominated solutions, employing SAW, FUCA, TOPSIS, PROMETHEE, and VIKOR decision-making techniques. An entropy theory-based method ensures systematic, unbiased criteria weighting, augmenting the framework’s capacity to pinpoint designs balancing life cycle sustainability. The results reveal that NSGA-III is the algorithm converging towards the most cost-effective solutions, surpassing NSGA-II and RVEA by 21.11% and 10.07%, respectively, while maintaining balanced environmental and social impacts. The RVEA achieves up to 15.94% greater environmental efficiency than its counterparts. The analysis of non-dominated solutions identifies the $A_4$ design, utilizing 35 MPa concrete and B500S steel, as the most sustainable alternative across 80% of decision-making algorithms. The ranking correlation coefficients above 0.94 demonstrate consistency among decision-making techniques, underscoring the robustness of the integrated MOO and MCDM framework. The results in this paper expand the understanding of the applicability of novel techniques for enhancing engineering practices and advocate for a comprehensive strategy that employs advanced MOO algorithms and MCDM to enhance sustainable infrastructure development. Full article

Wildtype Escherichia coli cells cannot grow on L-1,2-propanediol, as the fucAO operon within the fucose (fuc) regulon is thought to be silent in the absence of L-fucose. Little information is available concerning the transcriptional regulation of this operon. Here, we first confirm that fucAO operon expression is highly inducible by fucose and is primarily attributable to the upstream operon promoter, while the fucO promoter within the 3′-end of fucA is weak and uninducible. Using 5′RACE, we identify the actual transcriptional start site (TSS) of the main fucAO operon promoter, refuting the originally proposed TSS. Several lines of evidence are provided showing that the fucAO locus is within a transcriptionally repressed region on the chromosome. Operon activation is dependent on FucR and Crp but not SrsR. Two Crp-cAMP binding sites previously found in the regulatory region are validated, where the upstream site plays a more critical role than the downstream site in operon activation. Furthermore, two FucR binding sites are identified, where the downstream site near the first Crp site is more important than the upstream site. Operon transcription relies on Crp-cAMP to a greater degree than on FucR. Our data strongly suggest that FucR mainly functions to facilitate the binding of Crp to its upstream site, which in turn activates the fucAO promoter by efficiently recruiting RNA polymerase. Full article

The integration of sustainability principles into the structural design and decision-making processes for transportation infrastructure, particularly concerning reinforced concrete precast modular frames (RCPMF), is recognized as crucial for ensuring outcomes that are environmentally responsible, economically feasible, and socially beneficial. In this study, this challenge is addressed, with the significance of sustainable development in modern engineering practices being underscored. A novel approach, which is a combination of multi-objective optimization (MOO) with multi-criteria decision-making (MCDM) techniques, is proposed, tailored specifically for the design and selection of RCPMF. The effectiveness of three repair operators—statistical-based, random, and proximity-based—in optimizing economic, environmental, and social objectives is evaluated. Precise evaluation of objective functions is facilitated by a customized Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm, complemented by a detailed life cycle analysis (LCA). The utilization of simple additive weighting (SAW) and fair un choix adéquat (FUCA) methods for the scoring and ranking of the MOO solutions has revealed that notable excellence in meeting the RCPMF design requirements is exhibited by the statistical-based repair operator, which offers solutions with lower impacts across all dimensions and demonstrates minimal variability. MCDM techniques produced similar rankings, with slight score variations and a significant correlation of 0.9816, showcasing their consistent evaluation capacity despite distinct operational methodologies. Full article