Search Results (6,970)

As Industry 5.0 emerges as a human-centric evolution of industrial systems, this study investigates the effectiveness of training interventions in companies aimed at supporting the transition to Industry 5.0, emphasizing human-centric and resilient skill development. Drawing from multiple case studies involving engineers and operators, the research applies both meta-analysis and meta-regression to assess the added value of experiential learning approaches such as Teaching and Learning Factories. In addition, a novel methodology combining quantitative analyses with qualitative interpretation of emerging competences is presented. Principal Component Analysis and classification frameworks are employed to identify and organize key competence clusters along technological, organizational, and social dimensions. Special attention is given to the emergence of human-centered competences such as decision empowerment, which are shown to complement traditional operational capabilities. The findings confirm that experiential training interventions enhance both self-efficacy and adaptive operational readiness, while the use of fusion techniques enables the generalization of results across heterogeneous corporate settings. This work contributes to ongoing discourse on Industry 5.0 readiness by linking training design to strategic company incentives and highlights the role of structured evaluation in informing future policy and implementation pathways. Full article

Metastasis is the main cause of failure in anticancer therapies, and is frequently related to poor prognosis for patients. The true challenge in extending cancer patient life expectancy, eventually managing cancer as a chronic disease with periodic but controllable relapses, relies on the development of effective therapeutic strategies specifically targeting key mechanisms involved in the metastatic cascade. Traditional chemotherapy with alkylating agents, microtubule inhibitors, and antimetabolites has shown limited efficacy against metastatic cells, largely due to the emergence of chemoresistant populations that undergo epithelial-to-mesenchymal transition (EMT), promoting the colonization of distant organs and sustaining metastatic progression. This scenario has spurred significant efforts to identify small molecules and biologics capable of interfering with specific steps in the metastatic process. In this review, we provide an overview of recent advances involving small interfering RNAs (siRNAs) and microRNAs (miRNAs) in cancer therapy. Although most of these agents are still under investigation and have not yet been approved for clinical use, insights into their development stage offer valuable information to identify new targets in the ongoing fight against metastasis. Particular emphasis is placed on the role of chemical modifications applied to siRNAs, such as backbone, sugar, terminal, base, and conjugation changes, and how these factors influence their stability, immunogenicity, and targeting precision. By integrating these aspects into the discussion, this review provides a focused and up-to-date resource for researchers in medicinal chemistry, drug delivery, and pharmaceutical formulation, where molecular design plays a critical role in therapeutic success. Full article

Asphalt is widely used as a binder in pavement engineering. The temperature-dependent phase transition behavior of asphalt binders critically influences pavement performance. This study comprehensively evaluates phase transition characteristics to establish robust performance indicators. Dynamic mechanical analysis (DMA) was employed to characterize 30 neat asphalt binders across a broad temperature range. Phase transition temperatures and moduli were derived from complex and loss modulus curves. Correlations with saturate, aromatic, resin, and asphaltene (SARA) fractions and conventional properties (penetration, viscosity, ductility) were statistically analyzed. The results revealed significant performance variations among binders of identical penetration grades. T_g effectively differentiated low-temperature behavior, overcoming empirical limitations. High-temperature indicators (T₂, E₂₀) strongly correlated with viscosity (R² > 0.96). SARA analysis showed that saturates reduced T_g (r = −0.566) while asphaltenes increased E₂₀ (r = 0.804). Multiple regression models confirm synergistic interactions among SARA fractions, although low-temperature indices exhibit a weaker dependence on composition. DMA-derived phase transition parameters provide physically meaningful performance indicators, superior to conventional metrics. Incorporating T_g and T₂/E₂₀ into grading systems can enhance asphalt selection for thermal susceptibility, advancing pavement durability design. Full article

BaTiO₃ (BT)-based lead-free ceramics are regarded as highly promising candidates for solid-state electrocaloric (EC) cooling devices due to their large spontaneous polarizations, shiftable Curie temperatures, and environmental friendliness. This review summarizes recent progresses in the design and optimization of BT-based EC ceramics. Key aspects include thermodynamic principles of the EC effect (ECE); structural phase transitions; and strategies such as constructing relaxor ferroelectrics, multi-phase coexistence, etc. Finally, future research directions are proposed, including the exploration of local microstructural evolution, polarization flip mechanisms, and bridging material design and device integration. This work aims to provide insights into the development of high-performance BT-based materials for solid-state cooling devices. Full article

Purpose: This study investigates the relationship between flexible working arrangements (FWAs), employee experiences (EEs), and perceived productivity (PP) in the context of New Zealand employees. The study aims to understand how opportunities and challenges within FWAs impact employee productivity, utilising the Job Demands–Resources (JD-R) model as a theoretical framework. Design/methodology/approach: A survey was conducted with 176 employees who transitioned from traditional office settings to FWAs. Data were collected using a structured questionnaire measuring work demand, autonomy, employee experiences, and perceived productivity. The analysis involved correlational and moderated regression techniques to assess the relationships between the variables. Findings: The study found that positive employee experiences (expressed as opportunities) are significantly associated with higher perceived productivity (r = 0.610, p < 0.001), while negative experiences (expressed as challenges) are associated with lower perceived productivity (r = 0.515, p < 0.001). Moreover, management strategies were found to moderate these relationships, further influencing perceived productivity. Originality: This research contributes to the understanding of how FWAs, when effectively managed, can enhance employee productivity by fostering positive experiences. It also highlights the importance of addressing challenges to mitigate negative impacts on productivity. The use of the JD-R model offers a novel approach to exploring these dynamics in the context of FWAs. Practical and social implications: Organisations can enhance productivity by focusing on management strategies that amplify positive employee experiences and reduce challenges within FWAs. Effective FWAs can improve work–life balance, employee wellbeing, and organisational commitment, contributing to a more satisfied and productive workforce. Full article

Background: Slow transit constipation (STC) represents a refractory gastrointestinal disorder with limited therapeutic options. Deglycosylated azithromycin (Deg-AZM) is a small molecule Transgelin agonist effective against STC, which has been approved for 2024 clinical trials. Objectives: This study comprehensively evaluated the cardiac safety (hERG inhibition), acute cardiovascular–respiratory effects, and single/repeated-dose toxicity of Deg-AZM in Beagle dogs to de-risk clinical translation. Methods: Using automated patch-clamp (hERG-HEK293 cells; 0.1–1000 μM), telemetric monitoring in Beagles (3/8/24 mg/kg; Latin square design), and GLP-compliant toxicity studies (single-dose: 150–300 mg/kg; 28-day: 5–50 mg/kg/day), we assessed functional, biochemical, histopathological, and toxicokinetic parameters. Results: Deg-AZM showed negligible hERG inhibition (maximum 21.3% at 1000 μM). Transient PR prolongation (24 mg/kg; resolved by 4 h) and respiratory rate reduction (8–24 mg/kg; resolved by 2 h) occurred at supratherapeutic doses. Single-dose toxicity revealed one mortality at 300 mg/kg (acute cardiac ischemia), while 28-day studies identified fully reversible myocardial vacuolation at 50 mg/kg. Toxicokinetics demonstrated dose-proportional exposure (AUC and C_max) and low accumulation (accumulation factors ≤ 1.5). No hematological, coagulation, or hepatic toxicity was observed. Conclusions: With absent hERG liability and manageable transient physiological effects, Deg-AZM exhibited a favorable preclinical safety profile supporting its clinical development for STC. Full article

This paper presents the development and implementation of a shopfloor visualization-oriented digitalization framework for heterogeneous industrial equipment, aimed to enhance sustainable performance in manufacturing environments. The proposed solution addresses a critical challenge in modern industry: the integration of legacy and modern equipment into a unified, real-time monitoring and control system. In this paper, a modular and scalable architecture that enables data acquisition from equipment with varying communication protocols and technological maturity was designed and implemented, utilizing Industrial Internet of Things (IIoT) gateways, protocol converters, and Open Platform Communications Unified Architecture (OPC UA). A key contribution of this work is the integration of various data sources into a centralized visualization platform that supports real-time monitoring, anomaly detection, and performance analytics. By visualizing operational parameters—including energy consumption, machine efficiency, and environmental indicators—the system facilitates data-driven decision-making and supports predictive maintenance strategies. The implementation was validated in a real industrial setting, where the solution significantly improved transparency, reduced downtime, and contributed to measurable energy efficiency gains. This research demonstrates that visualization-oriented digitalization not only enables interoperability among heterogeneous assets, but also acts as a catalyst for achieving sustainability goals. The developed methodology and tools provide a replicable model for manufacturing organizations seeking to transition toward Industry 4.0 in a resource-efficient and future-proof manner. Full article

The transition to low-carbon energy systems requires efficient hydrogen production methods that minimise CO₂ emissions. This study presents a techno-economic assessment of hydrogen production via methane pyrolysis, utilising a novel liquid metal bubble column reactor (LMBCR) designed for CO₂-free hydrogen and solid carbon outputs. Operating at 20 bar and 1100 °C, the reactor employs a molten nickel-bismuth alloy as both catalyst and heat transfer medium, alongside a sodium bromide layer to enhance carbon purity and facilitate separation. Four operational scenarios were modelled, comparing various heating and recycling configurations to optimise hydrogen yield and process economics. Results indicate that the levelised cost of hydrogen (LCOH) is highly sensitive to methane and electricity prices, CO₂ taxation, and the value of carbon by-products. Two reactor configurations demonstrate competitive LCOHs of 1.29 $/kgH₂ and 1.53 $/kgH₂, highlighting methane pyrolysis as a viable low-carbon alternative to steam methane reforming (SMR) with carbon capture and storage (CCS). This analysis underscores the potential of methane pyrolysis for scalable, economically viable hydrogen production under specificmarket conditions. Full article

Technological advancements in computational power and algorithm design have enabled artificial intelligence to become a transformative force in microbiome research. This paper presents a concise overview of recent applications of this computational paradigm in human and animal health, with a particular emphasis on aquaculture. International projects focused on the intestinal microbiome have allowed human research to consistently dominate in terms of application cases, offering insights into various pathological conditions. In contrast, animal research has leveraged artificial intelligence in microbiome analysis to promote sustainable productivity, addressing environmental and public health concerns linked to livestock husbandry. In aquaculture, on the other hand, artificial intelligence has mainly supported management practices, improving rearing conditions and feeding strategies. When considering microbiome manipulation, however, fish farms have often relied on traditional methods, without harnessing the immense potential of artificial intelligence, whose recent applications include biomonitoring and modeling interactions between microbial communities and environmental factors in farming systems. Given the paradigm shift currently underway in both human health and animal husbandry, we advocate for a transition in the aquaculture industry toward smart farming, whose interconnected infrastructure will allow to fully leverage artificial intelligence to seamlessly integrate both biological measurements and rearing parameters. Full article

Traumatic injuries to the brain and spinal cord remain among the most challenging conditions in clinical neuroscience due to the complexity of repair mechanisms and the limited regenerative capacity of neural tissues. Nanotechnology has emerged as a transformative field, offering precise diagnostic tools, targeted therapeutic delivery systems, and advanced scaffolding platforms that are capable of overcoming the biological barriers to regeneration. This review summarizes the recent advances in nanoscale diagnostic markers, functionalized nanoparticles for drug delivery, and nanostructured scaffolds designed to modulate the injured microenvironment and support axonal regrowth and remyelination. Emerging evidence indicates that nanotechnology enables real-time, minimally invasive detection of inflammation, oxidative stress, and cellular damage, while improving therapeutic efficacy and reducing systemic side effects through targeted delivery. Electroconductive scaffolds and hybrid strategies that integrate electrical stimulation, gene therapy, and artificial intelligence further expand opportunities for personalized neuroregeneration. Despite these advances, significant challenges remain, including long-term safety, immune compatibility, the scalability of large-scale production, and translational barriers, such as small sample sizes, heterogeneous preclinical models, and limited follow-up in existing studies. Addressing these issues will be critical to realize the full potential of nanotechnology in traumatic brain and spinal cord injury and to accelerate the transition from promising preclinical findings to effective clinical therapies. Full article

This paper presents the design and implementation of a control algorithm for power converters in a microgrid, with the main objective of providing the flexibility to adjust the system inertia. The increasing integration of renewable energy sources in microgrids has driven the development of advanced control techniques to ensure stability and power quality. The proposed algorithm combines droop control, synchronverter dynamics, and virtual impedance to achieve a robust and efficient control strategy. Simulations were conducted to validate the algorithm’s performance, demonstrating its capability to maintain voltage within acceptable limits and improve the inertial response of the microgrid. The results contribute to the advancement of intelligent and resilient microgrid development, which is essential for the transition towards a more sustainable energy system. Full article

Fuel with a tight lattice structure in the reactor core is an important design direction for high-performance water reactors. Due to the dispersed flow characteristic, research on post-dryout heat transfer is limited. However, a better understanding of post-dryout heat transfer characteristics under accident conditions is significantly important for fuel design and safety analysis. This study experimentally investigates the characteristics of post-dryout dispersed flow heat transfer in a 3-rod tight-lattice bundle with a pitch-to-diameter ratio of 1.2. The working conditions are as follows: system pressure ranging from 6 to 10 MPa, mass flux between 65 to 200 kg/(m²s), and heat flux varying from 75 to 200 kW/m². Circumferentially non-uniform heat transfer is obviously observed. The wall temperature is higher in the narrow gaps between rods, while lower in the vicinity of the subchannel center. The specific mechanisms of the above phenomena are analyzed. Parametric effects on post-dryout heat transfer are discussed and illustrated. Using the experimental data, commonly utilized correlations for transition boiling and film boiling are evaluated. In order to improve the prediction accuracy, new heat transfer correlations for transition boiling and film boiling in the tight-lattice under low mass flux and low heat flux are developed based on the experimental data and mechanistic analysis. Full article

Nanofluids have long been explored for enhancing heat transfer, with early studies focusing primarily on improved thermal conductivity. However, in spray and droplet cooling applications, recent research indicates that conductivity alone cannot fully account for the observed performance gains. Additional mechanisms, such as Brownian-motion-induced convection, dynamic wetting, and nanoparticle-driven surface modification, significantly affect droplet impact dynamics, spreading behavior, boiling transitions, and transient heat transfer during impact and evaporation. This review critically synthesizes these effects, emphasizing how nanofluids interact with complex flow fields, steep thermal gradients, and heated substrates. It also examines emerging strategies for optimizing nanofluid design, including hybrid suspensions and phase-change-enhanced formulations. These developments open new avenues for high-efficiency cooling in electronics, renewable energy systems, and industrial spray processes. By moving beyond thermal conductivity as the sole performance metric, this review promotes a multi-scale, interdisciplinary framework for advancing nanofluid-based thermal technologies that align with sustainability, energy efficiency, and cost effectiveness. Full article

Energy policies and economies of scale have promoted the expansion of renewable energy sources, leading to the displacement of conventional generation units and a consequent reduction in system inertia. Low inertia amplifies frequency deviations in response to generation–load imbalances, increasing the risk of load shedding and service interruptions. To address this issue, this paper proposes a coordinated control strategy based on neuro-fuzzy networks, applied to a hybrid energy storage system (HESS) composed of batteries and supercapacitors. The controller is designed to simultaneously emulate virtual inertia and implement virtual droop control, thereby improving frequency stability and reducing reliance on spinning reserve. Additionally, a state-of-charge (SOC) management layer is integrated to prevent battery operation in critical zones, mitigating degradation and extending battery lifespan. The neuro-fuzzy controller dynamically coordinates the power exchange both among the energy storage technologies (batteries and supercapacitors) and between the HESS and the conventional generation unit, enabling a smooth and efficient transition in response to power imbalances. The proposed strategy was validated through simulations in MATLAB R2022b using a two-area power system model with parameters sourced from the literature and validated references. System performance was evaluated using standard frequency response metrics, including performance indicators (ITSE, ISE, ITAE and IAE) and the frequency nadir, demonstrating the effectiveness of the approach in enhancing frequency regulation and ensuring the operational safety of the energy storage system. Full article

Hybrid Renewable Energy Systems are pivotal for the sustainable energy transition, yet their design and operation present complex optimization challenges due to diverse components, stochastic resources, and multifaceted objectives. This systematic review formalizes the HRES optimization problem space and identifies critical research gaps. Employing the PRISMA 2020 guidelines, it comprehensively analyzes the literature (2015–2025) from Scopus, IEEE Xplore, and Web of Science, focusing on architectures, mathematical formulations, objectives, and solution methodologies. The results reveal a decisive shift from single-objective to multi-objective optimization (MOO), increasingly incorporating environmental and emerging social criteria alongside traditional economic and technical goals. Metaheuristic algorithms (e.g., NSGA-II, MOPSO) and AI techniques dominate solution strategies, though challenges persist in scalability, uncertainty management, and real-time control. The integration of hydrogen storage, vehicle-to-grid (V2G) technology, and multi-vector energy systems expands system boundaries. Key gaps include the lack of holistic frameworks co-optimizing techno-economic, environmental, social, and resilience objectives; disconnect between long-term planning and short-term operation; computational limitations for large-scale or real-time applications; explainability of AI-based controllers; high-fidelity degradation modeling for emerging technologies; and bridging the “valley of death” between simulation and bankable deployment. Future research must prioritize interdisciplinary collaboration, standardized social/resilience metrics, scalable and trustworthy AI, and validation frameworks to unlock HRESs’ potential. Full article