Search Results (10,641)

Inter-basin water transfer projects (IBWTPs) play a pivotal role in alleviating the spatiotemporal imbalances of water resources. However, their operation is exposed to multiple, highly interdependent safety risks that can significantly undermine system stability and water supply reliability. Existing studies predominantly focus on isolated risk factors or rely heavily on subjective data, which limits their ability to capture the complex interrelationships among risks and reveal their underlying propagation mechanisms. To address these limitations, this study proposes a novel risk correlation analysis framework that integrates Interpretive Structural Modeling (ISM) with copula functions. ISM is first employed as a preprocessing tool to structure expert knowledge and develop an initial risk correlation framework. It is then used to hierarchically organize the complex interrelationships among risks. Subsequently, copula functions are utilized to model nonlinear dependencies and tail behaviors among risk variables. This enables a quantitative assessment of correlation strengths and facilitates the construction of a risk topological network. An empirical case study is conducted based on the Middle Route of the South-to-North Water Diversion Project. The results reveal 13 significant correlations among six second-level risk categories. Natural risks (e.g., floods and geological hazards) are identified as the primary driving factors. They exhibit a strong positive correlation (0.6155) with engineering risks and serve as the most critical nodes for proactive risk prevention and control. Engineering risks function as central intermediary hubs in the risk transmission process, whereas water quality and economic risks are characterized as terminal endpoints. Furthermore, three principal risk propagation pathways are identified: (1) natural risks → engineering risks → economic risks; (2) natural risks → operational scheduling risks → social risks; and (3) engineering risks → water quality risks → economic risks. The resulting risk topological network demonstrates significant small-world properties, indicating highly efficient risk transmission within the system. Ultimately, this study provides a robust quantitative approach for analyzing risk interactions in complex engineering systems and enriches the theoretical framework of engineering risk management. It also identifies critical nodes and key transmission pathways for risk prevention and control in IBWTPs, thereby offering significant practical implications for operational safety. Full article

The acceleration method has been significant in past studies that sought to reduce overtime in repetitive projects. The purpose of this paper is to present a novel optimization model that minimizes total overtime hours while achieving a specified project deadline for repetitive construction projects. To achieve this objective, the study develops a dual-model algorithm. The proposed method offers unique capabilities for identifying an optimal/near-optimal schedule that minimizes overtime utilization while meeting the project deadline. The method computations are organized into two main models: (1) an optimization model that searches for and identifies an optimal schedule that minimizes the overtime hours and (2) a scheduling mdoel that presents novel algorithms to determine the project duration and start and finish times of each repetitive unit while providing the flexibility of (a) utilizing multiple crews to perform the work in an activity, (b) considering any feasible crew assignment strategy, (c) utilizing unique crew assignment strategy for each activity, and (d) complying with crew work continuity constraint. To demonstrate the application and effectiveness of the proposed method, a case study is presented to illustrate the study concept, method, and computations, and to highlight the method’s novel capabilities by comparing its results with previous algorithms in the literature. The main findings reveal that the proposed method reduces overtime utilization by at least 86.4% compared with previous models. The results demonstrate the algorithm’s effectiveness in optimizing repetitive projects and achieving stakeholder satisfaction, instilling confidence in the proposed methodology’s potential to improve project outcomes. Full article

Intermodal container terminals play a critical role in modern logistics systems, where operational efficiency and energy consumption are strongly influenced by container stacking strategies. Inefficient yard organization leads to increased reshuffling operations, which negatively affect handling time and resource utilization. Despite extensive research, the relationship between operational performance and energy consumption remains insufficiently explored under dynamic terminal conditions. This study applies a discrete-event simulation framework to evaluate the impact of alternative container stacking strategies on both operational efficiency and energy consumption. The model represents container arrivals, storage decisions, retrieval processes, and reshuffling operations over a multi-day simulation horizon. Three stacking strategies—FIFO, balanced distribution, and departure-time clustering—are analysed under identical and dynamically evolving conditions using performance indicators related to reshuffling intensity, handling efficiency, and energy consumption. The results show that stacking strategies significantly affect terminal performance, but their effectiveness depends on the structure of container flows. While FIFO achieves the lowest reshuffling intensity and energy consumption under high-load conditions, departure-time clustering improves performance in outbound-dominated scenarios. The findings also reveal a structural discrepancy between operational and energy-related performance, as non-productive movements account for a higher share of operations than of total energy consumption. The study demonstrates that container stacking should be treated as a multi-criteria decision problem, where minimizing reshuffles does not directly correspond to minimizing energy consumption. The proposed simulation-based framework provides a consistent environment for evaluating trade-offs between operational and energy-related performance under controlled dynamic conditions. Full article

Cyclin-Dependent Kinase-Like 5 (CDKL5) Deficient Disorder (CDD) is a rare X-linked developmental and epileptic encephalopathy characterized by early-onset refractory epilepsy, severe neurodevelopmental impairment, and lifelong disability. Although more than thirty anti-seizure medications are available, most CDD patients remain pharmaco-resistant. Gene-based therapies are emerging, but therapeutic development is hindered by marked clinical heterogeneity, small patient populations, and the lack of robust, translatable brain-based biomarkers for clinical trials. Genetically engineered Cdkl5 mouse models recapitulate many cognitive, behavioral, and molecular features of CDD, yet their utility is limited by the absence of overt seizures, precluding seizure-based outcome measures. Here, we establish high-definition brain network (HDBN) biomarkers using advanced diffusion MRI tractography combined with graph-theoretical analysis to quantify whole-brain network organization in Cdkl5 knockout mice. Diffusion MRI enables non-invasive mapping of axonal connectivity by leveraging anisotropic water diffusion, while high-angular-resolution acquisition overcomes key limitations of conventional diffusion tensor imaging in regions with complex fiber architecture. We demonstrate that Cdkl5 knockout mice exhibit reproducible and region-specific disruptions in brain network organization, prominently affecting the somatosensory and somatomotor cortex, hippocampus, hypothalamus, amygdala, and superior colliculus—regions implicated in cognition, learning and memory, homeostasis, anxiety, and visual–motor function. In contrast, networks within the entorhinal cortex remain largely preserved. These findings identify HDBN metrics as sensitive, non-invasive biomarkers that capture clinically relevant circuit-level abnormalities in CDD. Because diffusion MRI–based network analyses are directly translatable across species, HDBN biomarkers provide a unified framework for therapeutic evaluation in mouse models, large animals, and human clinical trials, enabling longitudinal monitoring of disease progression and treatment response. Full article

Graphitic carbon nitride (CN) is considered a promising metal-free photocatalyst due to its adjustable electronic band structure and straightforward synthesis. Nevertheless, the practical utility of pristine CN is hindered by its rapid carrier recombination rate and low electrical conductivity. In this study, we enhanced CN’s molecular structure through copolymerization with organic molecules, thereby optimizing its crystallinity, resulting in significant improvements. The optimized photocatalyst, termed CNBM, demonstrated a remarkable hydrogen evolution rate of 23.13 mmol·h⁻¹·g⁻¹, a 118-fold increase compared to CN, with an apparent quantum efficiency of 87.9% at 420 nm. This notable enhancement in photocatalytic performance can be attributed to the increased surface area, providing more active sites, and the incorporation of barbituric acid through copolymerization into the CN framework, facilitating electron delocalization. Furthermore, the enhanced crystallinity of CNBM promotes the effective separation of photogenerated electron–hole pairs. Full article

Natural resources play a fundamental role in ensuring global food security, while agricultural production itself strongly influences their demand, extraction, and availability. This article discusses natural strategies for increasing crop productivity within the framework of sustainable intensification, focusing on the integrated role of plant biostimulants and micronutrients. Both groups of substances are analyzed from a resource-oriented perspective, highlighting their potential to be derived from renewable sources, particularly agro-industrial by-products and plant biomass. Plant extracts obtained from fruit, vegetable, and cereal processing residues contain numerous bioactive compounds, including phenolics, amino acids, peptides, and organic acids, which can stimulate plant growth, improve nutrient uptake, and enhance tolerance to abiotic stress. Micronutrients such as Fe, Zn, Mn, Cu, and B are also strategic resources in crop production because they regulate key metabolic processes and influence the efficiency of macronutrient utilization. Their effectiveness, however, depends strongly on chemical form and bioavailability in soil–plant systems. The novelty of this work lies in integrating perspectives from plant physiology, coordination chemistry, and resource management to propose a conceptual framework in which plant-derived extracts and micronutrient complexes act as complementary tools supporting circular and resource-efficient agricultural systems. Full article

Several studies have shown that supplementation with 100 to 130 mg of 3-nitrooxypropanol (3-NOP)/kg diet acts as a mitigating factor of enteric CH₄ production in ruminants. From an energy perspective, this effect could indicate improved feed energy utilization. Feed additives that reduce the acetate-to-propionate molar ratio and/or CH₄ production generally increase the efficiency of feed energy utilization and can alleviate the negative impact of high ambient heat loads on ruminant productivity. In seeking to test this assumption, the impact of supplementing 3-NOP in growing–finishing diets was evaluated in 24 intact male lambs (31.92 ± 3.77 kg). The experiment lasted 61 days. Treatments consisted of supplementing a total mixed growing–finishing diet (30:70 forage-to-concentrate ratio) with zero or 115 mg 3-NOP/kg diet. Lambs were assigned to 12 pens (two lambs/pen, six replicates per treatment). The temperature–humidity index (THI) during the experiment averaged 83.37 ± 6.4. The inclusion of 3-NOP tended to increase final weight (2.6%, p = 0.06) but increased dry matter intake by 10.6% (p = 0.03), thus decreasing the efficiency of dietary net energy utilization by 2.3% and 3%, respectively (p = 0.04). Lambs fed with 3-NOP showed greater (6.2%, p = 0.04) carcass weight and dressing percentage (3.3%, p = 0.03) without effects on the tissue shoulder composition. Supplemented lambs showed lower gastrointestinal (GIT) fill (9.3%, p = 0.02) and greater (1.3%) empty body weight (EBW, p < 0.01). Visceral organ mass (expressed as g/kg EBW) was not affected by 3-NOP supplementation. It was concluded that supplemental 3-NOP did not improve feed efficiency nor the efficiency of dietary energy utilization, but did improve carcass weight and dressing percentage in lambs fattened under high ambient heat load. The greater carcass weight observed in the present experiment was due mainly to a tendency for a greater final weight (p = 0.06) for 3-NOP lambs, whereas the improvement in dressing percentage was due mainly to a lower (p = 0.02) GIT fill. It is crucial to highlight that this is a pioneering study on the effect of 3-NOP on the productive efficiency of lambs subjected to high ambient heat loads. It is also important to note that enteric methane production was not measured in this experiment. Although the doses used in this experiment have consistently reduced methane production in several studies conducted under favorable climatic conditions, we cannot precisely determine the role of CH₄ production in the dietary net energy efficiency observed in lambs that received 3-NOP. The results presented here provide a basis for future research evaluating the anti-methanogenic and productive responses to the use of 3-NOP under high ambient temperature conditions. Full article

In transport and logistics systems, decision-making is increasingly influenced by uncertainty stemming from demand variability, technological disruptions, and systemic risks present in supply chains. In these contexts, organizations need approaches that are rooted in data and analysis to assess key elements affecting system resilience and performance. Although current studies widely utilize stochastic and fuzzy models for operational decision-making, there has been insufficient focus on the systematic assessment of human-centric system elements—especially competencies—as decision variables in intricate logistics systems. This research proposes an analytical framework for multi-criteria decision-making that is driven by data and aimed at evaluating the significance of various competencies that affect labor market competitiveness and the adaptability of supply chains. The approach combines expert assessment with statistical and information-theoretic metrics, utilizing Kendall’s coefficient of concordance for evaluating consistency, Shannon entropy for analyzing distributional uncertainty, and the Gini coefficient for measuring concentration. This integrated method allows for the measurement of both variability and inequality within decision frameworks in the face of uncertainty. The findings indicate that hands-on experience and professional skills play a crucial role in decision-making structures, whereas the ability to adapt to technological advancements and a commitment to ongoing learning greatly enhance system resilience. The entropy results reveal a significant degree of structural balance in the decision criteria, while the low Gini values affirm a lack of concentration, indicating a distributed and multi-dimensional decision-making environment. The study provides analytical insights into the structure and relative importance of competencies in decision-making contexts related to supply chain resilience. Full article

Integrating biochar with plant growth-promoting rhizobacteria (PGPR) is a promising strategy for sustainable soil management; however, the synergistic mechanisms governing rhizosphere microbial assembly remain inadequately understood. In this study, we investigated the combined effects of maize biochar (YM) and Bacillus amyloliquefaciens (BA) on tomato performance, soil physicochemical properties, and bacterial community dynamics via a controlled pot experiment. The results demonstrated that the synergistic treatment (YMBA) significantly enhanced tomato yield by 18.3% compared to the control, outperforming individual applications. This promotion was coupled with a comprehensive improvement in soil fertility, characterized by significant increases in soil organic matter (SOM), available nutrients (N, P, and K), and the activities of urease and acid phosphatase. High-throughput sequencing revealed that YMBA treatment significantly restructured the rhizosphere bacterial community, significantly increasing microbial richness and diversity. Notably, the synergistic application promoted the recruitment of beneficial taxa, particularly within the phylum Pseudomonadota. Mantel test analysis further elucidated that SOM and available phosphorus (AP) were the primary environmental drivers shaping the bacterial community turnover. Our findings suggest that biochar acts as a functional niche that facilitates B. amyloliquefaciens colonization and modulates the indigenous microbiota, providing a theoretical framework for utilizing cross-trophic synergies to optimize crop productivity and soil health. Full article

This study investigates the geochemical behavior and transport mechanisms of Rare Earth Elements (REEs), Yttrium (Y), Zirconium (Zr), and Hafnium (Hf) in three natural water systems under reducing conditions: the Santa Barbara and Occhio dell’Abisso mud volcanoes and a sulphureous spring at Villafranca Sicula. A comprehensive fractionation approach was applied to isolate the truly dissolved fraction (TDF < 10 kDa), the colloidal fraction (10 kDa < CF < 450 nm), the suspended particulate matter (SPM > 450 nm), and the associated bottom sediments. Analytical results reveal that REE distribution is significantly influenced by redox conditions and solid–liquid interface processes. The absence of negative Cerium (Ce) anomalies and the presence of pronounced positive Europium (Eu) anomalies in the Santa Barbara and Occhio dell’Abisso waters suggest strongly reducing environments where Eu²⁺ stability is enhanced. Shale-normalized patterns indicate that, while SPM and sediment fractions often exhibit Middle REE (MREE) enrichment, linked to Mn-bearing and Fe-oxyhydroxide phases, the dissolved phase reflects dissolution processes governed by a non-CHARAC (CHarge-and-RAdius-Controlled) behavior. Furthermore, the study highlights a significant decoupling in the Zr/Hf and Y/Ho pairs. While these pairs remain coherent during magmatic processes, they undergo mutual fractionation in aqueous systems due to differential reactivity toward colloidal surfaces and organic ligands. Specifically, Zr/Hf ratios in the colloidal and dissolved fractions deviate from chondritic values, driven by the preferential scavenging of Hf onto mineral surfaces. These findings underscore the utility of REE and Zr-Hf systematics as high-resolution tracers for reconstructing water–rock interaction processes and elemental cycling in complex hydrological environments. Full article

Although numerous studies have focused on the potential application of heterotrophic nitrification–aerobic denitrification (HNAD) bacteria in wastewater treatment, research exploring their potential in aquaculture biofloc systems remains limited. In this study, a promising HNAD strain, identified as Stutzerimonas stutzeri MJ20, was isolated from mature biofloc. This strain efficiently utilized low-cost carbon sources (e.g., glucose) and small-molecule carbon sources (e.g., sodium acetate and sodium succinate). Under conditions with glucose as the carbon source, a carbon-to-nitrogen (C/N) ratio of 15, pH 6–9, temperature 25–35 °C, salinity 0–35‰, and shaker speed of 0–150 rpm, it achieved removal rates of 95–100% for NH₄⁺-N, NO₂⁻-N, and NO₃⁻-N at initial concentrations of 100 mg/L each. Even at higher concentrations (up to 200 mg/L NH₄⁺-N and 500 mg/L for both NO₂⁻-N and NO₃⁻-N), removal rates exceeded 99%. Under mixed nitrogen sources, strain MJ20 demonstrated efficient nitrogen removal, preferentially utilizing NH₄⁺-N, with only minimal and transient accumulation of nitrite and nitrate. Genomic analysis revealed that MJ20 carries key denitrification genes, including napA, nirS, norB and nosZ, and possesses complete pathways for nitrate reduction to nitrogen gas and ammonia assimilation, although typical autotrophic nitrification genes were not detected. Combined genomic data and autotrophic culture experiments indicated that, in addition to utilizing various organic carbon sources, the strain also exhibited certain autotrophic growth capabilities. Furthermore, MJ20 showed strong flocculation ability (flocculation rate > 96% within 16 h), sensitivity to multiple common antibiotics, and no toxicity to zebrafish, demonstrating favorable biosafety. In simulated seawater aquaculture wastewater with a C/N ratio of 5, it achieved a total nitrogen removal rate exceeding 94% within 72 h. These results indicate that strain MJ20 possesses comprehensive advantages, including efficient nitrogen removal, broad carbon source adaptability, strong environmental resilience, minimal accumulation of intermediate nitrogen products, excellent flocculation ability, and high biosafety. These traits highlight its potential for application in biofloc systems and in treating aquaculture tail water with a low C/N ratio. This study provides theoretical insights and practical guidance for screening HNAD bacteria suitable for biofloc systems. Full article

Fast, reliable detection methods are paramount in the fight against the spread of aquatic invasive species (AIS), and eDNA techniques provide many benefits over traditional sampling methods. AIS are spreading rapidly around the world, reshaping ecosystems, outcompeting native species, and experiencing explosive population growth. Some sources cite the Laurentian Great Lakes as the most heavily invaded freshwater system in the world. The advantages of using eDNA technology for AIS detection include: (1) it is often more sensitive, (2) it can cover much more area, (3) it is less destructive, (4) it does not require trapping of threatened species, and (5) it can be done with considerably less taxonomic training. This study was implemented to test the utility of a commercially available metabarcoding assay against a targeted, qPCR approach for the detection of four AIS in Lake Erie. We sampled eight localities monthly throughout the summer of 2024 using both techniques. Our target AIS were the bloody red shrimp Hemimysis anomala, the fishhook waterflea Cercopagis pengoi, the water flea Daphnia lumholtzi, and the gammarid scud Echinogammarus ishnus. We found that the targeted, qPCR approach was more successful at AIS detection for our four target organisms than the specific, commercially available metabarcoding assay that was used. Full article

Corn processing waste represents an abundant, renewable, and low-cost lignocellulosic resource with considerable potential for environmental remediation applications. Large quantities of residues generated during corn processing, including cobs, husks, bran, and other by-products, are produced annually and can be utilized directly as native biomass or converted through thermochemical processes into hydrochars and biochars. This systematic review provides a comparative analysis of native corn processing biomass, hydrochars produced via hydrothermal carbonization, and biochars obtained through pyrolysis, with a focus on their potential as adsorbents for the removal of organic and inorganic pollutants from soil and water systems. Particular attention is given to the influence of thermochemical conversion processes on the physicochemical properties of the materials, including surface chemistry, porosity, functional groups, and structural characteristics, which govern adsorption mechanisms such as ion exchange, electrostatic interactions, surface complexation, hydrogen bonding, and π–π interactions. Furthermore, the advantages and limitations of each material type are discussed, together with key environmental and techno-economic considerations related to their production and practical application, including indicative production costs (USD per kg of adsorbent) and cost–performance relationships in terms of adsorption capacity. By linking biomass conversion processes, material properties, and adsorption performance, this review aims to provide a comprehensive overview of corn processing waste valorization and to support the development of sustainable adsorbent materials for soil and water remediation. A total of 36 studies were included in the qualitative synthesis following PRISMA guidelines. Full article

Cancer remains a major global health challenge, characterized by abnormal cell growth and metastasis. Current limitations of conventional therapies, particularly non-specific toxicity harming healthy cells, highlight the need for more targeted approaches. Nanotechnology offers a revolutionary solution, utilizing nanoparticles (NPs) for precise drug delivery to tumor sites while minimizing off-target effects. These nanometer-scale particles enable superior binding to cancer cell membranes, the tumor microenvironment, or nuclear receptors, facilitating significantly higher local concentrations of therapeutic agents. NPs, synthesized via physical, chemical, or biological methods, are categorized as organic (organic material-based) or inorganic (metallic particle-based). Key delivery mechanisms include the Enhanced Permeability and Retention (EPR) effect and Active Transport and Retention (ATR). This review specifically examines NP applications for the most prevalent cancers in the US (2025): breast, prostate, and lung. Gold and magnetic NPs show significant promise for early breast cancer detection. For lung cancer, polymeric NPs like PCL, PLA, and PLGA are effective carriers for peptides, proteins, and nucleic acids. BIND-014, a docetaxel-loaded NP formulation, represents an emerging strategy for prostate cancer. Clinically established examples include liposomal doxorubicin and albumin-bound paclitaxel. We comprehensively discuss the synthesis methods, delivery mechanisms, and the current landscape of NPs in research and clinical trials for these cancers. This analysis underscores the potential of nanotechnology to provide more effective and targeted therapeutic options for cancer patients in the future. A distinctive feature of this review is its comparative cancer-specific analysis of NP platforms in breast, prostate, and lung cancers. Unlike previous generalized reviews, this work integrates synthesis strategies, delivery mechanisms, translational challenges, and clinically relevant formulations to provide a bench-to-bedside perspective on the future of nanomedicine in oncology. Full article

Dysregulated iron handling—including catalytic iron and ferroptosis, hepcidin–ferroportin signaling, ferritin dynamics, and neutrophil gelatinase-associated lipocalin (NGAL)-mediated siderophore transport—has been implicated in the initiation and propagation of acute kidney injury (AKI) across ischemia–reperfusion, sepsis, and nephrotoxic contexts. To provide a SANRA-aligned narrative synthesis of mechanistic and translational evidence on iron biology in AKI, clarifying biomarker readiness and therapeutic prospects while explicitly separating preclinical from human findings. PubMed, Scopus, and Web of Science (1 January 2000 to 30 September 2025), plus appraised grey literature (guidelines/registries) using predefined criteria (authority, update recency, and methodological transparency). Narrative review with comprehensive database searches, single-reviewer screening/extraction (acknowledged as a limitation), and qualitative synthesis. Evidence is organized by pathway (catalytic iron/ferroptosis, transferrin (Tf)/transferrin receptor (/TfR), ferritin/ferritin heavy chain (FtH), hepcidin–ferroportin and NGAL) and translational domain (biomarkers and therapeutics). Statements are tagged as [Preclinical] or [Human]. [Preclinical] Robust signals support roles for catalytic iron and ferroptosis, protection by iron chelation, hepcidin modulation, heme oxygenase 1 (HO-1)/FtH induction, and apotransferrin/NGAL-based strategies. [Human] Biomarkers such as NGAL show clinical utility for kidney injury detection, whereas catalytic iron assays (labile plasma iron [LPI]/bleomycin-detectable iron [BDI]) remain investigational with limited standardization. Observational links between iron-regulatory pathways and AKI risk exist, but interventional trials are sparse; dose, timing, and safety of iron-targeted strategies in defined AKI settings remain to be established. Iron-handling pathways are compelling targets for AKI prevention/mitigation, yet high-quality human trials are limited. Priorities include standardized catalytic-iron assays, biomarker-guided enrichment, and pragmatic trials of tractable interventions (e.g., peri-contrast or cardiopulmonary bypass settings). Until such evidence accumulates, recommendations beyond standard care should be avoided. Full article