Search Results (7,716)

Accurate model aggregation is pivotal for the efficient dispatch and control of massive distributed photovoltaic (PV) and energy storage (ES) resources. However, the lack of unified standards across equipment manufacturers results in inconsistent data formats and resolutions. Furthermore, external disturbances like noise and packet loss exacerbate the problem. The resulting data are massive, multi-source, and heterogeneous, which poses severe challenges to building effective aggregation models. To address these issues, this paper proposes a hierarchical aggregation method based on multi-source multi-scale data fusion. First, a Multi-source Multi-scale Decision Table (Ms-MsDT) model is constructed to establish a unified framework for the flexible storage and representation of heterogeneous PV-ES data. Subsequently, a two-stage fusion framework is developed, combining Information Gain (IG) for global coarse screening and Scale-based Trees (SbT) for local fine-grained selection. This approach achieves adaptive scale optimization, effectively balancing data volume reduction with high-fidelity feature preservation. Finally, a hierarchical aggregation mechanism is introduced, employing the Analytic Hierarchy Process (AHP) and a weight-guided improved K-Means algorithm to perform targeted clustering tailored to the specific control requirements of different voltage levels. Validation on an IEEE-33 node system demonstrates that the proposed method significantly improves data approximation precision and clustering compactness compared to conventional approaches. Full article

The integration of smart electricity management models in buildings is a key strategy for improving living comfort and optimizing energy efficiency. The incentive mechanisms introduced by the Italian regulatory framework for widespread self-consumption and energy communities encourage the deployment of smart management systems within Collective Self-Consumption Groups (CSGs) and Renewable Energy Communities (RECs). These mechanisms drive the search for solutions that combine occupant well-being with economic benefits, thereby fostering citizen participation in aggregation models that play a key role in the transition towards a progressively decarbonized electricity system. In this context, an optimization model for the management of residential heat pumps is proposed, aimed at identifying the best compromise between thermal comfort, electricity consumption, and economic benefits. The approach developed in the research encourages citizens to take an active role without the need for burdensome commitments and/or significant changes in their daily habits, in line with the importance that users themselves attribute to these aspects. To demonstrate the potential of the proposed approach, a case study was developed on a residential building located in Sardinia (Italy). The implementation of an optimization model aimed at simultaneously maximizing economic benefits and indoor thermal comfort is simulated. The model’s economic and energy performance is assessed and compared with the results obtained using different advanced heat pump control and management strategies. Full article

The Weishan rare earth element (REE) deposit, located in western Shandong, North China Block, is a typical carbonatite REE deposit and constitutes the third largest light REE resource in China. Its mineralization is closely related to the multi-stage evolution of a carbonatite magma–hydrothermal system. However, the mechanisms governing REE enrichment, migration, and precipitation remain insufficiently constrained from a mineralogical perspective, which hampers the understanding of the ore-forming processes and the establishment of predictive exploration models. Apatite is a pervasively developed REE phase in the Weishan deposit which occurs in multiple generations, and thus represents an ideal recorder of the magmatic–hydrothermal evolution. In this study, different generations of apatite hosted in carbonatite orebodies from the Weishan deposit were investigated using cathodoluminescence (CL), electron probe microanalysis (EPMA), and in situ LA-ICP-MS trace element analysis. Three types of apatite were identified. In paragenetic sequence, Ap-1 occurs as polycrystalline aggregates coexisting with calcite, is enriched in Na, Sr, and LREEs, and shows high (La/Yb)_N ratios, suggesting crystallization from an evolved carbonatite magma. Ap-2 and Ap-3 display typical replacement textures: both contain abundant dissolution pits and dissolution channels within the grains, which are filled by secondary minerals such as monazite and ancylite, and thus exhibit characteristic features of fluid-mediated dissolution–reprecipitation during the hydrothermal stage. Ap-2 is commonly associated with barite and strontianite, whereas Ap-3 is associated with pyrite and monazite and is characterized by relatively sharp grain boundaries with adjacent minerals. From Ap-1 to Ap-3, total REE contents decrease systematically, whereas Na, Sr, and P contents increase. All three apatite types lack Eu anomalies but display positive Ce anomalies. Discrimination diagrams involving LREE-Sr/Y and log(Ce)-log(Eu/Y) indicate that apatite in the Weishan REE deposit formed during the magmatic to hydrothermal evolution of a carbonatite, and that the dissolution of early magmatic apatite, followed by element remobilization and mineral reprecipitation, effectively records the progressive evolution of the ore-forming fluid. Full article

The six platinum group elements (PGE) are among the rarest elements in the upper continental crust of the earth. Higher values of PGE have been detected in the upper mantle and in chondrite meteorites. The PGE are siderophile and chalcophile elements and are divided into the following: (1) the Ir subgroup (IPGE) = Os, Ir, and Ru and (2) the Pd subgroup (PPGE) = Rh, Pt, and Pd. The IPGE are more refractory and less chalcophile than the PPGE. High concentrations of PGE led, in rare cases, to the formation of mineral deposits. The PGE are carried in discrete phases, the platinum group minerals (PGM), and are included as trace elements into the structure of base metal sulphides (BM), such as pentlandite, chalcopyrite, pyrite, and pyrrhotite. Similarly to PGE, the PGM are also divided into two main groups, i.e., IPGM composed of Os, Ir, and Ru and PPGM containing Rh, Pt, and Pd. The PGM occur both in mafic and ultramafic rocks and are mainly hosted in stratiform reefs, sulphide-rich lenses, and placer deposits. Presently, there are only 169 valid PGM that represent about 2.7% of all 6176 minerals discovered so far. However, 496 PGM are listed among the valid species that have not yet been officially accepted, while a further 641 are considered as invalid or discredited species. The main reason for the incomplete characterization of PGM resides in their mode of occurrence, i.e., as grains in composite aggregates of a few microns in size, which makes it difficult to determine their crystallography. Among the PGM officially accepted by the IMA, only 13 (8%) were discovered before 1958, the year when the IMA was established. The highest number of PGM was discovered between 1970 and 1979, and 99 PGM have been accepted from 1980 until now. Of the 169 PGM accepted by the IMA, 44% are named in honour of a person, typically a scientist or geologist, and 31% are named after their discovery localities. The nomenclature of 25% of the PGM is based on their chemical composition and/or their physical properties. PGM have been discovered in 25 countries throughout the world, with 64 from Russia, 17 from Canada and South Africa (each), 15 from China, 12 from the USA, 8 from Brazil, 6 from Japan, 5 from Congo, 3 from Finland and Germany (each), 2 from the Dominican Republic, Greenland, Malaysia, and Papua New Guinea each, and only 1 from Argentine, Australia, Bulgaria, Colombia, Czech Republic, England, Ethiopia, Guyana, Mexico, Serbia, and Tanzania each. Most PGM phases contain Pd (82 phases, 48% of all accepted PGM), followed, in decreasing order of abundances, by those of Pt 35 phases (21%), Rh 23 phases (14%), Ir 18 phases (11%), Ru 7 phases (4%), and Os 4 phases (2%). The six PGE forming the PGM are bonded to other elements such as Fe, Ni, Cu, S, As, Te, Bi, Sb, Se, Sn, Hg, Ag, Zn, Si, Pb, Ge, In, Mo, and O. Thirty-two percent of the 169 valid PGM crystallize in the cubic system, 17% are orthorhombic, 16% hexagonal, 14% tetragonal, 11% trigonal, 3% monoclinic, and only 1% triclinic. Some PGM are members of a solid-solution series, which may be complete or contain a miscibility gap, providing information concerning the chemical and physical environment in which the mineral was formed. The refractory IPGM precipitate principally in primitive, high-temperature, mantle-hosted rocks such as podiform and layered chromitites. Being more chalcophile, PPGE are preferentially collected and concentrated in an immiscible sulphide liquid, and, under appropriate conditions, the PPGM can precipitate in a thermal range of about 900–300 °C in the presence of fluids and a progressive increase of oxygen fugacity (fO₂). Thus, a great number of Pt and Pd minerals have been described in Ni-Cu sulphide deposits. Two main genetic models have been proposed for the formation of PGM nuggets: (1) Detrital PGM represent magmatic grains that were mechanically liberated from their primary source by weathering and erosion with or without minor alteration processes, and (2) PGM reprecipitated in the supergene environment through a complex process that comprises solubility, the leaching of PGE from the primary PGM, and variation in Eh-pH and microbial activity. These two models do not exclude each other, and alluvial deposits may contain contributions from both processes. Full article

Concrete waste generated from the demolition of structures constitutes a significant source of waste worldwide. Recycled concrete aggregates (RCA) obtained from this waste exhibit disadvantages such as high porosity and low mechanical strength; therefore, they are not used in pavement structures without improvement. This study investigates the feasibility of using RCA improved with waste-based stabilizers as highway subbase material. RCA was used as fine aggregate and blended with basalt aggregate (BA) at different replacement ratios. The mixtures were subjected to California Bearing Ratio (CBR) tests to determine the optimum RCA content. Subsequently, unconfined compressive strength (UCS) tests were conducted using calcium carbide slag (CCS) as an activator and sewage sludge ash (SSA) as pozzolanic material at various proportions. The experimental results indicated that the mixture containing 35% RCA exhibited the most favorable performance, while higher RCA contents resulted in significant reduction in CBR values. The highest UCS value was obtained in the mixture containing 30% waste additive by weight of RCA with a CCS:SSA ratio of 3:7. For this mixture, CBR reached 315%, and displacement measured in the cyclic plate loading test under a load of 35 kN was 2.5 mm. This mixture provides sustainable and mechanically suitable alternatives for highway subbase applications. Full article

Electrical curing is a viable alternative to traditional thermal curing for geopolymer materials due to its capability for rapid and internal geopolymerization. In this research, reinforced geopolymer-based composite beams were successfully fabricated at a macroscale using a binary system of fly ash (FA) and granulated blast furnace slag (GBFS). The mixture was activated with a solution of sodium silicate (Na₂SiO₃) and sodium hydroxide (NaOH) with a fixed molar ratio of 2:1 for both, and aggregate-to-binder and activator-to-binder (A/B) ratios of 2.5 and 0.7, respectively. To ensure electrical conductivity, individual fiber systems were employed, including carbon fiber (CF), steel fiber (SF), and waste wire erosion (WWE), each incorporated at a dosage of 0.5 vol.% of the total mix volume. In addition, carbon black (CB) was introduced as a conductive filler at a constant dosage of 2.0 vol.% of the binder content in selected specimens. Each beam specimen contained only one type of conductive reinforcement or filler. A total of twelve reinforced geopolymer-based composite beams with a 150 mm square section and a span of 1300 mm, with a clear span of 1200 mm, were successfully cast and reinforced based on reinforced concrete beam designs and standards, with a dominant goal of enhancing beam behavior under flexure. The beams were cured in ambient curing conditions, or using thermal curing at 80 °C for 24 h, and using electrical curing from the fresh states with a fixed voltage of 25 V. Notwithstanding a common beam size and reinforcement pattern, distinct curing methods significantly influenced beam structure properties. Peak loads were between 20.8 and 31.5 kN, initial stiffness between 1.75 and 6.09 kN/mm, and total energy absorption between 690 and 1550 kN/mm, with a post-peak energy component of between 0.12 and 0.55. Displacement-based ductility measures spanned from 3.2 to 8.1 units with a distinct improvement in electrical curing regimes, especially in the SF-reinforced specimens; this indicates that electrical curing in reinforced geopolymer composite materials works as a governing mechanism in performance rather than simply a method for enhancing the strength of materials. Full article

Soil total carbon (TC) and total nitrogen (TN) are key indicators of soil fertility and ecosystem stability, particularly in dryland agroecosystems. However, how rotational tillage combined with straw return affects aggregate formation and aggregate-associated TC and TN stabilization remains insufficiently understood. In this study, we aimed to clarify how rotational tillage affects aggregate structure, stability, and the spatial distribution of TC and TN, thereby revealing internal processes driving nutrient stabilization in dryland farming systems. A long-term field experiment was conducted at the Shenfeng site of Shanxi Agricultural University, China, including three rotational tillage systems with straw return: T1 (two years of no tillage (NT) + one year of deep tillage (DT)), T2 (two years of conventional tillage (CT) + one year of DT), and T3 (two years of DT + one year of CT). Soil aggregates were separated into total mechanical aggregate (TMA), 0.25–2 mm MA, and 2–10 mm MA, and they were further fractionated into water-stable aggregates (WM, Wm, and Wf) for TC and TN analysis. The results showed that aggregate stability, TC, and TN were positively correlated and decreased with soil depth, indicating strong surface enrichment. TC was mainly enriched in 0.25–2 mm MA, whereas TN was concentrated in 2–10 mm MA, and water-stable macroaggregates (WM) acted as the dominant reservoirs for R_C and R_N. Relative to the 2016 baseline (CK), TC in 2022 tended to be higher under rotational tillage with straw return, while NT-containing systems better maintained TN across the 0–60 cm profile. Among the treatments, T1 provided the most balanced performance, with a higher MWD and GMD, lower D, and improved aggregate-associated TC and TN retention. These findings suggest that rotational tillage with straw return, particularly the NT–NT–DT sequence, can support aggregate stability and is associated with improved aggregate-mediated TC and TN retention in the Loess Plateau dryland winter wheat system. Full article

The rapid adoption of Machine Learning (ML) in high-impact domains has intensified the need for systematic tools to assess and improve the trustworthiness of predictive models beyond conventional performance metrics. This paper presents TWEEF (Trustworthiness Estimation and Enhancement Framework), a modular and extensible framework that operationalizes trustworthiness through the joint evaluation of performance, fairness, and interpretability. TWEEF integrates intuitionistic fuzzy logic and subjective logic to transform quantitative trust-related metrics into linguistic assessments, which are subsequently aggregated using operators such as the Linguistic Weighted Average (LWA), Gaussian Weighted Aggregation (GWA), and Subjective Logic (SL). The framework extends the scikit-learn ecosystem through a meta-estimator, the TrustworthyClassifier, which orchestrates metric computation, bias-mitigation procedures, surrogate-model generation, and trust aggregation within a unified, pipeline-compatible workflow. The framework is empirically evaluated through four experiments on widely used benchmark datasets (German Credit, COMPAS, and Adult) in binary classification settings. Results show that TWEEF consistently reveals fairness and interpretability limitations that may remain hidden when relying solely on predictive performance, and that the resulting trust scores respond coherently to different metric configurations and weighting schemes. These findings indicate that TWEEF provides a structured mechanism for trust assessment and enhancement, while also offering a flexible foundation for future extensions to additional learning tasks and evaluation dimensions. Full article

This study investigated the effects of rubber substitution ratios (0%, 5%, 10%, 15%) on the frost resistance of rubber concrete with recycled brick–concrete aggregate (BRC). The freeze–thaw (F–T) damage model was established and improved, and the damage mechanism was revealed. The results showed that with the increase in rubber substitution ratio, the frost resistance indices of BRC did not improve or decline synchronously. An increase in rubber content could enhance one index, such as the relative compressive strength, but was often achieved at the expense of reductions in other indices, such as the relative dynamic elastic modulus (RDEM) and relative quality. Consequently, a single indicator was insufficient for evaluating the overall frost resistance. To address this limitation, an entropy weight-based evaluation system was developed. This system integrated the multiple indices into a unified damage score. When combined with defined damage grades, it enabled a holistic assessment of the damage state. For the nonlinear accelerated damage stage during freeze–thaw cycles, the Weibull distribution-based freeze–thaw damage model demonstrated higher prediction accuracy (R² > 0.85) compared to the conventional freeze–thaw fatigue model. The freeze–thaw damage in BRC originated from the competition between “pore deterioration and crack propagation at weak interfaces” and “the elastic buffering effect of rubber.” This study provided a reference for the frost-resistance design and freeze–thaw life prediction of BRC in cold regions. Full article

In GPS-denied environments, the spatio-temporal coupling of errors caused by dynamic network topologies poses a fundamental challenge to cooperative localization, presenting existing methods with a dilemma: approaches pursuing global optimization lack dynamic adaptability, while those focusing on local adaptation struggle to guarantee global convergence. To address this challenge, this paper proposes ST-DCL, a cooperative localization framework based on a novel principle of closed-loop spatio-temporal decoupling. The core of ST-DCL comprises two modules: a Dynamic Weighted Multidimensional Scaling (DW-MDS) optimizer, responsible for providing a globally consistent coarse estimate with provable convergence, and a specially designed Spatio-Temporal Graph Neural Network (ST-GNN) corrector, tasked with compensating for local nonlinear errors. The DW-MDS effectively suppresses interference from historical errors via an adaptive sliding window and confidence weights derived from our error propagation model. The key innovation of the ST-GNN lies in its two newly designed components: a Dynamic Topological Attention Module for actively modulating neighbor aggregation to inhibit spatial error diffusion, and a Dilated Causal Convolution Module for modeling long-term temporal dependencies to curb error accumulation. These two modules form a closed loop via a confidence feedback mechanism, working in synergy to achieve continuous error suppression. Theoretical analysis indicates that the framework exhibits bounded-error convergence under dynamic topologies. In simulations involving 200 nodes, velocities up to 50 m/s, and 15% NLOS links, the ST-DCL achieves a normalized root mean square error (NRMSE) of 0.0068, representing a 21% performance improvement over state-of-the-art methods. The practical efficacy and real-time capability are further validated through real-world flight experiments with a 10-UAV swarm in complex, GPS-denied scenarios. Full article

Chitosan hydrogels are effective wound dressings that promote healing through the synergy of chitosan’s inherent biological properties and the moist environment they maintain. We previously developed hydrogel microparticles using a highly biocompatible chitosan derivative with superior therapeutic effects. This study aimed to enhance their clinical translation for Endoscopic Sinus Surgery (ESS) by optimizing preparation conditions to achieve an extrusion force of <20 N, facilitating ergonomic, single-handed administration by surgeons. While reducing the particle size alone was insufficient to lower the extrusion force significantly, the introduction of a mechanical “kneading” process to de-agglomerate microparticle aggregates resulted in a substantial reduction in the required force from 213 ± 80 N to approximately 47 N. By further optimizing the polymer concentration to 5.0% (w/v), we successfully reduced the maximum extrusion force to below 20 N (17 ± 1 N). These results demonstrate that the optimized injectable chitosan gel microparticles achieve the practical usability required for precise surgical maneuvers during ESS. Full article

The exponential growth of data generated by modern digital applications, including systems inspired by Industrial Internet of Things (IIoT) requirements, has accelerated the adoption of NoSQL databases due to their scalability, flexibility, and performance advantages over traditional relational systems. Among document-oriented solutions, MongoDB and RavenDB stand out due to their architectural features and their ability to manage dynamic, large-scale datasets. This paper presents a comparative analysis of MongoDB and RavenDB, focusing on the performance of fundamental CRUD (Create, Read, Update, Delete) operations. To ensure a controlled performance evaluation, a mobile and web application for managing product orders was implemented as a case study inspired by IIoT data characteristics, such as high data volume and frequent transactional operations, with experiments conducted on datasets ranging from 1000 to 1,000,000 records. Beyond the core CRUD evaluation, the study also investigates advanced operational scenarios, including joint processing strategies (lookup versus document inclusion), bulk data ingestion techniques, aggregation performance, and full-text search capabilities. These complementary tests provide deeper insight into the systems’ architectural strengths and their behavior under more complex and data-intensive workloads. The experimental results highlight MongoDB’s consistent performance advantage in terms of response time, particularly with large data volumes, while RavenDB demonstrates competitive behavior and offers additional benefits such as built-in ACID compliance, automatic indexing, and optimized mechanisms for relational retrieval and bulk ingestion. The analysis does not propose a new benchmarking methodology but provides practical insights for selecting an appropriate document-oriented database for data intensive mobile and web application contexts, including IIoT-inspired data characteristics, based on a controlled single-node experimental setting, while acknowledging the limitations of a single-host experimental environment. Full article

Microalgal amendments can improve soil structure by regulating extracellular polymeric substances (EPSs). However, the mechanisms underlying this process in red soils (characterized by high clay content and susceptibility to acidification) under different farming practices remain unclear. This study examined how Chlorella vulgaris (C. vulgaris) amendment influences EPS composition to enhance soil aggregate stability under arable land and rice paddy farming. A five-month pot experiment using a completely randomized design was conducted to investigate the effects of Chlorella vulgaris amendment on soils cultivated with Pennisetum × sinese and rice, two economically important crops commonly grown in South China. At the end of the experiment, Chlorella vulgaris amendment substantially increased both the mean weight diameter (MWD) and geometric mean diameter (GMD) of soil aggregates under both farming systems. Excitation–emission matrix (EEM) fluorescence spectroscopy revealed distinct changes in soil EPS components between the two farming types. Under arable land farming, humic-like and protein-like EPSs were dominant in Chlorella vulgaris-amended treatments, with fluorescence intensities more than doubling compared to the control. Conversely, under rice paddy farming, soil fulvic acid was the main component and showed a moderate increase. Partial least squares path modeling (PLS-PM) demonstrated that protein-like and humic-like EPSs had the strongest direct effects on aggregate stability in arable land red soil, while fulvic acid was the key factor in rice paddy red soil. The present study demonstrates that Chlorella vulgaris amendment improves aggregate stability in red soils through farming-specific, EPS-mediated pathways, providing a quantitative framework for researchers and land managers seeking to apply microalgal amendments for red soil enhancement and sustainable land management. Full article

Cells are continuously exposed to physiological and environmental stressors that disrupt homeostasis, triggering adaptive mechanisms such as the integrated stress response (ISR). A central feature of ISR is the selective translation of activating transcription factor 4 (ATF4), which orchestrates gene programs essential for metabolic adaptation and survival. Stress-induced acute ATF4 expression occurs in diverse mammalian cell types and is typically protective; however, chronic activation contributes to pathologies including cancer and neurodegeneration. Canonical ISR (c-ISR) is initiated by phosphorylation of eIF2α in response to stressors such as endoplasmic reticulum or mitochondrial dysfunction, hypoxia, nutrient deprivation, and infections. This modification suppresses global protein synthesis while promoting ATF4 translation through upstream open reading frames (uORFs) in its 5′UTR. Recently, an alternative pathway, split ISR (s-ISR), enabling ATF4 translation independently of eIF2α phosphorylation, was identified in mice, suggesting ISR adaptability, though its relevance in humans remains unclear. Under normal conditions, cap-dependent translation predominates, mediated by the eIF4F complex and requiring the activity of eIF2B at its initial steps. During translational stress, eIF2α phosphorylation inhibits eIF2B activity, resulting in the formation of stalled initiation complexes, which can aggregate into stress granules (SGs). SGs sequester mRNAs and translation initiation factors, further repressing global translation, while ATF4 mRNA largely escapes sequestration, enabling selective translation. This partitioning highlights a finely tuned regulatory mechanism balancing ATF4 expression during stress. Recent advances reveal that, beyond cis-regulatory uORFs, trans-acting factors such as translation initiation factors and associated RNA-binding proteins critically influence ATF4 translation. Understanding these mechanisms provides insight into ISR plasticity and its implications for development, aging, and disease. Full article

The nasal microbiome represents a complex and dynamic microbial ecosystem that contributes to mucosal defense, epithelial homeostasis, immune regulation, and olfactory function. Increasing evidence indicates that this microbial community actively interacts with host physiology, while alterations in its composition are associated with chronic inflammation, oxidative stress, and olfactory impairment. Such changes have been reported in conditions including chronic rhinosinusitis, allergic rhinitis, and post-viral anosmia. Beyond local effects, chronic nasal inflammation has been hypothesized to influence neuroinflammatory processes and protein aggregation pathways involving α-synuclein and tau, potentially linking nasal microbial imbalance to neurodegenerative mechanisms. However, current evidence remains largely indirect and does not support a causal relationship. This narrative review summarizes current clinical and immunological evidence on the role of the nasal microbiome in olfactory function and dysfunction, highlighting limitations of existing studies and outlining future research directions. Full article