Search Results (289)

This paper presents a method to model and optimize the supply chain processes for floating offshore wind turbines using a network model based on Generalized Multi-Commodity Network Flows (GMCNF). The proposed method represents production bases, base ports, installation sites, component transfer areas, and transportation routes as nodes and arcs within the network. The installation process is modeled using three transport concepts: assembling components at the base port, direct assembly and installation at the installation site, and transferring components to the installation vessel at a nearby port. These processes are expressed as a linear network model, with the objective function set to minimize total transportation and assembly costs. The optimal transportation network is derived by solving the network problem while incorporating constraints such as supply, demand, and transportation capacity. Case studies demonstrate the method’s effectiveness in optimizing the supply chain and evaluating potential new production site locations for floating foundations, considering overall supply chain optimization. Full article

This study examines the complex interactions among soil moisture, evaporation, extreme weather events, and lightning, and their influence on fire activity across the extratropical and Pan-Arctic regions. Leveraging reanalysis and remote-sensing datasets from 2000 to 2020, we applied cross-correlation analysis, a modified Mann–Kendall trend test, and assessments of interannual variability to key variables including soil moisture, fire frequency and risk, evaporation, and lightning. Results indicate a significant increase in dry days (up to 40%) and heatwave events across Central Eurasia and Siberia (up to 50%) and Alaska (25%), when compared to the 1980–2000 baseline. Upward trends have been detected in evaporation across most of North America, consistent with soil moisture trends, while much of Eurasia exhibits declining soil moisture. Fire danger shows a strong positive correlation with evaporation north of 60° N (r ≈ 0.7, p ≤ 0.005), but a negative correlation in regions south of this latitude. These findings suggest that in mid-latitude ecosystems, fire activity is not solely driven by water stress or atmospheric dryness, highlighting the importance of region-specific surface–atmosphere interactions in shaping fire regimes. In North America, most fires occur in temperate grasslands, savannas, and shrublands (47%), whereas in Eurasia, approximately 55% of fires are concentrated in forests/taiga and temperate open biomes. The analysis also highlights that lightning-related fires are more prevalent in Eastern Europe and Southeastern Asia. In contrast, Western North America exhibits high fire incidence in temperate conifer forests despite relatively low lightning activity, indicating a dominant role of anthropogenic ignition. These findings underscore the importance of understanding land–atmosphere interactions in assessing fire risk. Integrating surface conditions, climate extremes, and ignition sources into fire prediction models is crucial for developing more effective wildfire prevention and management strategies. Full article

A comprehensive paleoecological study of a forested bog located in the middle taiga subzone of northeastern European Russia was carried out. According to the ¹⁴C radiocarbon dating and botanical composition analysis, the bog began forming 8200 calibrated years ago, evolving in three stages from grassy wetlands to its current state as a pine-Sphagnum peatland. Analysis revealed substantial carbon storage (81.4 kg m⁻²) within the peat deposit. Macrocharcoal particles were consistently present throughout the peat deposits, demonstrating continuous fire activity across the bog’s developing. High charcoal particle accumulation rates occurred not only during warm periods like the Holocene thermal maximum but also during colder and wetter periods. These periods include recent centuries, when high charcoal accumulation rates are likely due to increased human activity. Statistical analysis showed significant relationships between macrocharcoal content and several peat characteristics: higher charcoal levels correlated with increased soil carbon (r = 0.6), greater aromatic compounds (r = 0.8), and elevated polycyclic aromatic hydrocarbons (r = 0.7), all with p < 0.05. These findings highlight how fire has consistently shaped this ecosystem’s development and carbon storage capacity over millennia, with apparent intensification during recent centuries potentially linked to anthropogenic influences on fire regimes in the boreal zone. Full article

Background/Objectives: Spread through air spaces (STAS) is defined as the spread of tumor cells into the parenchymal alveolar space beyond the margins of the main tumor, and it is associated with worse clinical outcomes in resected lung adenocarcinoma. This study aimed to evaluate the preoperative computed tomography (CT) findings of primary lung adenocarcinoma in surgically resected T1 cases and to compare CT findings with and without STAS. Methods: A total of 145 patients were included in this study. The following factors were evaluated on CT images: nodule type (pure ground-glass nodule [GGN], part-solid nodule, or solid nodule), margin (smooth or irregular), the presence of lobulation, spicula, cavity, calcification, central low attenuation, peripheral opacity (well-defined or ill-defined), air bronchogram, satellite lesions, pleural retraction, pulmonary emphysema, and interstitial pneumonia; CT values (maximum, minimum, and mean); volume (tumor and solid component); and diameter (tumor and solid component). CT criteria were compared between the presence and absence of STAS. Results: Lobulation and central low attenuation were significantly more frequent in patients with STAS (p < 0.05). The mean CT value, and the volume, rate, and diameter of the solid component were significantly larger in cases with STAS (p < 0.05). A multiple logistic regression analysis identified central low attenuation as an indicator of the presence of STAS (p < 0.001; odds ratio, 3.993; 95% confidence interval, 1.993–8.001). Conclusions: Quantitative and qualitative analyses are useful for differentiating between the presence and absence of STAS. Full article

Extensive wildfires and logging have affected the Russian boreal forests in recent decades. Scots pine (Pinus sylvestris L.) forests are widespread in Russia and are one of the most disturbed tree species in Siberia. However, the effects of disturbance on soil CO₂ efflux in the vast Siberian forests are still poorly understood. We used the LI 8100A infrared gas analyzer to study changes in soil CO₂ efflux into the atmosphere in mature Scots pine forests in the Siberian central taiga five–six years following fires and logging. Measurements of soil CO₂ efflux rates were performed on sites where automatic weather stations have been continuously operational since 2022, which gives us temporal patterns of meteorological fluctuations across forests with different disturbance histories. We found significant differences in soil efflux rates depending on the site and disturbance characteristics. In the undisturbed dry lichen-dominated forest, CO₂ efflux was 4.8 ± 2.1 µmol m⁻² s⁻¹, while in the wet moss-dominated forest it was 2.3 ± 1.3 µmol m⁻² s⁻¹, with soil efflux in Sphagnum sp. being twofold of that in feather moss. Both fire and logging significantly reduced CO₂ efflux, with a smaller reduction in soil CO₂ efflux observed in the moss-dominated plots (5%–40%) compared to the lichen-dominated plots (36%–55%). The soil efflux rate increased exponentially with increasing topsoil temperatures in lichen-dominated Scots pine sites, with disturbed plots showing less dependence compared to undisturbed forest. In the wet moss-dominated Scots pine forest, we found no significant dependence of soil efflux on temperature for all disturbance types. We also found a positive moderate relationship between soil efflux and forest floor depth in both lichen- and moss-dominated Scots pine forests across all the plots studied. Our findings advance the understanding of the effects of fire and logging on the carbon cycle and highlight the importance of accounting for disturbance factors in Earth system models due to changing climate and anthropogenic patterns. Full article

Timberline marks the transitions from continuous forests to sparse forests and tundra landscapes. As the spatial distribution and dynamics of timberline are closely associated with regional energy and carbon balance, mapping timberline is important to a wide range of environmental and ecological studies. However, current timberline delineation approaches remain under-developed. We proposed an automatic timberline delineation method based on a seeded region-growing segmentation technique and satellite-derived products of tree fractional cover. We applied our approach to the West Siberian Plain and Alaska treeline regions as defined by the Circumpolar Arctic Vegetation Map. The results demonstrate the effectiveness of the proposed method for the accurate delineation of the timberlines that spatially align well with very-high-resolution satellite images. Based on the delineated timberlines, we find regional-scale tree encroachment to be not as substantial as previously reported. The proposed approach can be applied to understanding climate-induced forest responses and inform forest management practices. Full article

Forest fires critically disrupt soil ecosystems by altering physicochemical properties and microbial structure-function dynamics. This study assessed short-term impacts of fire intensities (light/moderate/heavy) on microbial communities in Larix gmelinii forests one year post-fire. Using phospholipid fatty acid (PLFA) and Biolog EcoPlate analyses, we found the following: (1) fire reduced soil organic carbon (SOC), dissolved organic carbon (DOC), total nitrogen (TN), and available nitrogen/potassium (AN/AK) via pyrolytic carbon release, while heavy-intensity fires enriched available phosphorus (AP), AN, and AK through ash deposition. (2) Thermal mortality and nutrient-pH-moisture stress persistently suppressed microbial biomass and metabolic activity. Moderate fires increased taxonomic richness but reduced functional diversity, confirming “functional redundancy.” (3) Neither soil microbial biomass nor metabolic activity at the fire site reached pre-fire levels after one year of recovery. Our findings advance post-fire soil restoration frameworks and advocate multi-omics integration to decode fire-adapted functional gene networks, guiding climate-resilient forest management. Full article

Diffracted X-ray tracking (DXT) was applied to evaluate spatial heterogeneities in polyacrylamide gel networks. Diffraction spots from the (111) planes of gold nanocrystals (GNPs) encapsulated in the gels exhibited temporal motion during time-resolved X-ray diffraction measurements using a quasi-monochromatic X-ray beam. This observation indicates that the GNPs undergo rotational motion within the gel matrix. An analysis of the diffraction spot trajectories revealed that the rotational diffusion coefficient of GNPs in homogeneous gels follows a single Gaussian distribution, whereas that of heterogeneous PAAm gels, with regions of varying cross-linking density, is described by a bimodal distribution. These findings demonstrate that DXT is a powerful technique for analyzing polymer network heterogeneity. Full article

Olyokma Nature Reserve, where we conducted our research, is in Eastern Siberia in the middle taiga zone in an area characterized by continuous permafrost. This is the only protected area in the region with a complete reserve regime, where there is no human activity. Here, we studied 14 different types of water bodies located along the Olyokma River valley, 13 of which were studied for the first time. For some of the studied water bodies, a high content of biogenic elements was noted, which may be associated with the characteristics of permafrost water bodies, which are under nutrient release from permafrost thaw. The concentration of several biogenic elements, including ammonium, nitrates and phosphates, increases in the water of the lakes toward the bottom of the river valley. In the composition of various communities of these water bodies, including both planktonic and non-planktonic, we identified 246 species and varieties of microalgae. The abundance and biomass of phytoplankton, as well as the number of species, decreased down the river valley. At the same time, at the upper stations there were more diatoms; while at the stations down the valley, green algae came to the fore; and even lower down, cyanobacteria prevailed. At the lower stations, the indicators of microalgae development were minimal. In accordance with the bioindicative properties of microalgae, a decrease in the trophic status of water bodies was noted down the river valley, which, in our opinion, is a characteristic feature of the waters of an undisturbed catchment basin in the permafrost area. This indicates that the studied aquatic ecosystem changes within a set of environmental and biological indicators, that is, it exists in natural conditions for this catchment basin. Research on the territory of Olyokma Nature Reserve allowed us to obtain information on natural transformation and removal of nutrients in permafrost catchments, while excluding the likelihood of anthropogenic impact on these processes. Full article

The long-term post-fire recovery phase is a critical stage for forest ecosystems to progress toward regeneration and mature succession. During this process, soil bacteria exhibit greater environmental adaptability, rapidly driving nutrient cycling and facilitating vegetation restoration. This study investigated the community structure and diversity of soil bacteria during long-term recovery after forest fires in the cold temperate zone, focusing on soils from the 2000 fires in Daxing’anling. Soil samples were classified into Low (L), Moderate (M), and High (H) fire damage intensity, with bacterial community composition and diversity analyzed using Illumina sequencing technology. After long-term fire recovery, the contents of soil organic carbon, black carbon, total nitrogen, alkaline nitrogen, available phosphorus, and available potassium were significantly higher elevated (p < 0.05), and water content was significantly lower, compared with that in the control check (CK) group. Soil urease, fluorescein diacetate, soil acid phosphatase, and soil dehydrogenase activities were significantly higher, and soil sucrase activity was significantly lower in H. There was a significant difference in the Alpha diversity index among the groups. Compared with CK, the Shannon index was significantly increased (p < 0.05) in L, while both Chao1 and Shannon indices were significantly decreased (p < 0.05) in M and significantly higher in H than CK. The results of the PCoA showed that there was a significant difference in the Beta diversity of the bacterial community among the groups (R² = 0.60 p = 0.001). The dominant bacteria groups were Proteobacteria and Acidobacteriota, while Actinobacteria became the new dominant group during the long-term post-fire recovery. AP, WC, DOC, MBC, S-DHA, and S-SC were significantly and positively correlated with soil bacterial diversity (p < 0.05). The results of the co-occurrence network analysis showed that all groups were dominated by symbiotic relationships, with M having the highest network complexity and strongest competitive effects. This study found that the physicochemical properties of soils recovered over a long period of time after fire returned to or exceeded the unfired forest condition. The Actinobacteria phylum became a new dominant bacterial group, with stronger network complexity and competition, in the process of forest recovery after moderate fire. Full article

In this report, we document and analyze a case in which the Irkut virus (IRKV) (Mononegavirales: Rhabdoviridae) caused a fatal human case following a bat bite in June 2021. Unfortunately, the available data did not permit a detailed taxonomic classification of the carrier bat (Chiroptera). The event occurred in the southwestern part of the Sikhote-Alin mountain region (Russian Far East) covered by the Ussuri taiga forest. The symptoms of the illness began with the following: fever; pronounced psychomotor and motor agitation; tremor of the lower jaw and tongue; aphasia; dyslexia; and dysphagia. These rapidly developed, leading to a severe and fatal encephalitis. The patient was not vaccinated for rabies and did not receive rabies immunoglobulin. Using brain sections prepared from the deceased, molecular diagnostics were performed: immunofluorescence (polyclonal anti-rabies immunoglobulin) indicating the presence of the lyssavirus antigen; and RT-PCR indicating traces of viral RNA. Sectional material (brain) was used for whole-genome sequencing, resulting in a near-complete sequence of the lyssavirus genome. The obtained genomic sequence was identified as the Irkut virus. A comparative analysis of the new sequence and other currently available IRKV sequences (NCBI) revealed differences. Specifically, amino acid differences between antigenic sites in the isolate and those of the rabies vaccine strain used regionally were noted. The patient history and subsequent analysis confirm human IRKV infection following bat contact. Like other fatal cases of IRKV infection described earlier, this case occurred in the southern part of the Russian Far East. Two have occurred in the southwestern part of the Sikhote-Alin mountain region. This indicates the possible existence of an active, natural viral focus. Full article

Trichosporon austroamericanum is a recently described yeast species related to Trichosporon inkin and exclusively isolated from clinical specimens. However, its genomic features and pathogenic potential remain poorly understood. In this study, we performed whole-genome sequencing on three blood-derived isolates from patients with invasive fungal infections and comparative analyses with 13 related Trichosporon species. The three isolates yielded high-quality assemblies of 9–10 scaffolds (~21 Mb), facilitating reliable comparisons. While most species had comparable genome sizes, Trichosporon ovoides, Trichosporon coremiiforme, and Cutaneotrichosporon mucoides displayed large, fragmented genomes, suggestive of polyploidy. ANI analysis and phylogenetic trees based on ANI and single-copy orthologs supported the classification of T. austroamericanum as a distinct clade with moderate intraspecific divergence. Using the Galleria mellonella, a model for fungal pathogenicity, all T. austroamericanum strains reduced larval survival, and NIIDF 0077300 exhibited virulence comparable to T. asahii and greater than T. inkin. To explore the gene-level differences associated with pathogenicity, we performed ortholog analysis based on single-copy genes. This revealed a unique Zn(II)₂Cys₆-type transcription factor gene (OG0010545) present only in NIIDF 0077300 and T. asahii. These findings highlight the genomic diversity and infection-associated traits of T. austroamericanum, providing a framework for future functional studies. Full article

Background: T1 mapping has become a valuable technique in cardiac magnetic resonance imaging (CMR) for evaluating myocardial tissue properties. However, its quantitative accuracy remains limited by noise-related variability. Super-resolution deep learning-based reconstruction (SR-DLR) has shown potential in enhancing image quality across various MRI applications, yet its effectiveness in myocardial T1 mapping has not been thoroughly investigated. This study aimed to evaluate the impact of SR-DLR on noise reduction and measurement consistency in myocardial T1 mapping. Methods: This single-center retrospective observational study included 36 patients who underwent CMR between July and December 2023. T1 mapping was performed using a modified Look-Locker inversion recovery (MOLLI) sequence before and after contrast administration. Images were reconstructed with and without SR-DLR using identical scan data. Phantom studies using seven homemade phantoms with different Gd-DOTA dilution ratios were also conducted. Quantitative evaluation included mean T1 values, standard deviation (SD), and coefficient of variation (CV). Intraclass correlation coefficients (ICCs) were calculated to assess inter-observer agreement. Results: SR-DLR had no significant effect on mean native or post-contrast T1 values but significantly reduced SD and CV in both patient and phantom studies. SD decreased from 44.0 to 31.8 ms (native) and 20.0 to 14.1 ms (post-contrast), and CV also improved. ICCs indicated excellent inter-observer reproducibility (native: 0.822; post-contrast: 0.955). Conclusions: SR-DLR effectively reduces measurement variability while preserving T1 accuracy, enhancing the reliability of myocardial T1 mapping in both clinical and research settings. Full article

This study presents the first comprehensive examination of ¹³⁷Cs behavior in northern taiga ecosystems of the Kola Peninsula, a previously understudied region regarding radionuclide mobility. The background radioactive contamination of these ecosystems stems from global fallout and differs from more extensively studied contaminated areas. Twelve monitoring sites at varying distances from the Kola nuclear power plant were established to assess ¹³⁷Cs accumulation in dominant plant species across three forest tiers. Gamma-spectrometric measurements revealed high mobility of ¹³⁷Cs with specific activity ranging within 4.7–34.5 Bq/kg in trees, 8.4–164.8 Bq/kg in shrubs, and 15.0–94.5 Bq/kg in mosses. Notably, Ericaceae family plants demonstrated the highest accumulation capacity. ¹³⁷Cs concentrations were significantly higher at the background site (30 km from the power plant) than in the sanitary protection zone, indicating no detectable influence from the nuclear facility. Strong correlations (up to |rs| = 0.93) between bioaccumulation indicators and soil properties were found—particularly with potassium content, exchangeable cation concentration, and organic matter content—suggesting that soil characteristics primarily determine ¹³⁷Cs mobility. These findings highlight the potential risk of ¹³⁷Cs movement through food chains in northern taiga ecosystems, with bioaccumulation coefficients exceeding those of central Russian landscapes and being comparable to those of Scandinavian taiga ecosystems. Full article

Regional mapping of Above Ground Biomass Density (AGBD) using Remote Sensing data has shown high accuracy but lacks replicability at a global scale. In contrast, global models capture AGBD variability across biomes but struggle with biome-specific accuracy. To address this gap, we develop and assess the performance of a Deep Learning model for mapping AGBD at 10-m resolution using multi-source satellite data (Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI) across four biomes: Mediterranean, taiga (boreal forests), tropical rainforests, and semi-arid savannas. The model is trained and validated separately for each biome, yielding four regional models with normalized RMSEs of 0.43–0.67 and correlation coefficients (r) of 0.61–0.77 against forest inventories. We compare predictions from these models to a benchmark dataset and to a model trained on all four biomes combined. The regional models consistently outperform both, achieving better metrics than the benchmark. Additionally, an analysis of prediction drivers reveals biome-specific differences, reinforcing the importance of per-biome mapping approaches. This study highlights the advantages and limitations of regional against global modeling, creating the basis for biome-specific, replicable, scalable and multi-temporal AGBD mapping. Full article