Search Results (2,592)

Maintaining a stable melt flow index (MFI) is a critical objective in industrial polypropylene production because MFI directly reflects polymer molecular weight and strongly influences downstream processing performance. Although the effects of catalyst formulation and hydrogen concentration on polypropylene properties are well established, the operational origins of residual fluctuations in MFI under highly stable industrial conditions remain poorly understood. In this work, the relationships between feedstock quality, process operation, and residual MFI variability were investigated during the production of a commercial polypropylene grade in an industrial gas-phase reactor. A dataset comprising 61 industrial observations was assembled by integrating laboratory quality measurements with operational variables related to hydrogen concentration, catalyst management, reactor hydrodynamics, thermal behavior, productivity, and fouling. In parallel, the concentrations of key catalyst inhibitors, including carbon oxides, sulfur compounds, water, oxygen, acetylene, methylacetylene, propadiene, arsine, and phosphine, were quantified before and after the use of a modified zeolite-based purification system. The purification process reduced catalyst poisons to ppb levels, producing polymer-grade propylene with monomer purity exceeding 99.95 wt.%. Under these highly controlled conditions, the production campaign exhibited remarkable quality stability, with an average MFI of 3.03 g/10 min and a coefficient of variation of only 6.63%. Principal component analysis revealed that two dominant operational domains could describe 86.49% of the total process variability. The first domain was associated with reactor hydrodynamics, fouling behavior, and thermal conditions, whereas the second domain was governed by catalyst-system variables and hydrogen-mediated chain-transfer mechanisms. Variable importance in projection analysis identified Plate Fouling Factor (VIP = 2.17), Production Rate (VIP = 1.33), and H₂/C₃ Ratio (VIP = 1.17) as the variables most strongly associated with residual MFI fluctuations. The results demonstrate that once feedstock-related disturbances are effectively minimized, residual MFI variability arises from interactions among the hydrodynamic, thermal, and catalytic operational domains rather than from a single controlling parameter. These findings provide new insights into process–quality relationships in industrial polypropylene manufacturing and establish a practical framework for identifying the operational origins of subtle fluctuations in polymer quality in highly stabilized production systems. Full article

Water Resources Plans (WRPs) are foundational policy instruments globally, yet implementation rates remain persistently low. Without consistent action classification, policymakers cannot define what to measure, track outcomes systematically, or generate evidence for adaptive learning. This study develops and validates a comprehensive typology of water resources actions, positioning it as a foundational framework for systematic performance measurement and international transferability. The typology was constructed through a rigorous multi-phase methodology: initial consolidation and unification of actions from Ceará’s hydrographic plans (serving as a methodological foundation due to the state’s comprehensive participatory water resources planning process, 2021–2024), expert consensus via focal group discussions, and empirical validation across the entire Brazilian national context. Validation encompassed 53 Water Resources Plans (20 Brazilian state plans, 14 Brazilian river basin plans, and 19 international plans), achieving 99.6% applicability. The typology operationalizes action classification through 13 first-order categories and 160 subtypes, organized around the concept of ‘deliverable’—a governance-neutral principle that permits instantiation across diverse institutional arrangements. The identified action categories reflect universal principles of water management maturity recognized in international planning contexts (European Water Framework Directive, Turkish and Moroccan water governance systems), demonstrating that the typology captures generalizable patterns of adaptive planning behavior rather than Brazil-specific peculiarities. Furthermore, the typology’s governance-agnostic design—based on deliverable-centered logic rather than institutional-specific procedures—enables its adaptation to diverse water governance models, from highly decentralized (Brazil’s basin committees) to centralized systems (as in other countries). By offering a structured and comprehensive categorization, this typology functions as a valuable menu of action types for future Water Resources Plans development, ensuring a holistic consideration of potential interventions. Its dual role—as a precursor to robust indicator development and as a guide for future planning—underscores its transformative potential for both assessing past actions and informing prospective water management. Full article

Universities are increasingly expected to contribute not only to teaching and research, but also to public-sector innovation, regional development, and digitally enabled governance. This article examines how higher education institutions organize that contribution by comparing two university-based transfer architectures: Smart-EDU Hub @ SNSPA in Bucharest and the distributed transfer portfolio of RheinMain University of Applied Sciences and Arts (HSRM). Using a qualitative comparative case-study design based on the document analysis of internal strategy and regulatory documents, institutional webpages, and European policy frameworks, the study analyzes the mission framing, organizational form, program architecture, trust infra-structure, and scaling logic. The documentary analysis indicates that Smart-EDU Hub is formally presented and institutionally organized as a centralized, branded, mission-led platform that bundles conferences, courses, projects, visiting scholars, and publication channels under a recognizable public-facing identity. HSRM, by contrast, is documented as a distributed transfer portfolio linking transfer strategy, dialogue formats, digitally supported teaching, administrative digitalization, continuing education, and AI support services. The comparison should therefore be read as an analysis of formal and publicly documented transfer architectures, not as an evaluation of actual institutional performance, stakeholder experience, or societal impact. The article contributes to Administrative Sciences by conceptualizing university transfer for smart governance as a public-management and governance-design problem. It develops an analytical hybrid transfer-architecture framework in which a visible hub is combined with distributed specialist nodes, shared quality assurance, and explicit safeguards for ethics, cybersecurity, and trustworthy AI. Full article

The efficacy of working memory training (WMT) in facilitating academic achievement remains heavily debated. To resolve this efficacy paradox, the current study implemented an integrated adaptive WMT (IA-WMT) paradigm to investigate near transfer to inhibitory control (IC) and far transfer to mathematical abilities in school-age children. We assigned 89 typically developing children (M_age = 109.08 ± 3.90 months; 43 girls) to an IA-WMT group (29 students), an active control group (30 students), or a passive control group (30 students). Pretest and posttest assessments measured core working memory capacity, IC, exact calculation (EC), and approximate calculation (AC). Results revealed that six sessions of IA-WMT significantly enhanced visual–spatial and verbal working memory. Furthermore, the training induced potential near transfer to IC and asymmetric far transfer to EC, while yielding no specific gains for AC. This functional dissociation provides valuable alignment with the dual-system model of mathematical cognition. The findings suggest that far transfer may not operate as a generalized spillover effect but appears to be governed by the degree of functional overlap between trained executive processes and inherent task demands. Ultimately, organically integrated cognitive training represents a promising targeted intervention tool to facilitate cognitive and academic development during early school years. Full article

Maintaining regional landscape ecological stability and enhancing rural landscape ecosystem services are critical research priorities. This study selected Xiangxi Autonomous Prefecture (XXAP), a representative mountainous region in Southwestern (SW) China, as the case study area. This study aims to construct a rural landscape ecological risk (RLER) evaluation index system based on five-period remote sensing data (2000–2020), analyze the spatio-temporal characteristics of RLER, and provide a scientific basis for landscape ecological management and rural spatial governance. The results show that the RLERI exhibited a balanced multi-ring development trend, decreasing slightly from 0.295 in 2000 to 0.282 in 2020, suggesting a slight alleviation of overall risk. Medium-risk areas of the RLERI consistently accounted for the largest proportion (over 37%). Notably, the share of high-risk areas remained relatively stable, fluctuating narrowly between 7.98% and 8.73%. Meanwhile, high-risk areas of the landscape disturbance degree (LDD) expanded markedly from 1.87% to 10.28%. Correspondingly, high-risk areas of the landscape fragility degree (LFD) also increased significantly, rising from 0.93% to 2.8%. Spatially, RLER displayed significantly positive spatial autocorrelation, with high–high (H-H) clusters concentrated in the central-southern part and low–low (L-L) clusters distributed in the northern and southern margins, indicating pronounced spatial differentiation. In conclusion, this study provides a transferable framework for ecological risk assessment in mountainous regions. Furthermore, it underscores the importance of optimizing landscape patterns in ecologically fragile areas, strengthening ecological risk management, and mitigating ecological risks in rural settings. Full article

We characterize observability in representation learning through Platonic Projection Structures (PPS), an operator-theoretic framework for analyzing representation accessibility under partial observation. Rather than treating observable outputs as direct reflections of latent representations, PPS models observation as a geometry induced by a self-adjoint positive semidefinite operator acting on a latent Hilbert space. A system is represented as a triple $(\mathcal{H},\Pi ,O),$ where $\mathcal{H}$ denotes a latent representation space, $\Pi ⪰0$ is an observation operator, and $O\left(v\right)=⟨v,\Pi v⟩$ defines an induced scalar observable. The framework characterizes observability through the quotient geometry $\mathcal{H}/ker\left(\Pi \right),$ which represents equivalence classes of latent states that are indistinguishable under observation. From this perspective, observable behavior is governed not by latent representations themselves, but by the geometry induced through the observation operator. We show that both quantum measurement and representation inference under linear observation models can be formulated within this common operator-theoretic structure while differing in the algebraic properties of their observation operators. Within this perspective, quantum measurement serves primarily as a mathematically canonical example of projection-mediated observability. The correspondence developed in PPS is therefore structural rather than physical. Within the same framework, representation transfer and knowledge distillation can be interpreted as approximate preservation of observable geometry through the intertwining condition $\Phi {\Pi }_T\approx {\Pi }_S\Phi .$ PPS further reveals a structural limitation of output-based interpretability: latent components contained in $ker\left(\Pi \right)$ are fundamentally inaccessible from observables generated through the induced observation process. Accordingly, attribution and explanation methods inherit intrinsic constraints imposed by the observation geometry itself. We provide controlled empirical validations demonstrating kernel-invariant observability, projection-induced attribution gaps, and rank-controlled observable geometry in latent representation spaces. Overall, PPS provides a mathematically explicit characterization of observability through operator-induced quotient geometry, offering a unified perspective on representation accessibility, interpretability, and representation transfer. Full article

The development of recycled asphalt mixtures combining reduced production temperatures with adequate mechanical performance remains challenging in circular pavement engineering. This study assessed the performance-based redesign of a half-warm mix asphalt (HWMA) produced at approximately 90 °C with a very high reclaimed asphalt pavement (RAP) content and foamed bitumen, using previously validated cold recycled mixture (CRM) and hot recycled mix asphalt (HRMA) formulations as contextual benchmarks. An initial CRM-derived HWMA was evaluated to assess whether cold-recycling design logic could be transferred to half-warm production without added water or cement. Although the mixture showed satisfactory volumetric and moisture-related responses, wheel tracking identified rutting as the governing limitation. The mixture was redesigned by incorporating coarse steel slag aggregate (SSA) to correct the aggregate size distribution, reducing filler content and adjusting the added foamed bitumen while maintaining RAP and SSA at 98% of the aggregate skeleton. The combined redesign reduced the wheel-tracking slope in air from 1.25 to 0.32 mm/10³ cycles and the proportional rut depth in air from 28.1% to 10.4%. Nevertheless, the redesigned HWMA remained less rut-resistant than both benchmarks, confirming the need for further optimisation. It achieved stiffness close to the HRMA benchmark and a fatigue response compatible with base-layer application, although moisture durability requires further validation. Overall, the study demonstrates the feasibility of a sequential performance-based redesign approach for high-RAP HWMA while highlighting the need for systematic optimisation and field validation before broader implementation. Full article

Fluid injection in deep reservoirs can induce fault reactivation and seismicity, posing challenges for geothermal and subsurface energy development. This study investigates the mechanical interaction between two adjacent non-intersecting faults under fluid injection using a pseudo-three-dimensional thermo-hydro-mechanical (THM)-coupled numerical model. The results show that injection first triggers slip on F2, which then redistributes stress onto F1. The response of F1 is strongly heterogeneous: some segments are stabilized due to a decrease in Coulomb failure stress, whereas other segments are destabilized due to an increase in Coulomb failure stress. Stress-path analysis indicates that the immediate response of F1 to F2 slip is mainly governed by changes in effective normal stress and shear stress, rather than abrupt pore pressure changes on F1. These findings demonstrate that fault slip can act as a mechanical stress source that either promotes or inhibits adjacent fault reactivation. Therefore, slip-induced stress transfer should be explicitly considered when assessing fault stability in reservoirs containing multiple closely spaced faults. Full article

Background: Currently, expected goal models are tools that enable quantitative analysis in the study of conventional sports, although they have seen very little application in the Paralympic context. Objective: To present a trained expected goals model for 5-a-side blind soccer games based on an analysis of 164 offensive plays by the national team that won first place at the 2022 IBSA Copa América. The novelty of this work lies in being, to our knowledge, the first expected goals (xG) model developed for Paralympic blind football (B1): conventional xG weights cannot be transferred directly because shooting in F5 is governed by auditory orientation, the absence of an offside rule, a smaller rebound-walled pitch, and fully blind executors, so a sport-specific, reproducible and SHAP-interpretable benchmark is required where none previously existed. Materials and Methods: The SHapley Additive exPlanations library was used to analyze the data via partial dependency plots, dependency scatter plots, waterfall plots, decision plots, and SHAP heatmaps. Additionally, ten machine learning algorithms were compared, including logistic regression, random forest, extra trees, gradient boosting, XGBoost, LightGBM, CatBoost, support vector machine, k-nearest neighbors, and multilayer perceptron, using a 70/30 stratification process with fivefold stratified cross-validation to define the main hyperparameters. Results: The most consistent model was CatBoost (F1 = 0.778; AUC-ROC = 0.913; AUC-PR = 0.828; MCC = 0.729; Brier = 0.072), which allowed for independent analysis and evaluation of the dataset. The five main offensive variables were determined to be (i) distance to the goal before the shot; (ii) lateral coordinate; (iii) absolute magnitude of the shooting angle; (iv) magnitude of the progression vector; (v) proximity to the side kickboard. However, none of these variables proved to be decisive in the tournament (n = 24), a characteristic that the model captured as a significant negative contribution from the opponent variable. Conclusions: The expected goals model considered for this study serves as a starting point for further analysis of tactical variables in 5-a-side soccer for the blind. Because the model was trained on a single team in a single tournament with few positive cases, these results should be read as preliminary, hypothesis-generating tactical insights rather than validated performance estimates, and require external validation before transfer to other teams or competitions. Full article

This exploratory study examines the heterogeneous spatial evolution of cities in a fragmented non-metropolitan region of Southern Brazil and develops an original functional-symbolic typological framework that integrates functional performance and symbolic production in the classification of cities. Grounded in the theoretical contributions of Lefebvre, Santos, and Corrêa, the framework was designed by the authors to simultaneously incorporate economic, territorial, cultural, and identity-related dimensions that are typically analysed separately in conventional urban typologies. The research adopts a qualitative and inductive approach to analyse secondary data from municipalities in the state of Santa Catarina. Rather than treating urbanisation as a homogeneous process, the study conceptualises urban typologies as analytical devices capable of revealing differentiated urban trajectories, uneven capacities of territorial articulation, and distinct modes of governance in non-metropolitan contexts. The findings show that cities with similar demographic scales perform diverse social, cultural, and economic roles shaped by historically and symbolically produced spatial relations. Five urban typologies were identified: Multifunctional Metropolises, Industrial Regional Capitals, Agroindustrial Cities, Cultural Tourist Cities, and Local Centres of Basic Function. The results demonstrate that urban centrality in non-metropolitan regions is not determined solely by economic performance or demographic scale, but also by symbolic attributes such as cultural heritage, territorial identities, festivals, and religious functions. By integrating material and symbolic dimensions within a single analytical structure, the proposed framework advances the understanding of fragmented urban systems, contributes to contemporary debates on non-metropolitan urbanisation and territorial governance, and offers a transferable approach for the analysis of urban diversity beyond the Brazilian context. The findings also provide practical implications for regional planning and public policy by highlighting the role of symbolic production in shaping territorial organisation and regional influence. Full article

Grain storage is vital for a country within a framework of food sovereignty and security. It helps stabilize markets, prices, and imbalances between supply and demand. In Mexico, public storage infrastructure is almost nonexistent, having been transferred to the private sector. The objective of this article is to analyze the relationship between public storage infrastructure and distribution problems that maize producers face in Mexico. A mixed-methods analysis procedure was implemented. Semi-structured interviews were conducted with small, medium, and large distributors, selected using the snowball sampling technique. The analysis identifies a positive association between references to storage infrastructure and distribution problems in the interview materials. Additionally, Spearman’s rank correlation coefficient was applied to the counts to strengthen the analysis. The results indicated a positive and significant relationship between the variables “storage infrastructure” and “distribution problems”, but also that, around the latter, there are others: lack of government support, price fixing, guaranteed price, insecurity, production costs, and inconveniences that require attention to stabilize the maize market. Inadequate infrastructure limits storage capacity, affects grain quality, increases costs, reduces producers’ bargaining power, and contributes to price volatility. It also impacts logistics, transportation, and marketing, especially in less developed regions. Evidence suggests that public storage infrastructure is a strategic element for food security; however, its concentration and predominantly private nature generate territorial inequalities. Full article

This systematic narrative review synthesizes 42 distinct sources including peer-reviewed journal articles, selected conference papers, and policy documents to examine the role of knowledge management (KM) processes in Saudi higher education accreditation, with specific focus on the National Center for Academic Accreditation and Evaluation (NCAAA) standards. Drawing on literature published between 2005 and 2025, the review investigates how KM frameworks, including Nonaka and Takeuchi’s SECI model (socialization, externalization, combination, and internalization), may be associated with accreditation outcomes in Saudi universities. The reviewed literature suggests an association between systematic KM approaches and more effective accreditation processes; causal conclusions are not warranted given the observational and case study nature of the evidence base. Certainty of the overall evidence body is rated as low to moderate. The study reveals significant challenges, including information decentralization, inadequate training, resistance to change, and the absence of dedicated governance structures that appear to impede effective knowledge transfer during accreditation processes. A secondary sustainability coding pass identified associations between KM-driven accreditation practices and institutional sustainability, environmental sustainability, and alignment with SDG 4 (Quality Education) and SDG 16 (Strong Institutions); these findings are hypothesis-generating rather than confirmatory. It should be noted that all screening and data extraction were conducted by a sole reviewer; a post hoc validation exercise achieved Cohen’s kappa = 0.81 (95% CI: 0.72–0.90) for inclusion/exclusion decisions, providing retrospective assurance of acceptable consistency. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Full article

Hydrophobic silica aerogels are widely used as thermal-insulation materials, but the thermal decomposition of their organic surface groups may affect their stability and safety during high-temperature service. In this study, ambient-pressure-dried silica aerogels modified with trimethylsilyl, dimethylsilyl, and methylsilyl groups were prepared and denoted as TSA, DSA, and MSA, respectively, to clarify how the degree of methyl substitution in the surface modifier controls the pyrolysis behavior of hydrophobic silica aerogels. Thermogravimetric analysis at different heating rates was combined with TG-FTIR, a model-free kinetic analysis, a model-fitting analysis and thermodynamic calculation. With decreasing methyl substitution from TSA to MSA, the aerogel framework became denser, the specific surface area decreased, and the contribution of solid-phase heat transfer increased slightly. The main pyrolysis process occurred at 250–800 °C and involved multiple overlapping reactions. The average activation energies of TSA, DSA, and MSA were 241.4, 246.6, and 285.5 kJ/mol according to the Kissinger–Akahira–Sunose (KAS) method and 243.0, 248.2, and 289.0 kJ/mol according to the Flynn–Wall–Ozawa (FWO) method, respectively. The higher activation energy of MSA indicates that the more condensed silica-rich framework and lower organic methyl content improves its resistance to the main degradation process. The model-fitting analysis further suggested an A1/2 mechanism for TSA and A2/5 mechanisms for DSA and MSA. TG-FTIR further confirmed the evolution of CO₂, H₂O, CH₄, and C₂H₄ and revealed distinct gas-release behaviors among the three samples. These results demonstrate that the surface methyl-substitution structure governs the balance between hydrophobic modification, pore-structure preservation, pyrolysis resistance, and volatile-product release, providing a basis for selecting surface modifiers for thermally stable silica-aerogel insulation materials under oxygen-limited high-temperature conditions. Full article

Tesla valves have emerged as promising passive flow-regulation devices for sustainable water systems because they provide directional flow control without moving parts, external energy input, or complex maintenance requirements. This review systematically examines the fundamental mechanisms, structural evolution, and engineering applications of Tesla valves in water-related systems. The underlying rectification behavior is analyzed from the perspectives of flow separation, recirculation, jet interaction, vortex evolution, and mechanism switching under varying hydraulic conditions. Recent advances in geometric optimization, multistage configurations, three-dimensional architectures, topology optimization, and data-driven design approaches are summarized to illustrate the transition from classical Tesla geometries to next-generation passive flow-control structures. Current applications in microfluidic systems, water-quality monitoring, thermo-hydraulic devices, pressure-regulation networks, and hydraulic safety enhancement are critically reviewed. The analysis indicates that Tesla-valve performance is governed by coupled interactions among geometry, flow regime, fluid properties, and operating conditions, while multifunctional designs increasingly integrate flow regulation, mixing enhancement, heat transfer, and pressure management. Finally, key challenges related to performance standardization, realistic operating conditions, manufacturability, and system-level integration are discussed. Tesla valves are expected to play an increasingly important role in intelligent and energy-efficient water infrastructure, supporting the development of next-generation sustainable water and fluid-management systems. Full article

Agricultural karst watersheds are highly vulnerable to nutrient loss because strong surface water–groundwater (SW–GW) connectivity can rapidly transfer nitrogen and sulfur species from soils, agricultural activities, and human settlements into aquatic systems. However, the coupled behavior and contrasting controls of nitrate (NO₃⁻) and sulfate (SO₄²⁻) in such agroecosystems remain insufficiently understood, limiting effective nutrient and groundwater-quality management. In this study, a typical karst agricultural watershed in Southwest China was selected to investigate the sources, transformation processes, and transport pathways of NO₃⁻ and SO₄²⁻ under strong SW–GW interactions. During the rainy season, 44 groundwater and 40 surface water samples were collected for major hydrochemical and nitrate–sulfate stable isotope analyses. An integrated framework combining hydrochemical analysis, self-organizing maps (SOM), positive matrix factorization (PMF), and MixSIAR were used to identify dominant sources, quantify source contributions, and clarify controlling processes. The results showed that groundwater was mainly characterized by carbonate-controlled Ca-HCO₃ facies, whereas surface water exhibited higher mineralization and a shift toward Ca-SO₄ facies, indicating stronger external inputs and rapid hydrological responses. Nitrate was primarily controlled by external nitrogen inputs, with manure and sewage and soil nitrogen contributing 39–62% and 16–33%, respectively. Nitrate was also regulated by nitrification under oxic conditions, while denitrification was negligible. In contrast, sulfate was predominantly governed by geogenic processes, with sulfide oxidation contributing 63–83%, while other sources were minor. These contrasting controls resulted in distinct spatial and process behaviors: nitrate showed source-driven variability associated with agricultural and domestic inputs, whereas sulfate displayed process-driven accumulation mainly controlled by water–rock interactions. Strong SW–GW connectivity enhanced the transfer of anthropogenic nutrient signals, while subsurface mixing and buffering regulated their expression in groundwater and surface water. These findings demonstrate a clear decoupling between nitrate and sulfate controls in agricultural karst systems and provide a scientific basis for nutrient pollution control, groundwater protection, and sustainable agricultural water management in vulnerable karst regions. Full article