Complex Interactions Research Articles

Associations between Dynamic-Contrast enhanced MRI with histopathological features in cholangiocarcinoma.

The associations between histopathology and imaging remain elusive and investigating underlying reasons of tumor microstructure resulting in an imaging phenotype is of clinical importance. The present study used cross-sectional guided biopsy specimen to employ the exact spatial biopsy localization to correlate the prebioptic magnetic resonance imaging (MRI) with immunohistochemical stainings of the histopathological specimen. Twenty-seven patients with mass-forming cholangiocarcinoma (CCA) were included in the present analysis. All patients were imaged by a 1.5 T clinical scanner at last one month before the biopsy. The contrast enhanced dynamic sequences were analyzed with quantified signal intensities. The bioptic specimen were obtained by cross-sectional guided biopsy and was further analyzed with cell density, proliferation index (Ki67), tumor-infiltrating lymphocytes, tumor-stroma ratio as well as Collagen. There were no statistically significant correlations between the signal intensities of the MRI with cell count, tumor-stroma ratio, Ki67 index and CD45 count. Only a moderate correlation was identified between relative signal intensities of the venous phase with the Collagen-stained area (r=0.40, p=0.04). DCE MRI is not associated with histopathology features in CCA. The complex interactions of the tumor and the tumor micromilieu are not reflected by the MRI phenotype.

The Jyndevad Experiment: Revealing long-term interactions between liming and phosphorus fertilization in a coarse sand soil

The Jyndevad field experiment, initiated in 1942 on a coarse sand soil in South of Denmark, explores the effect of four liming levels (0, 4, 8 and 12 Mg lime ha−1). These were in 1944 combined with two levels of mineral phosphorus (P) fertilizer (0 and 15.6 kg P ha−1 year−1), with or without a high initial dose of 156 kg mineral P ha−1. This study assesses interactions between liming and P fertilization on soil pH, Olsen-P contents and barley yields covering the last three decades. Annual P application improved barley yield regardless of liming, but the optimal liming level differed from year to year. This emphasizes the need for long-term field experiments to detect the complex interactions between liming and P availability on crop performance. The initial high P dose in 1944 and annual P fertilization increased Olsen-P contents in soil. The unlimed soil with pH(CaCl2) values below 4 had the highest Olsen-P content. The Jyndevad Experiment now harbors wide gradients in soil P (Olsen-P contents: 9–82 mg P kg−1 soil) and pH (3.6–6.9), providing a unique research platform for future studies on interactions between liming and P fertilization on coarse sand soils. We present a selection of studies that have used the Jyndevad Experiment to illustrate the research potential of the experiment.

Bioaerosols and VOC emissions from landfill leachate treatment processes: Regional differences and health risks

The landfill leachate treatment process (LLTP) is a crucial anthropogenic source of bioaerosols and volatile organic compounds (VOCs) with potential environmental impacts and on-site health risks to plant workers. However, factors influencing microbial aerosol and VOC emissions remain poorly understood. We sampled and analyzed bioaerosols and VOCs in two process sections (oxidation ditch [OD] and reverse osmosis membrane [RO]) of LLTPs in northern (NLF) and southern (SLF) China. Bioaerosol concentrations were highest in OD, and particle size predominantly ranged from 0.654.7 µm. Microbial community analysis revealed distinct differences between geographical locations and process sections, with 332 genera identified. Genera such as Paenibacillus, Bacillus, and Pseudomonas were prevalent at all sampling sites. Oxygen-containing compounds (e.g., acetophenone and propionic acid) were the dominant VOCs, particularly in SLF-OD. Network analysis showed complex interactions, with Sphingomonas and ketones playing central roles in microbial and VOC communities, respectively. Partial least squares (PLS) modeling indicated a significant correlation between bioaerosols and VOCs. Specific microorganisms, such as TK10, Adhaeribacter, and Lachnospiraceae, were major contributors to emissions of hazardous VOCs (e.g., toluene and styrene). The ozone-generation potential and olfactory effect of the OD were significantly higher than those of RO; and those of SLF were higher than those of NLF. Health risk assessments indicated potential chronic toxicity and cancer risks associated with VOC exposure to specific compounds, such as trichloroethylene. Bioaerosol exposure occurred primarily through inhalation, particularly in male workers. This study establishes a theoretical foundation for the prevention and control of air-phase pollutant risks associated with LLTPs.

A novel variant BCL11B mutation in a pediatric patient with difficult‐to‐treat eosinophilic esophagitis

AbstractEosinophilic esophagitis (EoE) is an immunoinflammatory disease of the esophagus attributable to a complex interaction between genetic and environmental factors. While several genetic risk variants have been linked with EoE, we report a novel association between B‐cell lymphoma/leukemia 11B genetic mutation in a child with dysmorphic facies, developmental delays, atopic comorbidities, and difficult‐to‐treat EoE. After a prolonged course of EoE and multiple esophagogastroduodenoscopies with biopsies, this patient achieved clinical and histologic remission on a combination of swallowed topical steroids and high‐dose proton pump inhibitor (PPI) therapy. However, her EoE relapsed when we attempted to wean her off PPI, and it was finally controlled after adding PPI back to her regimen. This report underscores the importance of genetic testing in patients with unusual clinical features and difficult‐to‐treat EoE. Relevant to real‐world clinical practice, this case also raises the question of the treatment goals in children with EoE and underlying genetic mutation(s).

Gut Microbiota and Metabolic Alterations Associated with Heart Failure and Coronary Artery Disease.

This study investigates the role of gut microbiota in cardiovascular diseases, with an additional focus on pro-atherogenic metabolites. We use advanced network analysis and machine learning techniques to identify key microbial features linked to coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF). This cross-sectional study included 189 participants divided into three groups: coronary artery disease (n = 93), heart failure with reduced ejection fraction (n = 43), and controls (n = 53). Assessments included physical exams, echocardiography, dietary surveys, blood analysis, and fecal analysis. Gut microbiota composition was analyzed using next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR). Statistical analysis methods for testing hypotheses and correlations, alpha and beta-diversity analyses, co-occurrence networks, and machine learning were conducted using Python libraries or R packages with multiple comparisons corrected using the Benjamini-Hochberg procedure. Significant gut microbiota alterations were observed, with higher Bacillota/Bacteroidota ratios in CAD and HFrEF groups compared to controls (p < 0.001). Significant differences were observed in α-diversity indices (Pielou, Chao1, Faith) between disease groups and controls (p < 0.001). β-diversity analyses also revealed distinct microbial profiles (p = 0.0015). Interestingly, trimethylamine N-oxide (TMAO) levels were lower in CAD and HFrEF groups compared to controls (p < 0.05), while indoxyl sulfate (IS) levels were comparable between the study groups. Co-occurrence network analysis and machine learning identified key microbial features linked to these conditions, highlighting complex interactions within the gut microbiota associated with cardiovascular disease.

Microbial community composition and co-occurrence network analysis of the rhizosphere soil of the main constructive tree species in Helan Mountain of Northwest China

To understand the microbial diversity and community composition within the main constructive tree species, Picea crassifolia, Betula platyphylla, and Pinus tabuliformis, in Helan Mountain and their response to changes in soil physicochemical factors, a high throughput sequencing technology was used to analyze the bacterial and fungal diversity and community structure. RDA (Redundancy Analysis) and Pearson correlation analysis were used to explore the influence of soil physicochemical factors on microbial community construction, and co-occurrence network analysis was conducted on the microbial communities. The results showed that the fungal and bacterial diversity was highest in B. platyphylla, and lowest in P. crassifolia. Additionally, the fungal/bacterial richness was greatest in the rhizosphere soils of P. tabuliformis and B. platyphylla. RDA and Pearson correlation analysis revealed that NN (nitrate nitrogen) and AP (available phosphorus) were the main determining factors of the bacterial community, while NN and SOC (soil water content) were the main determining factors of the fungal community. Pearson correlation analysis between soil physicochemical factors and the alpha diversity of the microbial communities revealed a significant positive correlation between pH and the bacterial and fungal diversity, while SOC, TN (total nitrogen), AP, and AN (available nitrogen) were significantly negatively correlated with the bacterial and fungal diversity. Co-occurrence network analysis revealed that the soil bacterial communities exhibit richer network nodes, edges, greater diversity, and greater network connectivity. Indicating that bacterial communities exhibit more complex and stable interaction patterns in soil. This study reveals the complex interactive relationship between microbial communities and soil physicochemical factors in forest ecosystems. By analyzing the response of rhizosphere microbial communities of major tree species in Helan Mountain to nutrient dynamics and pH changes, we can deepen our understanding of the role of microorganisms in regulating ecosystem functions and provide theoretical basis for soil improvement and ecological restoration strategies.

Phylogenomic Analysis and Functional Characterization of the APETALA2/Ethylene-Responsive Factor Transcription Factor Across Solanaceae.

The AP2/ERF family constitutes one of the largest groups of transcription factors in the Solanaceae. AP2/ERF contributes to various plant biological processes, including growth, development, and responses to various stresses. The origins and functional diversification of AP2/ERF within the Solanaceae family remain poorly understood, primarily because of the complex interactions between whole-genome duplications (WGDs) and tandem duplications. In this study, a total of 1282 AP2/ERF proteins are identified from 7 Solanaceae genomes. The amplification of AP2/ERF genes was driven not only by WGDs but also by the presence of clusters of tandem duplicated genes. The conservation of synteny across different chromosomes provides compelling evidence for the impact of the WGD event on the distribution pattern of AP2/ERF genes. Distinct expression patterns suggest that the multiple copies of AP2/ERF genes evolved in different functional directions, catalyzing the diversification of roles among the duplicated genes, which was of great significance for the adaptability of Solanaceae. Gene silencing and overexpression assays suggest that ERF-1 members' role in regulating the timing of floral initiation in C. annuum. Our findings provide insights into the genomic origins, duplication events, and function divergence of the Solanaceae AP2/ERF.

Spatial-temporal graph neural networks for groundwater data.

This paper introduces a novel application of spatial-temporal graph neural networks (ST-GNNs) to predict groundwater levels. Groundwater level prediction is inherently complex, influenced by various hydrological, meteorological, and anthropogenic factors. Traditional prediction models often struggle with the nonlinearity and non-stationary characteristics of groundwater data. Our study leverages the capabilities of ST-GNNs to address these challenges in the Overbetuwe area, Netherlands. We utilize a comprehensive dataset encompassing 395 groundwater level time series and auxiliary data such as precipitation, evaporation, river stages, and pumping well data. The graph-based framework of our ST-GNN model facilitates the integration of spatial interconnectivity and temporal dynamics, capturing the complex interactions within the groundwater system. Our modified Multivariate Time Graph Neural Network model shows significant improvements over traditional methods, particularly in handling missing data and forecasting future groundwater levels with minimal bias. The model's performance is rigorously evaluated when trained and applied with both synthetic and measured data, demonstrating superior accuracy and robustness in comparison to traditional numerical models in long-term forecasting. The study's findings highlight the potential of ST-GNNs in environmental modeling, offering a significant step forward in predictive modeling of groundwater levels.

Modelling the present and future of Phrynosoma orbiculare habitat and wildfire distribution and their environmental niche overlap in Mexico

Wildfires are natural phenomena that have shaped ecosystems and maintained biodiversity for millions of years. However, the increased frequency and severity of wildfires in recent decades are predominantly attributed to human activities. These anthropogenic factors, including land use change, climate change, and fire suppression, have disrupted the natural fire regime and heightened the risk of large-scale, destructive wildfires. Reptiles, as ectothermic and often slow-moving animals, are particularly vulnerable to the effects of fires due to their limited mobility and reliance on specific microhabitats. Understanding the impacts of wildfires on reptile populations is crucial for their effective conservation and management in fire-prone areas. This paper focuses on Phrynosoma orbiculare, a species distributed across the northern and southeastern regions of Mexico, where wildfires are common. The study revealed that key environmental variables driving the distribution of P. orbiculare include altitude, temperature extremes, and forest composition, while fire occurrence is strongly influenced by climatic conditions such as temperature and precipitation. As fires become more frequent and severe, the niche overlap between P. orbiculare and fire-prone regions is expected to expand. These findings highlight the importance of integrating fire management into conservation planning, particularly for protecting fire-sensitive ecosystems like Abies forests. Understanding the complex interaction between fire and species distributions is essential for developing effective conservation strategies that ensure the survival of P. orbiculare and other fire-sensitive species in Mexico’s changing landscapes.

Therapy-Related Myeloid Neoplasms: Complex Interactions among Cytotoxic Therapies, Genetic Factors, and Aberrant Microenvironment.

Therapy-related myeloid neoplasm (t-MN), characterized by its association with prior exposure to cytotoxic therapy, remains poorly understood and is a major impediment to long-term survival even in the era of novel targeted therapies due to its aggressive nature and treatment resistance. Previously, cytotoxic therapy-induced genomic changes in hematopoietic stem cells were considered sine qua non in pathogenesis; however, recent research demonstrates a complex interaction between acquired and hereditary genetic predispositions, along with a profoundly senescent bone marrow (BM) microenvironment. We review emerging data on t-MN risk factors and explore the intricate interplay among clonal hematopoiesis, genetic predisposition, and the abnormal BM microenvironment. Significance: t-MN represents a poorly understood blood cancer with extremely poor survival and no effective therapies. We provide a comprehensive review of recent preclinical research highlighting complex interaction among emerging therapies, hereditary and acquired genetic factors, and BM microenvironment. Understanding the risk factors associated with t-MN is crucial for clinicians, molecular pathologists, and cancer biologists to anticipate and potentially reduce its incidence in the future. Moreover, better understanding of the molecular pathogenesis of t-MN may enable preemptive screening and even intervention in high-risk patients.

Zebrafish: A Versatile Animal Model in Biomedical Research

Zebrafish (Danio rerio) has emerged as a powerful animal model in biomedical research, offering a unique combination of genetic tractability, rapid development, and conserved gene function with humans. This review highlights the significance of zebrafish in understanding various human diseases, including neurodegenerative disorders, metabolic disorders, cancer, and more. The zebrafish genome, with over 70% similarity to the human genome, allows for the modelling of human diseases with high fidelity. The ease of genetic manipulation, high fecundity, and low maintenance costs make zebrafish an attractive model for large-scale genetic screens and drug discovery. Zebrafish models of neurodegenerative diseases, such as Parkinson's disease, Alzheimer's disease, and Huntington's disease, have been developed, providing insights into disease mechanisms and potential therapeutic targets. Similarly, zebrafish models of metabolic disorders, including diabetes, dyslipidaemia, and atherosclerosis, have been established, enabling the study of disease pathogenesis and prevention strategies.The zebrafish has also been used to model various types of cancer, including leukaemia, melanoma, and pancreatic cancer, facilitating the discovery of novel oncogenes and tumor suppressors. The transparent nature of zebrafish embryos and larvae allows for in vivo imaging of cancer cells, enabling the study of cancer cell behavior and response to therapy. Furthermore, zebrafish has been used to investigate brain-to-organ communication, cell transplantation, and cell-cell interactions, providing insights into the complex interactions between different tissues and organs. The development of novel tools, such as CRISPR/Cas9 genome editing and single-cell RNA sequencing, has further expanded the capabilities of zebrafish research.

Intratumoral CXCL12 Gradients Contextualize Tumor Cell Invasion, Migration and Immune Suppression in Breast Cancer.

Although the CXCL12/CXCR4 pathway has been prior investigated for its prometastatic and immuno- suppressive roles in the tumor microenvironment, evidence on the spatiotemporal regulation of these hallmarks has been lacking. Here, we demonstrate that CXCL12 forms a gradient specifically around cancer cell intravasation doorways, also known as Tumor Microenvironment of Metastasis (TMEM) doorways, thus facilitating the chemotactic translocation of prometastatic tumor cells expressing CXCR4 toward the perivascular TMEM doorways for subsequent entry into peripheral circulation. Fur- thermore, we demonstrate that the CXCL12-rich micro-environment around TMEM doorways may cre- ate immunosuppressive niches, whereby CD8 + T cells, despite being attracted to these regions, often exhibit reduced effector functions, limiting their efficacy. While the CXCL12/CXCR4 pathway can mini- mally influence the overall composition of immune cell populations, it biases the distribution of CD8 + T cells away from TMEM doorways, justifying its prior-established role as immunosuppressive factor for CD8 + T cells. Our research suggests that the complex interactions between CXCL12 and the various tumor and immune cell types contributes not only to the completion of the initial steps of the metastatic cascade, but also offers an immunological "sanctuary" to prometastatic tumor cells homed around TMEM doorways. Overall, our study enhances our current understanding on the mechanisms, via which CXCL12 orchestrates tumor cell behavior and immune dynamics, potentially guiding future thera- peutic strategies to combat breast cancer metastasis and improve anti-tumor immunity.

Impact of Fertilization on Productivity and Nutritional Quality of Napier Varieties in Southern Mindanao, Philippines

Aims: This study investigates the effects of fertilizer application on the growth performance, proximate composition, and chlorophyll content of three Napier grass varieties (King, Pakchong, and Juncao) in Southern Mindanao, Philippines. Study Design: Utilizing a Randomized Complete Block Design with a 3x2 factorial arrangement. Place and Duration of Study: The experiment was performed at the University of Southern Mindanao Animal Production Center facilities from January to March 2023. Methodology: The three Napier grass varieties (King, Pakchong, and Juncao) was the first factor, and fertilizer application (with or without) were the second factor. Four blocks were prepared, each containing six plots, resulting in 24 plots. The fertilized plots received two applications of 150kg N/ha and 75kg N/ha of the recommended NPK fertilizer, respectively, while non-fertilized plots did not receive any fertilizer. Results: Results showed that fertilizer application significantly improved herbage yield, with fertilized plants yielding 20.25 tons per hectare compared to 15.14 tons in non-fertilized plants. Pakchong exhibited the highest yield and crude fiber content, while Juncao grass showed higher crude protein content without fertilizer. Fertilization also increased ether extract content, with Pakchong displaying the greatest response. However, nitrogen-free extract (NFE) was higher in non-fertilized plants across all varieties, indicating a complex interaction between nutrient availability and carbohydrate allocation. Conclusion: These findings underscore the importance of targeted fertilizer management to optimize both growth and nutritional quality, depending on specific production goals. The differential responses among Napier varieties suggest the potential for variety-specific fertilization strategies, which can enhance forage quality and sustainability in livestock farming. Further research is recommended to explore the long-term impacts of continuous fertilization and the underlying genetic mechanisms driving varietal differences.

Examining Complexities of Artisanal and Small-Scale Gold Mining on Buru Island, Maluku Province, Indonesia

The Artisanal and Small-scale Gold Mining (ASGM) sector is presently one of the largest global sources of anthropogenic mercury emissions. The risk of mercury pollution from ASGM in Indonesia challenges other important industries including fisheries and tourism. Environmental degradation and risks to food safety and human health are major concerns that have been realised at local scales, including on Buru Island, Indonesia. Since the discovery of gold on Buru Island in 2011 the community has undergone dramatic changes. Some of these, such as rapid wealth accumulation, have been of benefit to people involved in the industry, however, they have been marred by negative social and economic consequences including rapid inflation, reduced rice production, and changes to the social fabric. We explore the Buru Island example through over 12 years of research interest and using empirical material through a socio-legal lens. Various legislative changes and government interventions have occurred since 2011 and there are complex interactions between industry players. Currently, the mining is low key with ore being transported to ‘back yard’ processing operations while a permitting system is anticipated. There is a legacy of land degradation and contamination as a result of the mining and ore processing. Alternatives to mercury are being considered but are challenged by uncertainty about product effectiveness, potential toxicity, and a lack of processing knowledge.

Community structure of tropics emerging from spatio-temporal variations in the Intertropical Convergence Zone dynamics

The Intertropical Convergence Zone (ITCZ) is a narrow tropical belt of deep convective clouds, intense precipitation, and monsoon circulations encircling the Earth. Complex interactions between the ITCZ and local geophysical dynamics result in high climate variability, making weather forecasting and prediction of extreme rainfall or drought events challenging. We unravel the complex spatio-temporal dynamics of the ITCZ and the resulting teleconnection patterns via a novel tropical climate classification achieved using complex network analysis and community detection. We reduce the high-dimensional complex ITCZ dynamics into a simple yet insightful community structure that classifies the tropics into seven regions representing distinct ITCZ dynamics. The two largest communities, encompassing landmasses over the Northern and Southern hemispheres, are associated with coherent seasonal ITCZ dynamics and have significant long-range connections. Temporal analysis of the community structure highlights that the tropical Pacific and Atlantic Oceans communities exhibit substantial variation on multidecadal scales. Further, these communities exhibit incoherent dynamics due to atmosphere-ocean interactions driven by equatorial and coastal oceanic upwelling.

Pseudomonas fragi and Pseudomonas lundensis drove the co-spoilage in chilled pork: Insights from the metabolome

Pseudomonas fragi and Pseudomonas lundensis are key spoilage microorganisms in aerobically stored chilled meat, which had co-spoilage effect on chilled pork. However, the mechanism of co-spoilage interaction of P. fragi and P. lundensis has not been elucidated. The metabolism of nutrients in pork by mixed bacteria may differ from that by single strains. This study applied metabolomics and in vitro metabolite utilization experiment to assess the mechanism of that co-metabolize raw pork during storage. Results showed that co-spoilage group had 104 differential metabolites (histamine, N-methylhydantoin and D-gluconic acid, etc.) and 78 differential metabolites (putrescine, uracil acid and uracil, etc.) compared to P. fragi and P. lundensis group, respectively. These differential metabolites were mainly related to histidine metabolism, arginine biosynthesis, and purine. The co-spoilage effect of P. fragi and P. lundensis was related to the promotion of deamination and decarboxylation of histidine to produce histamine, the promotion of α-ketoglutarate and glutamate-mediated transamination, and the full utilization of the arginine deiminase pathway by the co-culture bacteria in the degradation of arginine to produce putrescine. In vitro experiment, co-cultures of these strains resulted in greater consumption of glucose, higher utilization activity, and promoted deamination and decarboxylation of amino acids. These findings reveal the complex and competitive interactions of co-culture of P. fragi and P. lundensis, providing insight into microbial spoilage mechanisms in chilled pork.

Activation of plant immunity through conversion of a helper NLR homodimer into a resistosome.

Nucleotide-binding domain and leucine-rich repeat (NLR) proteins can engage in complex interactions to detect pathogens and execute a robust immune response via downstream helper NLRs. However, the biochemical mechanisms of helper NLR activation by upstream sensor NLRs remain poorly understood. Here, we show that the coiled-coil helper NLR NRC2 from Nicotiana benthamiana accumulates in vivo as a homodimer that converts into a higher-order oligomer upon activation by its upstream virus disease resistance protein Rx. The cryo-EM structure of NbNRC2 in its resting state revealed intermolecular interactions that mediate homodimer formation and contribute to immune receptor autoinhibition. These dimerization interfaces have diverged between paralogous NRC proteins to insulate critical network nodes and enable redundant immune pathways, possibly to minimise undesired cross-activation and evade pathogen suppression of immunity. Our results expand the molecular mechanisms of NLR activation pointing to transition from homodimers to higher-order oligomeric resistosomes.

Investigating the impact of nanoplastics in altering the efficacy of clarithromycin antibiotics through In vitro studies

Plastics have significant global implications due to their environmental contamination from extensive use and improper disposal. Among plastic particles, nanoplastics (<1 μm) pose notable risks to organisms and ecosystems due to their high surface area, reactivity, and potential to carry environmental pollutants. This study explores the interaction between polystyrene nanoplastics (PSNPs) and clarithromycin (CLA), a broad-spectrum antibiotic, focusing on their combined impact on insulin (INS) and antibiotic-resistant (AMR) bacteria. PSNPs can adsorb CLA, leading to structural changes in insulin and affecting its physiological functions, potentially causing insulin resistance. Additionally, PSNPs reduce CLA's inhibitory effects on pathogenic bacteria, facilitating antibiotic resistance. Our research utilized UV–Vis Spectroscopy, FTIR, Fluorescence spectroscopy, and Circular dichroism (CD) spectroscopy to assess INS structural changes, alongside the Kirby-Bauer disk diffusion method for microbiological examination. The findings highlight the synergistic and antagonistic effects of PSNPs and CLA, underscoring the enhanced toxicity of CLA when adsorbed onto PSNPs and the complex interactions affecting both human health and bacterial resistance. Further studies are essential to fully understand these mechanisms and their broader implications.

Spatio-temporal and multi-mode prediction for blast furnace gas flow

The reasonable and stable distribution of blast furnace (BF) gas flow is the basis for maintaining the smooth operation of BF. Therefore, the accurate detection of the gas flow distribution is essential in the BF ironmaking process due to the direct impact on productivity, stability, and efficiency. However, there is a significant challenge to capture the complex interactions and dynamic changes of the ironmaking process by single predictive mode and two-dimensional (2D) distribution, leading to a lack of flexibility and interpretability in dealing with different abnormalities. To address this issue, a novel spatio-temporal multi-mode approach for three-dimensional (3D) BF gas flow prediction is proposed in this article. First, Pearson correlation analysis is employed to evaluate correlated variables in the spatial dimension. The precise temporal correlations among the multiple variables are matched with mutual information (MI) to extract spatio-temporal variables. Next, the spatio-temporal variables are decomposed utilizing variation mode decomposition (VMD), and the noise is removed with integrated correlation analysis and Fourier transform (FT) to identify and retain the relevant information. Finally, the MI-VMD-Informer is innovatively proposed to establish three different prediction modes based on spatio-temporal features, thus obtaining 2D and 3D gas flow distributions. The superiority of the proposed method is verified by actual BF production data.

Habitat quality assessment on the Qinghai-Tibet plateau across vegetation ecoregions using InVEST and Geodetector models

IntroductionThe Qinghai-Tibet Plateau holds a significant position in the global ecosystem, with its unique high altitude and complex geographical features fostering rich biodiversity. The plateau’s high-altitude environment and distinctive climate system significantly influence the Asian monsoon and regional hydrological cycles. Its vast glaciers and snow reserves are crucial in regulating the Asian climate. While previous studies have analyzed the habitat quality of the Qinghai-Tibet Plateau, significant variations exist across different vegetation ecoregions, warranting further investigation into these variations and their influencing factors.MethodsThis study conducted a comprehensive assessment of habitat quality on the Qinghai-Tibet Plateau by analyzing the impacts of human activities, climate change, and grazing intensity. Using the InVEST Model and Geodetector Model, we evaluated habitat quality across the plateau’s six vegetation ecoregions from 2000 to 2020. The efficacy of ecological red-line policies in actual conservation efforts was also examined.ResultsThe results indicate that habitat quality among vegetation ecoregions is shaped by a complex interaction of geographical and human-induced factors, leading to notable spatiotemporal variations. From 2000 to 2020, the quality of habitats was significantly impacted by human activities, climate change, grazing intensity, and land-use changes. These effects were especially prominent during the period from 2005 to 2010.DiscussionThe changes in habitat quality on the Qinghai-Tibet Plateau are influenced by multiple driving factors, with significant differences in the drivers across various vegetation ecoregions. The ecological redline policy has played an important role in protecting the ecological environment in key areas, particularly in regions with high human intervention, where its effectiveness is more pronounced. In future ecological management, it is essential to strengthen conservation measures based on regional specificity. By comprehensively considering the impact of human activities and natural factors, developing more targeted management strategies is crucial for improving habitat quality.