Search Results (67)

Biomass ashes represent a promising secondary phosphorus (P) source, yet their agronomic performance depends on feedstock origin, processing, and crop-specific interactions. This study evaluated the P fertilizer efficacy of raw and processed biomass ashes derived from cereal straw and paludiculture biomass, compared with triple superphosphate (TSP), using two sequential greenhouse pot experiments with maize, amaranth, and blue lupine. Processed ash products, particularly compacted ashes and ash–straw mixtures, increased plant biomass and P uptake to levels comparable to or exceeding those achieved with TSP. The cumulative P uptake of the three crops reached up to 250–300 mg pot⁻¹ under processed ash treatments, exceeding the uptake under TSP (≈150–180 mg pot⁻¹) and the unfertilized control (≤80 mg pot⁻¹). However, crop-specific differences were observed: amaranth benefited most from the ash products, whereas combinations of ashes with lupine were less favorable. Beside acting as a P source, processed biomass ashes also increased soil pH by about 0.5 units, improved soil aggregation by increasing macroaggregates (>2 mm) to up to 20% compared with only about 7% in TSP and the control, and promoted favorable shifts in Hedley P fractions. Soil enzyme activities were governed primarily by crop species, with amaranth stimulating phosphatase activity the most. Further research should aim to refine crop-specific application strategies for processed biomass ashes and to elucidate their impacts on soil structure and P dynamics. Full article

We study bijective maps between algebras that preserve Jordan-type products. More precisely, given algebras $\mathcal{A}$ and $\mathcal{B}$, we consider maps $\Theta :\mathcal{A}\to \mathcal{B}$ satisfying $\Theta (\mathcal{A}\mathcal{B}+\mathcal{B}\mathcal{A})=\Theta \left(\mathcal{A}\right)\Theta \left(\mathcal{B}\right)+\Theta \left(\mathcal{B}\right)\Theta \left(\mathcal{A}\right)$ or, more generally, preserving the Jordan triple product $\Theta \left(\right\{\mathcal{A},\mathcal{B},\mathcal{C}\left\}\right)=\{\Theta (\mathcal{A}),\Theta (\mathcal{B}),\Theta (\mathcal{C}\left)\right\},$ where $\{\mathcal{A},\mathcal{B},\mathcal{C}\}=\mathcal{A}\mathcal{B}\mathcal{C}+\mathcal{C}\mathcal{B}\mathcal{A}$. We first show that if $\mathcal{A}$ is a prime unital algebra with a nontrivial idempotent and $\Theta$ is a bijection of the above form, then $\Theta$ is necessarily additive. This extends known additivity results for Jordan maps and Jordan triple maps on standard operator algebras and matrix algebras. We then prove that if, in addition, both $\mathcal{A}$ and $\mathcal{B}$ are prime algebras, any bijective map preserving the Jordan triple product is either multiplicative or anti-multiplicative. Equivalently, such a map is an isomorphism or an anti-isomorphism. These results unify and generalize earlier work on Jordan maps, Jordan triple maps, and structure-preserving transformations on prime rings and standard operator algebras. Full article

As artificial intelligence (AI) advances, deep learning models are shifting from convolutional architectures to transformer-based structures, highlighting the importance of accurate floating-point (FP) calculations. Compute-in-memory (CIM) enhances matrix multiplication performance by breaking down the von Neumann architecture. However, many FPCIMs struggle to maintain high precision while achieving efficiency. This work proposes a high-precision hybrid floating-point compute-in-memory (Hy-FPCIM) architecture for Vision Transformer (ViT) through post-alignment with two different CIM macros: Bit-wise Exponent Macro (BEM) and Booth Mantissa Macro (BMM). The high-parallelism BEM efficiently implements exponent calculations in-memory with the Bit-Separated Exponent Summation Unit (BSESU) and the routing-efficient Bit-wise Max Finder (BMF). The high-precision BMM achieves nearly lossless mantissa computation in-memory with efficient Booth 4 encoding and the sensitivity-amplifier-free Flying Mantissa Lookup Table based on 12T Triple Port SRAM. The proposed Hy-FPCIM architecture achieves 23.7 TFLOPS/W energy efficiency and 0.754 TFLOPS/mm² area efficiency, with 617 Kb/mm² memory density in 28 nm technology. With almost lossless architectures, the proposed Hy-FPCIM achieves an accuracy of 81.04% in recognition tasks on the ImageNet dataset using ViT, representing a 0.03% decrease compared to the software baseline. This research presents significant advantages in both accuracy and energy efficiency, providing critical technology for complex deep learning applications. Full article

Skin scarring, including hypertrophic scars and keloids, often results from dysregulated collagen deposition during wound healing. Tropocollagen (TC), the soluble triple-helical precursor of collagen fibers, serves as the fundamental structural unit of the extracellular matrix (ECM) and plays a pivotal role in tissue repair. This review summarizes current knowledge on collagen and TC in wound healing, scar management, and regenerative dermatology. TC self-assembles into fibrils, providing structural support, while interacting with fibroblasts and growth factors such as transforming growth factor beta (TGF-β) and vascular endothelial growth factor (VEGF) to regulate ECM remodeling, angiogenesis, and tissue regeneration. Various collagen preparations, including hydrolyzed collagen, gelatin, and native fibrillar forms, differ in molecular structure, bioavailability, and therapeutic applications. Emerging strategies, including collagen- and TC-based hydrogels, nanomaterial composites, and smart wound dressings, enhance stability, targeted delivery, and clinical efficacy. Despite promising preclinical and early clinical data, standardized preparations and robust randomized trials are needed to validate TC’s therapeutic potential and optimize its application in scar prevention and wound repair. Full article

This paper introduces KG-FLoc, a knowledge graph-enhanced framework for secondary circuit fault localization in intelligent substations. The proposed KG-FLoc innovatively formalizes secondary components (e.g., circuit breakers, disconnectors) as graph nodes and their multi-dimensional relationships (e.g., electrical connections, control logic) as edges, constructing the first comprehensive knowledge graph (KG) to structurally and operationally model secondary circuits. By reframing fault localization as a knowledge graph link prediction task, KG-FLoc identifies missing or abnormal connections (edges) as fault indicators. To address dynamic topologies and sparse fault samples, KG-FLoc integrates two core innovations: (1) a relation-aware gated unit (RGU) that dynamically regulates information flow through adaptive gating mechanisms, and (2) a hierarchical graph isomorphism network (GIN) architecture for multi-scale feature extraction. Evaluated on real-world datasets from 110 kV/220 kV substations, KG-FLoc achieves 97.2% accuracy in single-fault scenarios and 93.9% accuracy in triple-fault scenarios, surpassing SVM, RF, MLP, and standard GNN baselines by 12.4–31.6%. Beyond enhancing substation reliability, KG-FLoc establishes a knowledge-aware paradigm for fault diagnosis in industrial systems, enabling precise reasoning over complex interdependencies. Full article

A series of cobalt(II) dicyanamide (dca⁻) coordination polymers with substituted pyrazines (pyz) and pyrimidines (pym) as auxiliary ligands have been synthesized and structurally characterized to investigate the influence of the type and substitution pattern of the auxiliary ligand on the dimensionality and topology of the resulting frameworks. As a result of our studies, 13 novel heteroleptic cobalt(II) dicyanamide coordination polymers were obtained, and their crystal structures were determined by single-crystal X-ray diffraction. Eight of the investigated compounds exhibit a single-chain structure composed of [Co(L_pyz/_pym)₂]²⁺ units bridged via double μ_1,5–dca ligands. In two complexes, neutral triple-chain topologies were observed, in which double μ_1,5– and single μ_1,3,5–dca bridges connect two crystallographically independent cobalt(II) ions, both being six-coordinate in tetragonally elongated octahedral environments. Two- and three-dimensional architectures were confirmed only in the case of Co(II) compounds with 2,6–Me₂pyz and 4-NH₂-pym co-ligand, respectively The cobalt(II) complexes described herein have also been compared with dicyanamide-based cobalt(II) systems incorporating pyrazine- and pyrimidine-like ligands. These structural relationships are of high significance for the rational design and synthesis of heteroleptic cobalt(II) dicyanamide systems. Full article

The complexity of fake information and the inefficiency of parameter optimization in detection models present dual challenges for current detection technologies. Therefore, this paper proposes a hybrid detection model named MIBKA-CNN-BiLSTM, which significantly improves detection accuracy and efficiency through a triple-strategy enhancement of the Black Kite Optimization Algorithm (MIBKA) and an optimized dual-channel deep learning architecture. First, three improvements are introduced in the MIBKA. The population initialization process is restructured using circle chaotic mapping to enhance parameter space coverage. The conventional random perturbation is replaced by a random-to-elite differential mutation strategy (DE/rand-to-best/1) to balance global exploration and local exploitation. Moreover, a logarithmic spiral opposition-based learning (LSOBL) mechanism is integrated to dynamically explore the opposition solution space. Second, a CNN-BiLSTM dual-channel feature extraction network is constructed, with hyperparameters such as the number of convolutional kernels and LSTM units optimized by MIBKA to enable adaptive model structure alignment with task requirements. Finally, a high-quality fake information dataset is created based on social media platforms, including CCTV. The experimental results show that our model achieves the highest accuracy on the self-built dataset, which is 3.11% higher than the optimal hybrid model. Additionally, on the Weibo21 dataset, our model’s accuracy and F1-score increased by 1.52% and 1.71%, respectively, compared to the average values of all baseline models. These findings offer a practical and effective approach for detecting lightweight and robust false information. Full article

Small island developing states (SIDS) face a dual constraint of “environmental vulnerability and energy dependence” in the context of climate change. How to achieve just energy transitions has become a core proposition for SIDS to address. This paper focuses on how SIDS can advance Sustainable Development Goal (SDG) 7 (affordable and clean energy) and Sustainable Development Goal 13 (climate action) through UNCLOS–Paris Agreement integration in energy transitions. Grounded in the theoretical framework of the Multidimensional Vulnerability Index (MVI), this research aims to construct a comprehensive analytical system that systematically examines the energy transition challenges facing SIDS and provide multi-level energy transition solutions spanning from international to domestic contexts for climate-vulnerable SIDS. The research findings reveal that SIDS face a structural predicament of “high vulnerability–low resilience” and the triple challenge of “energy–climate–development”. International climate finance is severely mismatched with the degree of vulnerability in SIDS; the United Nations Convention on the Law of the Sea (UNCLOS) and the Paris Agreement lack institutional synergy and fail to adequately support marine renewable energy development in SIDS. In response to these challenges, this study proposes multi-level solutions to promote the synergistic achievement of SDG 7 and SDG 13: at the international level, improve climate finance rules, innovate financing mechanisms, strengthen technological cooperation, and integrate relevant international legal framework; at the domestic level, optimize the layout of marine renewable energy development, construct sustainable investment ecosystems, and strengthen environmental scientific research and local data governance. Full article

In this paper, we describe the study of total triple Roman domination. Total triple Roman domination is an assignment of labels from $\{0,1,2,3,4\}$ to the vertices of a graph such that every vertex is protected by at least three units either on itself or its neighbors while ensuring that none of its neighbors remains unprotected. Formally, a total triple Roman dominating function is a function $f:V\left(G\right)\to \{0,1,2,3,4\}$ such that $f\left(N\right[v\left]\right)\ge |AN(v)|+3$, where $AN\left(v\right)$ denotes the set of active neighbors of vertex v, i.e., those assigned a positive label. We investigate the algorithmic complexity of the associated decision problem, establish sharp bounds regarding graph structural parameters, and obtain the exact values for several graph families. Full article

The Circular Economy (CE) has become an essential management model to address the environmental challenges of the traditional linear model employed by companies, protecting society and ecosystems from resource depletion and intensified ecological emissions. Thus, this study proposes a framework with recommendations for CE implementation, structured around the Triple Helix (TH) model and designed to be government-led in guiding joint actions among government, organizations, and academia. The framework comprises 21 recommendations distributed across six interconnected stages: (1) Policy Generation from Academic Inputs, (2) Development of Pilot Projects with Industry, (3) Analysis and Academic Validation of Results, (4) Policy Improvement and Scaling, (5) Promotion of Innovation and Technology Transfer, and (6) Global Connection and Replicability. These stages collectively enhance policies and practices, accelerating the transition to a CE. This framework underscores the importance of regionally adapted public policies, technological innovations to extend material lifespans, and the promotion of conscious consumption. It also emphasizes the need for intersectoral collaboration to foster sustainability and efficiency in resource management. Methodologically, this study employs an integrative review to map technical and scientific CE practices in the United Kingdom, China, and the United States. The theoretical contribution validates the TH model as a strategic tool for developing the CE. Furthermore, the practical contribution is the structured pathway to implementing the CE, detailing the main phases of collaboration among TH actors to ensure the effective operationalization of circular strategies. Full article

The development of sustainable, healthy, and resilient buildings can position Canada as a global leader in the future of construction. Reforming the building procurement process will help achieve this goal, driving innovation in construction practices. Sustainable procurement has been gaining traction in the construction sector for the past two decades. Incorporating human health impact, durability, and resiliency into the framework ensures a more holistic approach to sustainability, addressing long-term well-being, structural longevity, and adaptability to changing environmental conditions. Yet there is a need to redefine sustainable procurement guidelines for buildings by incorporating human health impact and resiliency with the triple bottom line of sustainability. The objective of this research is to develop updated framework for the sustainable procurement of institutional buildings to enhance the construction procurement process by incorporating sustainability considerations and integrating resilience, durability and long-term human health. First, a comparative evaluation of system boundaries will be performed by comparing traditional procurement (cradle-to-gate) vs. the sustainable procurement framework (cradle-to-grave) for a selected institutional building. The outcomes of the case studies highlight that the cradle-to-grave system boundary offers a clear basis for decision-making in building construction. Second, a framework will be proposed for the sustainable procurement of institutional buildings based on the published literature and ISO 20400 standard, which will support the green procurement guidelines. The outcomes of this research will help assist Canada in achieving United Nations Sustainable Development Goals. Full article

Enterotoxigenic Escherichia coli (ETEC) produces two types of enterotoxins, LTs and STs, as well as several colonization factors (CFs), including CS21, CS3 fimbriae, and flagellar structures. This study investigated how these structures contribute to ETEC colonization and the immune response in HT-29 and HuTu-80 intestinal cells. ETEC strains with single, double, and triple mutations in the lngA, cstH, and fliC genes were generated and confirmed using PCR and Western blotting. The colonization of HT-29 and HuTu-80 intestinal cells by the ETEC E9034A strain, which was fully sequenced using a hybrid approach involving both Illumina and Oxford Nanopore technologies, was used to generate the mutant and recombinant proteins. The colonization and adherence of E9034A and its mutants were assessed through colony-forming unit (CFU) counts. Cytokine levels were assessed using flow cytometry and analyzed via FlowJo 7.6.1. Quantitative analysis revealed that the absence of the lngA, cstH, and fliC genes significantly (p < 0.01) reduced ETEC adherence to HT-29 and HutU-80 cells. In addition, only ETEC strains expressing the FliC protein induced IL-8 secretion. These findings suggest that LngA, CstH, and FliC in ETEC E9034A enhance adherence to intestinal cells and trigger the release of IL-8. Full article

We studied the boron-based composite cluster B₈Al₃⁺ doped with Al atoms. The global minimum structure of the B₈Al₃⁺ cluster is a three-layer structure, consisting of three parts: an Al₂ unit, a B₈ ring and an isolated Al atom. Charge calculations analysis shows that the cluster can be expressed as [Al]⁺[B₈]²⁻[Al₂]²⁺, has 6π/6σ double aromaticity and follows the (4n+2) Hückel rule. Born–Oppenheimer molecular dynamics (BOMD) simulation shows that the B₈Al₃⁺ cluster has dynamic fluxionality properties. Remarkably, at the single-point coupled cluster singles, doubles and triples (CCSD(T)) level, the energy barrier for intramolecular rotation is merely 0.19 kcal mol⁻¹. [B₈]²⁻ molecular wheels have magical 6π/6σ double aromaticity properties, providing a continuous cloud of delocalized electrons, which is a key factor in the dynamic fluxionality of the cluster. The B₈Al₃⁺ cluster provides a new example of dynamic structural fluxionality in molecular systems. Full article

Sea surface target detectors are often interfered by various complex sea surface factors such as sea clutter. Especially when the signal-to-clutter ratio (SCR) is low, it is difficult to achieve high-performance detection. This paper proposes a triple-channel network model for maritime target detection based on the method of multi-modal data fusion. This method comprehensively improves the traditional multi-channel inputs by extracting highly complementary multi-modal features from radar echoes, namely, time-frequency image, phase sequence and correlation coefficient sequence. Appropriate networks are selected to construct a triple-channel network according to the internal data structure of each feature. The three features are utilized as the input of each network channel. To reduce the coupling between multi-channel data, the SE block is introduced to optimize the feature vectors of the channel dimension and improve the data fusion strategy. The detection results are output by the false alarm control unit according to the given probability of false alarm (PFA). The experiments on the IPIX datasets verify that the performance of the proposed detector is better than the existing detectors in dealing with complex ocean scenes. Full article

The model error is a direct reflection of the accuracy of the model simulation. However, it is challenging to estimate the model error due to the presence of numerous uncertainties inherent to the atmospheric and soil data, as well as the structure and parameters of the model itself. This paper addresses the fundamental issue of error estimation in the simulation of soil moisture by the Variable Infiltration Capacity (VIC) model, with a particular focus on the continental United States from 2010 to 2020. The paper develops a model error estimation method based on the Triple Collocation (TC) error estimation and in situ data validation of the VIC model at different temporal and spatial scales. Furthermore, it addresses the issue of failing to consider the variability of temporal and spatial scales in model error estimations. Furthermore, it generates the standard product data on soil moisture simulation errors for the VIC model in the continental United States. The mean of the simulation error variance of the VIC model, estimated using the TC method for spatially scaled soil moisture in the continental United States, is found to be 0.0045 (m³/m³)², with a median value of 0.0042 (m³/m³)². The mean time-scale error variance of the VIC model, validated using ground station data, is 0.0096 (m³/m³)², with a median value of 0.0078 (m³/m³)². Concurrently, the paper employs Köppen climate classification and land cover data as supplementary data, conducting a comprehensive investigation and analysis of the characteristics and alterations of the VIC model error in the study area from both temporal and spatial perspectives. The findings indicate a proclivity for reduced error rates during the summer months and elevated rates during the winter, with lower rates observed in the western region and higher rates in the eastern region. The objective of this study is twofold: firstly, to conduct a quantitative assessment and analysis of the VIC model’s simulation capabilities; secondly, to validate the accuracy and quality of the soil moisture products simulated by the model. The accurate estimation of model errors is a fundamental prerequisite for the numerical simulation and data assimilation of models, which has a vast range of applications in numerical meteorological and hydrological forecasting, natural environment monitoring, and other fields. Full article