Search Results (29,864)

Amidst the escalating threat of global warming, which manifests in more frequent forest fires, the prompt and accurate detection of forest fires has ascended to paramount importance. The current surveillance algorithms employed for forest fire monitoring—including, but not limited to, fixed threshold algorithms, multi-channel threshold algorithms, and contextual algorithms—rely primarily upon the degree of deviation between the pixel temperature and the background temperature to discern pyric events. Notwithstanding, these algorithms typically fail to account for the spatial heterogeneity of the background temperature, precipitating the consequential oversight of low-temperature fire point pixels, thus impeding the expedited detection of fires in their initial stages. For the amelioration of this deficiency, the present study introduces a spatial feature-based (STF) method for forest fire detection, leveraging Himawari-8/9 imagery as the main data source, complemented by the Shuttle Radar Topography Mission (SRTM) DEM data inputs. Our proposed modality reconstructs the surface temperature information via selecting the optimally designated machine learning model, subsequently identifying the fire point through utilizing the difference between the reconstructed surface temperatures and empirical observations, in tandem with the spatial contextual algorithm. The results confirm that the random forest model demonstrates superior efficacy in the reconstruction of the surface temperature. Benchmarking the STF method against both the fire point datasets disseminated by the China Forest and Grassland Fire Prevention and Suppression Network (CFGFPN) and the Wild Land Fire (WLF) fire point product validation datasets from Himawari-8/9 yielded a zero rate of omission errors and a comprehensive evaluative index, predominantly surpassing 0.74. These findings show that the STF method proposed herein significantly augments the identification of lower-temperature fire point pixels, thereby amplifying the sensitivity of forest surveillance. Full article

The forest carbon market in Brazil presents a complex scenario filled with challenges and opportunities. This study employed SWOT analysis to evaluate the dynamics of this market, based on the perceptions of 77 specialists from various professional fields. The analysis revealed that extensive forest cover and biodiversity preservation are significant strengths that position Brazil as a potential leader in the global carbon credit market. However, weaknesses such as illegal deforestation and fragile public policies undermine the effectiveness of conservation efforts. Opportunities include the growing international demand for carbon credits and the recognition of the importance of local communities in forest conservation. Nevertheless, external threats like land conflicts and political instability pose considerable risks. The study concludes that it is crucial to strengthen public policies and regulatory frameworks, promote technological innovation, and ensure the active inclusion of local and indigenous communities to guarantee the sustainability and growth of Brazil’s forest carbon market. The research suggests that despite significant challenges, Brazil can overcome these obstacles with the implementation of effective strategies. Full article

Pinus massoniana L. is one of the most important conifer species in southern China and is the mainstay of the forest ecosystem and timber production, yet low temperatures limit its growth and geographical distribution. This study used 30-day-old seedlings from families of varying cold-tolerance to examine the morphological traits of needles and stems, chlorophyll fluorescence characteristics, protective enzymes, and changes in starch and lignin under different low-temperature stresses in an artificial climate chamber. The results showed that the seedlings of Pinus massoniana exhibited changes in phenotypic morphology and tissue structure under low-temperature stress. Physiological and biochemical indexes such as protective enzymes, osmoregulatory substances, starch, and lignin responded to low-temperature stress. The cold-tolerant family increased soluble sugars, starch grain, and lignin content as well as peroxidase activity, and decreased malondialdehyde content by increasing the levels of actual photochemical efficiency (ΦPSII), electron transport rate (ETR), and photochemical quenching (qP) to improve the cold tolerance ability. This study provides a reference for the selection and breeding of cold-tolerant genetic resources of Pinus massoniana and the mechanism of cold-tolerance, as well as the analysis of the mechanism of adaptation of Pinus massoniana in different climatic regions of China. Full article

Populus deltoides Bartr. ex Marsh. represents a valuable genetic resource for fast-growing plantations in temperate regions. It holds significant cultivation and breeding potential in northern China. To establish an efficient breeding population of poplar, we studied the genetic variation of P. deltoides from different provenances. Our focus was on genotypes exhibiting high growth rates and efficient water and nutrient use efficiency (WUE and NUE). We evaluated 256 one-year-old seedlings from six provenances, measuring height, ground diameter, total biomass, and leaf carbon and nitrogen isotope abundance (δ¹³C and δ¹⁵N). Our analytical methods included variance analysis, multiple comparisons, mixed linear models, correlation analysis, and principal component analysis. The results showed that the coefficient of variation was highest for δ¹⁵N and lowest for δ¹³C among all traits. Except for δ¹⁵N, the effects of intra- and inter-provenance were highly significant (p < 0.01). The rates of variation for all traits ranged from 78.36% to 99.49% for intra-provenance and from 0.51% to 21.64% for inter-provenance. The heritability of all traits in AQ provenance was over 0.65, and all exhibited the highest level except for seedling height. All traits were significantly positively correlated with each other (p < 0.05), while ground diameter, total biomass, and WUE were highly significantly negatively correlated with latitude (p < 0.01). After a comprehensive evaluation, two provenances and eight genotypes were selected. The genetic gains for seedling height, ground diameter, total biomass, WUE, and NUE were 27.46 cm (178-2-106), 3.85 mm (178-2-141), 16.40 g (178-2-141), 0.852‰ (LA05-N15), and 3.145‰ (174-1-2), respectively. Overall, we revealed that the abundant genetic variation in P. deltoides populations mainly comes from intra-provenance differences and evaluated provenances and genotypes. The results of this study will contribute to optimizing and enhancing the breeding process of Chinese poplar and improving the productivity of fast-growing plantations. Full article

Dirigent (DIR) genes play a pivotal role in plant development and stress adaptation. Manihot esculenta Crantz, commonly known as cassava, is a drought-resistant plant thriving in tropical and subtropical areas. It is extensively utilized for starch production, bioethanol, and animal feed. However, a comprehensive analysis of the DIR family genes remains unexplored in cassava, a crucial cash and forage crop in tropical and subtropical regions. In this study, we characterize a total of 26 cassava DIRs (MeDIRs) within the cassava genome, revealing their uneven distribution across 13 of the 18 chromosomes. Phylogenetic analysis classified these genes into four subfamilies: DIR-a, DIR-b/d, DIR-c, and DIR-e. Comparative synteny analysis with cassava and seven other plant species (Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa), soybean (Glycine max), tomato (Solanum lycopersicum), rice (Oryza sativa), maize (Zea mays), and wheat (Triticum aestivum)) provided insights into their likely evolution. We also predict protein interaction networks and identify cis-acting elements, elucidating the functional differences in MeDIR genes. Notably, MeDIR genes exhibited specific expression patterns across different tissues and in response to various abiotic and biotic stressors, such as pathogenic bacteria, cadmium chloride (CdCl₂), and atrazine. Further validation through quantitative real-time PCR (qRT-PCR) confirmed the response of DIR genes to osmotic and salt stress. These findings offer a comprehensive resource for understanding the characteristics and biological functions of MeDIR genes in cassava, enhancing our knowledge of plant stress adaptation mechanisms. Full article

With the global energy transition and advancements in electric vehicle technology, the use of pure electric heavy-duty vehicles in logistics is rising. However, current highway grade design standards do not fully consider their performance characteristics, making it urgent to establish appropriate grade limits. This study aims to explore the maximum grade and the critical length suitable for pure electric heavy-duty vehicles on highways. A co-simulation platform for pure electric heavy-duty vehicles was built using TruckSim and MATLAB/Simulink. A comparative analysis was conducted on the climbing characteristics of pure electric heavy-duty vehicles and traditional fuel-powered vehicles. Additionally, the climbing speed decay degree (DV) was introduced to investigate the speed variation characteristics of pure electric heavy-duty vehicles under the joint influence of multiple factors. These findings serve as the basis for determining the maximum grade and the critical length applicable to pure electric heavy-duty vehicles on highways. The research findings indicate that, compared to traditional fuel-powered heavy-duty vehicles, pure electric heavy-duty vehicles exhibit smoother acceleration and deceleration processes, smaller speed fluctuations, higher travel speeds, and greater equilibrium speed values during uphill climbing. The power-to-weight ratio has a greater impact on the climbing speed of pure electric heavy-duty vehicles, while the initial vehicle speed has a relatively minor effect. It was observed that the dynamic performance of pure electric heavy-duty vehicles does not align with the maximum grade stipulated by current regulations in China. These research findings provide important reference points for road longitudinal section design and vehicle management in road freight enterprises. Full article

Obesity, a significant public health concern with high prevalence in both adults and children, is a complex disorder arising from the interaction of multiple genes and environmental factors. Advances in genome-wide association studies (GWAS) and sequencing technologies have identified numerous polygenic causes of obesity, particularly genes involved in hunger, satiety signals, adipocyte differentiation, and energy expenditure. This study investigates the relationship between six obesity-related genes (CLOCK, FTO, GHRL, LEP, LEPR, MC4R) and their impact on BMI, WC, HC, WHR, and emotional eating behavior in 220 Romanian adults. Emotional eating was assessed using the validated Emotional Eating Questionnaire (EEQ). Our analysis revealed significant variability in obesity-related phenotypes and emotional eating behaviors across different genotypes. Specifically, CLOCK/CC, FTO/AA, and LEP/AA genotypes were strongly associated with higher obesity metrics and emotional eating scores, while GHRL/TT and MC4R/CC were linked to increased BMI and WHR. The interplay between genetic predisposition and emotional eating behavior significantly influenced BMI and WHR, indicating a complex relationship between genetic and behavioral factors. This study, the first of its kind in Romania, provides a foundation for targeted interventions to prevent and reduce obesity and suggests potential strategies for gene expression modulation to mitigate the effects of emotional eating. Adopting a ‘One Health’ approach by creating an evidence base derived from both human and animal studies is crucial for understanding how to control obesity. Full article

In uneven-aged forests, trees of different diameters, heights, and ages are located in a small area, which is due to the felling of individual trees or groups of trees, as well as small-scale natural disturbances. In this article, we present an objective method for classifying forest stands into even- and uneven-aged stands based on freely available low-resolution (with an average recording density of 5 points/m²) national lidar data. The canopy closure, dominant height, and canopy height diversity from the canopy height model and the voxels derived from lidar data were used to classify the forest stands. Both approaches for determining forest structural diversity (canopy height diversity—CHD_CHM and CHD_V) yielded similar results, namely two clusters of even- and uneven-aged stands, although the differences in vertical diversity between even- and uneven-aged stands were greater when using CHM. The first analysis, using CHM for the CHD assessment, estimated the uneven-aged forest area as 49.3%, whereas the second analysis using voxels estimated it as 34.3%. We concluded that in areas with low laser scanner density, CHM analysis is a more appropriate method for assessing forest stand height heterogeneity. The advantage of detecting uneven-aged structures with voxels is that we were able to detect shade-tolerant species of varying age classes beneath a dense canopy of mature, dominant trees. The CHD_CHM values were estimated to be 1.83 and 1.86 for uneven-aged forests, whereas they were 1.57 and 1.58 for mature even-aged forests. The CHD_V values were estimated as 1.50 and 1.62 for uneven-aged forests, while they were 1.33 and 1.48 for mature even-aged forests. The classification of stands based on lidar data was validated with data from measurements on permanent sample plots. Statistically significantly lower average values of the homogeneity index and higher values of the Shannon–Wiener index from field measurements confirm the success of the classification of stands based on lidar data as uneven-aged forests. Full article

Achieving the dual goals of “carbon neutrality and carbon peaking” will necessitate not only improving urban production and lifestyles to reduce carbon emissions but also minimizing the adverse effects of urban building elements on the diffusion of carbon emissions. This can facilitate the rapid flow of carbon emissions to high-carbon sink areas, thereby accelerating urban carbon circulation. This study calculated the carbon emissions of Hangzhou, utilized the WRF/Hysplit coupling method to simulate the city’s carbon emission diffusion status in 2020, and explored the impact of construction land layouts on carbon emission diffusion in terms of building height and building location. The results indicate the following: (1) The main sources of carbon emissions are located within the city, displaying a multi-center spatial distribution. The primary corridor for carbon emission diffusion is on the east side, where the underlying building density is relatively low. (2) As the building height increases from 24 to 36 m, the obstructive effect on carbon emission diffusion rapidly intensifies; however, this increase slows considerably once the building height exceeds 54 m. (3) The impact of buildings on carbon emission diffusion is the greatest when the distance between construction land and a carbon source area is 0 km. When this distance is 2 km, the obstructive effect of buildings significantly improves, depending on their heights. Beyond 7 km, the building height has almost no impact on carbon emission diffusion. The findings of this study may provide valuable suggestions for optimizing building heights in newly developed areas on the outskirts of cities, aiding in the effective design of construction land layouts to help China achieve its carbon neutrality and carbon peaking goals. Full article

Rehmannia glutinosa, a crucial medicinal plant native to China, is extensively cultivated across East Asia. We used high-throughput sequencing to identify viruses infecting R. glutinosa with mosaic, leaf yellowing, and necrotic symptoms. A novel Torradovirus, which we tentatively named “Rehmannia torradovirus virus” (ReTV), was identified. The complete sequences were obtained through reverse-transcription polymerase chain reaction (RT-PCR), 5′ and 3′ rapid amplification of cDNA ends, and Sanger sequencing. The amino acid sequence alignment between the ReTV-52 isolate and known Torradovirus species in the Pro-Pol and coat protein regions were 51.3–73.3% and 37.1–68.1%, respectively. Meanwhile, the amino acid sequence alignment between the ReTV-8 isolate and known Torradovirus species in the Pro-Pol and coat protein regions were 52.7–72.8% and 36.8–67.5%, respectively. The sequence analysis classified ten ReTV strains into two variants. The ReTV-52 genome has two RNA segments of 6939 and 4569 nucleotides, while that of ReTV-8 consists of two RNA segments containing 6889 and 4662 nucleotides. Sequence comparisons and phylogenetic analysis showed ReTV strains clustered within the Torradovirus, exhibiting the closet relation to the squash chlorotic leaf spot virus. The RT-PCR results showed a 100% ReTV detection rate in all 60 R. glutinosa samples. Therefore, ReTV should be classified as a novel Torradovirus species. ReTV is potentially dangerous to R. glutinosa, and necessitating monitoring this virus in the field. Full article

Reducing fertilizer use and increasing its efficiency will improve the quality of farmland and resource conservation. These are necessary steps to achieving green development in agriculture. Nevertheless, fertilizer-reduction and efficiency-increasing technologies (FREITs) remain limited. To improve the situation, 538 farmers in Jiangsu and Hubei Provinces were surveyed with the goal of measuring the information acquisition ability (IAA) of farmers using an Item Response Theory (IRT) model. A model of improved technology selection was employed in conjunction with an IV-probit model to examine the impacts of IAA on farmers’ adoption of FREITs. The results showed that 34.76% of the surveyed farmers had adopted FREITs, with 12.45% and 26.02% having adopted Soil Testing and Formula Fertilization Technology (STFFT) and Organic Fertilizer Replacement Technology (OFRT), respectively. Second, farmers who used more information access channels had greater IAA, which significantly improved their adoption of FREITs. Third, participation in technical training and an increased degree of technical understanding increased the probability of farmers adopting FREITs. The results remained robust after accounting for endogeneity and correlation. Consequently, enhancing farmers’ IAA, organizing technical training, and improving technical publicity will promote the adoption of FREITs. Full article

Wheat production is intrinsically linked to global food security. However, wheat cultivation is constrained by the progressive degradation of soil conditions resulting from the continuous application of fertilizers. This study aimed to examine the effects of deep tillage on rhizosphere soil microbial communities and their potential role in improving soil quality, given that the specific mechanisms driving these observed benefits remain unclear. Soil fertility in this research was evaluated through the analysis of various soil parameters, including total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium, among others. The high-throughput sequencing technique was utilized to examine the rhizosphere microbial community associated with deep tillage wheat. The findings indicated that deep tillage cultivation of wheat led to reduced fertility levels in the 0–20 cm soil layer in comparison with non-deep tillage cultivation. A sequencing analysis indicated that Acidobacteria and Proteobacteria are the dominant bacterial phyla, with Proteobacteria being significantly more abundant in the deep tillage group. The dominant fungal phyla identified were Ascomycota, Mortierellomycota, and Basidiomycota. Among bacterial genera, Arthrobacter, Bacillus, and Nocardioides were predominant, with Arthrobacter showing a significantly higher presence in the deep tillage group. The predominant fungal genera included Mortierella, Alternaria, Schizothecium, and Cladosporium. Deep tillage cultivation has the potential to enhance soil quality and boost crop productivity through the modulation of soil microbial community structure. Full article

The use of ferronickel slag powder (FNSP) as a cementitious additional material has been supported by numerous reports. FNSP concrete has the same shortcomings as ordinary concrete, including low hardness. In this study, in order to make FNSP concrete more durable, end-hooked type steel fibers were incorporated. To understand how various elements affect the mechanical properties of steel fibers, an experiment was carried out on the mechanical properties of steel FNSP concrete (SFNSPC). FNSP’s principal ingredients, with a particle size distribution ranging from 0.5 to 100 μm and a sheet-like powder shape, are CaO, SiO₂, Al₂O₃, MgO, and others, according to tests conducted on the material’s microstructure and composition. Then, eighteen mix proportions were developed, comprising six distinct FNSP replacement rate types and three distinct steel fiber content types. Crucial metrics were evaluated and analyzed, including the relationship among the toughness, tensile strength, and compressive strength as well as slump, splitting tensile strength, compressive strength, and uniaxial compressive stress–strain curve of SFNSPC. The results showed that the slump of SFNSPC under different FNSP replacement rates decreased with increasing steel fiber volume. Steel fibers have a small but positive effect on SFNSPC’s compressive strength; nonetheless, as FNSP replacement rates increased, SFNSPC’s slump gradually decreased, though not by much. These results show that FNSP is a viable alternative cementitious material in terms of strength. Specifically, the splitting tensile strength of SFNSPC improves with an increase in steel fiber content, and the pace at which SFNSPC strength drops with an increase in the FNSP replacement rate. With varying mix proportions, the stress–strain curve trend of SFNSPC remains mostly constant, and steel fibers improve the compressive toughness of SFNSPC. After adding 0.5% and 1.0% steel fibers, the toughness index of concrete with different FNSP replacement rates increased by 8–30% and 12–43%, respectively. Full article

To elucidate the function of the cold-resistance regulatory gene FmNAC1 from Fraxinus mandshurica Rupr., this study identified the role that overexpression of the FmNAC1 gene plays in tobacco growth and cold-stress regulation. The cloned FmNAC1 gene from F. mandshurica is 891 bp in length and encodes 296 amino acids. Our subcellular localization analysis confirmed that FmNAC1 is primarily located in the nucleus and functions as a transcription factor. FmNAC1 is responsive to cold and NaCl stress, as well as to the induction of IAA, GA, and ABA hormone signals. To further elucidate its function in cold resistance, four transgenic tobacco lines expressing FmNAC1 (FmNAC1-OE) were generated through tissue culture after the Agrobacterium-mediated transformation of wild-type (WT) Nicotiana tabacum L.. These FmNAC1-OE plants exhibited accelerated growth after transplantation. When exposed to low-temperature conditions at −5 °C for 24 h, the rates of wilting and yellowing of the FmNAC1-OE plants were significantly lower than those of the WT tobacco plants. Additionally, the membrane integrity, osmotic regulation, and reactive oxygen species (ROS)-scavenging abilities of the FmNAC1-OE tobacco lines were better than those of the WT plants, indicating the potential of the FmNAC1 gene to improve plant cold resistance. The gene expression results further revealed that the FmNAC1 transcription factor exhibits regulatory interactions with growth-related genes such as IAA and AUX1; cold-resistance-related genes such as ICE, DREB, and CBF1; and genes involved in the clearance of reactive oxygen species (ROS), such as CAT and SOD. All of this evidence shows that the FmNAC1 transcription factor from F. mandshurica plays a key role in contributing to the enhancement of growth, cold resistance, and ROS clearance in transgenic tobacco plants. Full article

China’s economic development has achieved great success in recent years, but the problems of energy scarcity and environmental pollution have become increasingly serious. To enhance the reliability and efficiency between energy, the environment and the economy, sustainable development is an inevitable choice. In the context of measuring sustainability efficiency, a network data envelopment analysis model is proposed to formulate the two-stage process of energy use and operations management. A double frontier is derived to optimize the available energy for sustainable development. Due to nonlinearity, previous linear methods are not directly applicable to identify the double frontier and calculate stage efficiencies for inefficient decision-making units. To address this problem, this study develops the primal-dual relationship between multiplicative and envelopment network models based on the Lagrange duality principle of parametric linear programming. The newly developed approach is used to evaluate the sustainability efficiency of 30 administrative regions in China. The results show that insufficient sustainability efficiency is a systemic problem. Different regions should take different measures to conserve energy and reduce pollutant emissions for sustainable development. To increase sustainability efficiency, regions should support energy-saving and emission-reducing technologies in production processes and strengthen their capacity for technological innovation. Compared with energy use efficiency, operations management efficiency in China has a wider range of changes. During the operations management stage, there is not much difference between the capacity and quantity of each region. Based on benchmark regions at the efficiency frontier, there is an opportunity to improve operations management in the near future. Blockchain technology can effectively improve energy allocation efficiency. Full article