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Abstract Machine learning algorithms investigate relationships in data to deliver useful outputs. However, past models required complete datasets as a prerequisite. In this study, rough set-based machine learning was applied using real-world incomplete datasets to generate a prediction model of biochar’s adsorption capacity based on key attributes. The predictive model consists of if–then rules classifying properties by fulfilling certain conditions. The rules generated from both complete and incomplete datasets exhibit high certainty and coverage, along with scientific coherence. Based on the complete dataset model, optimal pyrolysis conditions, biomass characteristics and adsorption conditions were identified to maximize tetracycline adsorption capacity (> 200 mg/g) by biochar. This study demonstrates the capabilities of rough set-based machine learning using incomplete practical real-world data without compromising key features. The approach can generate valid predictive models even with missing values in datasets. Overall, the preliminary results show promise for applying rough set machine learning to real-world, incomplete data for generating biomass and biochar predictive models. However, further refinement and testing are warranted before practical implementation.

Extracellular vesicles (EVs) and EV proteins are promising biomarkers for cancer liquid biopsy. Herein, we designed a case–control study involving 100 controls and 100 patients with esophageal, stomach, colorectal, liver, or lung cancer to identify common and type‐specific biomarkers of plasma‐derived EV surface proteins for the five cancers. EV surface proteins were profiled using a sequencing‐based proximity barcoding assay. In this study, five differentially expressed proteins (DEPs) and eight differentially expressed protein combinations (DEPCs) showed promising performance (area under curve, AUC > 0.900) in pan‐cancer identification [e.g., TENM2 (AUC = 0.982), CD36 (AUC = 0.974), and CD36‐ITGA1 (AUC = 0.971)]. Our classification model could properly discriminate between cancer patients and controls using DEPs (AUC = 0.981) or DEPCs (AUC = 0.965). When distinguishing one cancer from the other four, the accuracy of the classification model using DEPCs (85–92%) was higher than that using DEPs (78–84%). We validated the performance in an additional 14 cancer patients and 14 controls, and achieved an AUC value of 0.786 for DEPs and 0.622 for DEPCs, highlighting the necessity to recruit a larger cohort for further validation. When clustering EVs into subpopulations, we detected cluster‐specific proteins highly expressed in immune‐related tissues. In the context of colorectal cancer, we identified heterogeneous EV clusters enriched in cancer patients, correlating with tumor initiation and progression. These findings provide epidemiological and molecular evidence for the clinical application of EV proteins in cancer prediction, while also illuminating their functional roles in cancer physiopathology.

Biochar application to agricultural fields is an effective carbon sequestration measure that has the potential to reduce N2O emissions and increase soil water holding capacity. However, the interaction mechanisms of biochar under deficit irrigation on N2O emissions remain unclear. A two-year field experiment is conducted in the Guanzhong Plain, China, in order to quantify the effects of biochar and deficit irrigation on N2O emissions from winter wheat–summer maize crop rotation and to investigate the potential mechanisms of nitrification and denitrification. According to the combination of biochar application and actual evapotranspiration-based irrigation scheduling, four treatments are designed (B1W100: biochar 30 t·ha−1 + ET; B1W80: biochar 30 t·ha−1+ 0.8 ET; B0W100: no biochar + ET; B0W80: no biochar + 0.8ET). The soil N2O flux, soil physical and chemical properties, and key functional gene abundance related to N2O emissions in nitrification and denitrification at different growth stages are investigated and discussed. Results show that the interaction between deficit irrigation and biochar significantly reduces soil N2O emissions. During the wheat and maize season, the application of biochar reduces the N2O emissions by an average of 12.9% and 15.2%, respectively. Deficit irrigation also reduces the N2O emissions by an average of 17.4% and 15.5%, respectively. Pearson correlation analysis shows that soil N2O is significantly correlated with soil water-filled pore space during the phase with intense N2O emissions. Soil functional gene abundance is determined at different growth stages for both wheat and maize. Maximum soil denitrification functional gene abundance is observed at the time when wheat and maize enter the stage of their peak growth at the jointing stage. With biochar addition and deficit irrigation, the abundance of nirK and nosZ genes increases and AOB amoA genes decreases. These results suggest that biochar with deficit irrigation is a better solution to reduce N2O emissions from agricultural soils.

Excessive water and nitrogen inputs in agricultural production can result in resource wastage and environmental pollution. This makes it imperative to identify effective farmland management strategies to ensure sustainable agriculture development, and it remains to be explored whether biochar can be an effective solution. In this study, a 2-year (2021 and 2022) field experiment was conducted with two irrigation levels, W100 (ET) and W80 (0.8 ET), and three nitrogen fertilizer levels, NH (270 kg ha−1), NM (180 kg ha−1), and NL (90 kg ha−1), in full combination with biochar (30 t ha−1). The NM and N0 treatments without biochar at both irrigation levels were set as controls. The results of the study showed that there was no significant difference in maize yield between the high and medium N treatments. Further, maximum water productivity (WP), nitrogen agronomic efficiency (NAE), and nitrogen recovery efficiency (NRE) were obtained in NM treatments when water and nitrogen were kept consistent. Deficit irrigation was effective in reducing water consumption and increased WP by 15.54% and 11.06% in 2021 and 2022, respectively. Biochar application increased WP, nitrogen use efficiencies, and significantly increased the yield by 7.02% and 6.46% in 2021 and 2022, respectively. Therefore, the application of biochar can be an effective measure to promote crop growth and resource use. Based on the results of this experiment, an irrigation level of 0.8 ET in combination with NM and biochar application is recommended to ensure the sustainability of agricultural production.

The nano-scaled structural heterogeneity is closely associated with the magnetic softness and mechanical properties of Fe-based amorphous alloys. However, limited by the shape and size of ribbons, the details of the atomic-scale structural evolution in ribbons under external stimulation are still missing. In this work, Maxwell-Voigt model with 2 K units and 1 Mx unit was employed to investigate the structural response of FeBCCu amorphous ribbons by substitution of P for B during creeping process under nanoindentation. The P-added alloy exhibited a more sensitive mechanical response at various loading rates, especially for the reduction of hardness and the increase of maximum indentation depth and creep displacement. With the help of creep analysis using above Maxwell-Voigt model, both types of defects were inclined to be activated at a quasi-static loading mode in P-added alloy, and the small size defects seemed to be easily activated and finally coupled into large defects in the fast loading mode, revealing the atomic diffusion and reconstruction process of activated defects. These types of defects evolved into the response of structural heterogeneity to external stimulation, manifesting a large deformation behavior during creeping. This work enlightens the comprehensive insights into the evolution of structural defects in Fe-based amorphous ribbons and has certain guiding significance for the structural design of high-performance alloys.

Abstract Background Conducting an extensive study on the spatial heterogeneity of the overall carbon budget and its influencing factors and the decoupling status of carbon emissions from economic development, by undertaking simulation projections under different carbon emission scenarios is crucial for China to achieve its targets to peak carbon emissions by 2030 and to achieve carbon neutrality by 2060. There are large disparities in carbon emissions from energy consumption, the extent of land used for carbon absorption, and the status of decoupling of emissions from economic development, among various regions of China. Results Based on night light data and land use data, we investigated carbon budget through model estimation, decoupling analysis, and scenario simulation. The results show that the carbon deficit had a continuous upward trend from 2000 to 2018, and there was a significant positive spatial correlation. The overall status of decoupling first improved and then deteriorated. Altogether, energy consumption intensity, population density of built-up land, and built-up land area influenced the decoupling of carbon emissions from economic development. There are significant scenarios of carbon emissions from energy consumption for the study area during the forecast period, only in the low-carbon scenario will the study area reach the expected carbon emissions peak ahead of schedule in 2027; the peak carbon emissions will be 6479.27 million tons. Conclusions China’s provincial-scale carbon emissions show a positive correlation with economic development within the study period. It is necessary to optimize the economic structure, transforming the economic development mode, and formulating policies to control the expansion of built-up land. Efforts must be made to improve technology and promote industrial restructuring, to effectively reduce energy consumption intensity.

Abstract Background Glutathione S-transferase (GST) is a crucial enzyme for metabolism, detoxification, and stress resistance in organisms. Many GSTs have been identified in seaweeds, but the isolation and functional analysis of GSTs in Saccharina japonica have not been completed. Result In this study, a total of 32 SjGST genes, localized on 10 scaffolds and 6 contigs, were identified and categorized into three groups. Most of these SjGSTs were presumed to be distributed in the cytoplasm. Tandem duplication had a significant influence on the expansion of the SjGST gene family. Functional analysis of cis-acting elements in the promoter regions demonstrated that SjGSTs enhance the stress resistance of the kelp. Quantitative real-time PCR tests confirmed that SjGSTs positively influence S. japonica sporophytes under stress from low salinity, drought, and high temperature. Recombinant yeast tests further affirmed the role of SjGSTs in stress resistance; SjGSTs improved the growth rate of recombinant yeast under 1.5 M NaCl or 8 mM H2O2. Analysis of biochemical parameters indicated that the optimum temperatures for SjGST20 and SjGST22 were 20 °C, and the optimum pH values were 7.0 and 8.0 for SjGST20 and SjGST22, respectively. The K m values for the substrate 1-chloro-2,4-dinitrobenzene (CDNB) were 2.706 mM and 0.674 mM and were 6.146 mM and 3.559 mM for the substrate glutathione (GSH) for SjGST20 and SjGST22, respectively. Conclusion SjGSTs are important stress resistant genes in S. japonica. This research results will enhance our understanding the function of GSTs in brown seaweeds, and explained its functional roles in stress resistance in marine environments.

The reproductive characteristics of some hybrids from crosses of cultivated strains with wild populations are more similar to their wild parents. These hybrids form sorus twice a year in spring and autumn, unlike the conventional cultivars, which formed sorus once a year in summer. The S. japonica seedling industry begins in August in the north of China. However, hybrids form sorus in September or later. Therefore, these hybrids cannot be used as parental stock in the cultivation of summer seedlings in the north of China, hindering the promotion and application of these hybrids with excellent traits. Unfortunately, very few studies have focused on the induction and mechanism of sorus formation in kelp. It was of great significance to explore artificial induction technology for sorus formation of kelp hybrids and ensure the timely formation of sorus when the summer seedling cultivation based on an understanding of the biological process of sorus development. At present, research on the biological processes and characteristics of hybrid kelp sorus were limited. This study investigated the hybrid variety "Yudai No. 1". Discs from the kelp sporophytes were cultured in inflatable bottles. The sorus development process was divided into five stages (SA~SE) based on the appearance and morphological changes of the sorus. Samples for each stage were collected separately. The appearance, morphology, and tissue structure changes during the formation and development of sorus were systematically observed. Changes in the physiological and biochemical characteristics at different stages were also quantitatively studied. During sorus development, the surface of the sporophyte was smooth at stage SA, frosted in stage SB, noticeably protruded at stage SC, the cuticle at the apex of the paraphysis cells broken at stage SD, and the cuticle was smooth again in stage SE. The process was accompanied by the protrusion of epidermal cells (SB), the elongation of paraphysis cell (SC), the differentiation and development of sporoblast (SC, SD), and the formation and release of zoospores (SE). The cells (paraphysis cell and sporoblast) varied significantly and were constantly elongating at all stages (P < 0.05). The cells were especially elongated during the stage of zoospore formation and release (SE), zoospore cells were nearly 1-fold longer than the zoospores that were not released at stage SD. During the development of S. japonica sorus, the accumulation of nitrogen by sorus continued to increase, and there was little change after reaching the maximum level at stage SD. The formation of sorus was accompanied by the accumulation of nutrients. The protein content increased significantly in the early stages of sorus development and decreased at the stage of zoospore release. The protein content was significantly higher in the SC stage than that at stage SA (P < 0.05). Subsequently, the decline began after the SC stage, indicating the development of the sorus was the main biological activity, and the metabolic level was gradually reduced. Unlike that in previous studies, we identified a significant increase in the chlorophyll content during sorus development, which probably ensured all zoospores include chloroplasts. Meanwhile, hydrogen peroxide (H2O2) and superoxide anions showed similar trends of initially increasing at the beginning of sorus formation and decreasing in the later stages. Changes in the H2O2 content were highly significant in sorus formation. There were differences in the activity of different antioxidant enzymes in the process of sorus formation, among which superoxide dismutase (SOD) activity had a general downward trend, while ascorbate peroxidase (APX), peroxidase (POD), and catalase (CAT) showed a trend of rising in the early stages and then declining in the later stages. Moreover, POD, APX, and CAT activity had the significantly lowest levels at stage SC, SD, and SE, whereas the maximum levels of POD and APX were at stage SB, and maximum CAT levels were at stage SD. However, the malondialdehyde (MDA) content did not vary significantly during the whole development process. SOD activity gradually decreased throughout development, and the H2O2 content continued to increase, suggesting kelp sorus development may require hydrogen peroxide involvement. The activities of various antioxidant enzymes changed dynamically at different stages of sporangia development, and accurately regulated the oxygen species (ROS). The ROS increase in the process of sorus development did not harm any cells and ROS participated as a signaling molecule in the molecular regulation process of sorus development. In sorus development, the activity of RuBP carboxylase (RubisCO) initially decreased at stage SB and SC and then increased. There was no significant variation in the plant malate dehydrogenase activity. This study deepened the understanding of the hybrid kelp sorus formation process, physiological, and biochemical characteristics, and provided a theoretical basis for the artificial induction of hybrid kelp sorus formation in the future.

Abstract This study aimed to develop a robust predictive model for tetracycline (TC) adsorption onto biochar (BC) by employing machine learning techniques to investigate the underlying driving factors. Four machine learning algorithms, namely Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost) and Artificial Neural Networks (ANN), were used to model the adsorption of TC on BC using the data from 295 adsorption experiments. The analysis revealed that the RF model had the highest predictive accuracy (R2 = 0.9625) compared to ANN (R2 = 0.9410), GBDT (R2 = 0.9152), and XGBoost (R2 = 0.9592) models. This study revealed that BC with a specific surface area (S (BET)) exceeding 380 cm3·g−1 and particle sizes ranging between 2.5 and 14.0 nm displayed the greatest efficiency in TC adsorption. The TC-to-BC ratio was identified as the most influential factor affecting adsorption efficiency, with a weight of 0.595. The concentration gradient between the adsorbate and adsorbent was demonstrated to be the principal driving force behind TC adsorption by BC. A predictive model was successfully developed to estimate the sorption performance of various types of BC for TC based on their properties, thereby facilitating the selection of appropriate BC for TC wastewater treatment.

River basins play an important role in national economic development and ecological security and can be well expressed by ecosystem services (ESs) research. Due to rapid population growth and climate change, it has had a significant impact on the ecosystem of the Yellow River Basin (YRB). Although ESs have been assessed in several studies, few studies have used a composite ecosystem service index (CESI) in their assessment. Thus, here, based on the InVEST model, bivariate spatial autocorrelation, and spatial econometric model, we studied the composite ESs in the YRB, with an aim to build a CESI for evaluating the overall ESs in the YRB. We found that the CESI of the YRB from 1990 year–2020 year had an obvious spatiotemporal distribution law at the city level and grid scale, showing a high distribution characteristic in the southeast. The spatial trend also showed a significant difference in regional distribution. There was a positive spatial correlation between the CESI and urbanization indicators that reflected the level of urbanization, and the distribution of the aggregation type among the three was similar. Furthermore, population density had a strong positive spillover effect on the CESI, whereas economic density and land development had a negative spillover effect. Therefore, the YRB should pay attention to transforming the extensive development model and paying attention to the negative spillover effect of economic density when laying out industrial structures. Additionally, it is necessary to control the expansion of built-up land and improve land use efficiency, thereby reducing the negative spillover effect of land development. This study’s findings can serve as reference for policy formulation in major river basins worldwide.

With the accelerated development of urbanization, the exploration and usage of land resources is becoming more and more frequent, which leads to the decline of soil quality, resulting in a series of soil ecological issues, such as soil nutrient loss, soil quality degradation and destruction. At present, the contradiction between soil erosion and sustainable development of human society has become one of the hot issues studied by scholars. The Yellow River Basin is an important experimental area for high-quality development in China, constructing the Yellow River Ecological Economic Belt play an important role in China’s regional coordinated development. Although most of the affected area of the Lower Yellow River (AALYR) is in the plain, they have a large population density and are in the historical farming area. In latest years, because of the development and transformation of modern society, their ecological environment has become more fragile and soil erosion problems has become increasingly serious. Studying and analyzing soil erosion is of vital meaning for ecological protection and can provide scientific support for soil conservation work. Depending on the data of precipitation, soil properties, land use, population, etc., this paper studies and analyzes the soil erosion in AALYR from 2000 to 2020 through the RUSLE. We found that during the 20 years the proportion of very slight and slight grade area increased, and the distribution of moderate and above erosion grade was less, mainly in Zibo, Jinan, Anyang, Zhengzhou, and Tai 'an. Nearly three quarters of the regional soil erosion grade didn’t change, apart from the increase of slight grade area, the other erosion grades area showed a downward trend. We take the city, county and town zoning analysis find that as the scale decreases, the area of serious erosion grades increases, and the distribution is gradually detailed. Land use is the main influencing factor of erosion except DEM. Forestland and grassland are larger of the soil erosion in various types of land use. Through these conclusions in this paper, it is promising to provide theoretical references for the ecological environment governance and high-quality and sustainable development of great river basins of the world and similar regions.

Rapid urbanization is a global phenomenon that has altered many ecosystems and created ecological risks. Landscape ecological risk (LER) reflects the extent to which ecosystems are threatened by human activities and environmental change. LER can be also employed to effectively monitor and assess environmental quality. A large number of studies have been conducted to explore the LER in the basin from the perspective of Land Use and Land Cover (LUCC). Ecological environmental issues such as land degradation have seriously hindered the sustainable development of the Yellow River Basin (YRB). Based on the LUCC data of the YRB in the four periods of 1990, 2000, 2010 and 2020, this study aims to determine the most suitable spatial analysis scale using the coefficient of variation and semi-variogram, and analyzes the landscape pattern and LER of the YRB. We found that the landscape pattern of the YRB exhibits obvious scale dependence, and the analysis effect is most effective at the scale of 90 km × 90 km. Throughout the study period, the landscape pattern exhibited increasing fragmentation, a decrease in the degree of aggregation and an increase in the heterogeneity of distribution. In terms of LER, it is in a better state as most of the LER levels have shifted from higher to lower levels, and the proportion of lower and lowest risk is constantly increasing. This study improves the precision of spatial scale investigations and offers valuable insights for future studies on landscape pattern and LER in the basin.

Castleman disease (CD), first described in 1954, is a rare lymphoproliferative disorder. A 20-year-old female patient was treated for a "painless mass below the right ear for 1 year". The imagological examination of the patient showed a soft tissue mass about 2.8 cm in diameter in the right parotid gland. Moreover, the patient underwent a right superficial parotidectomy and facial nerve dissection. The mass in the parotid gland was removed, and CD was confirmed by further pathological examination. Imagological examination contributes to the diagnosis and preoperative evaluation of CD.

Sargassum thunbergii is distributed on reefs and rock marshes in mid- and low-tide zones, and some are periodically exposed to lengthy low tides. Dehydration is a key factor affecting the survival of S. thunbergii at low tides. In this study, using wild S. thunbergii as experimental material, the water loss rate, chlorophyll fluorescence parameters, and biochemical parameters under different stresses were determined by dehydrating the thalli in an incubator for 0, 1, 3, and 6 h. The results showed that: (1) algae of different sizes have significantly different water loss rates under different stresses. The shorter the stress time and the larger the algae, the lower the water loss rate, indicating that the water retention capacity of S. thunbergii with larger thalli is higher. Wild S. thunbergii grow in clusters on reefs. The leaves in the lower part of the branches and near the holdfast are wide. The middle and upper leaves are narrow and long, respectively. The lower broad leaves are easily blocked by the upper branches. Therefore, differences in the growth environment cause differences in the ecological structure and biochemical components of S. thunbergii. High temperature, strong light, and water loss at low tide are the main factors that cause severe environmental stress to sessile S. thunbergii in the intertidal zone. (2) Dehydration significantly reduced the chlorophyll fluorescence value of S. thunbergii, and different parts of the same individual of S. thunbergii had significantly different tolerance to dehydration, with the lowest tolerance at branch tips and the strongest tolerance at the base. The non-regulatory energy-dissipation mechanism plays a major role in the dehydration response of S. thunbergii. Under dry exposure, the light energy utilization efficiency of S. thunbergii was significantly reduced. This reduction in active light protection capacity indicates that dehydration reduces the adaptability of S. thunbergii to excessive light intensity. Dehydration can damage the tips of small individuals that cannot recover, while the base part of large individuals could return to a normal physiological state. (3) Antioxidant enzymes (ASAFR, SOD) and non-antioxidant substances (soluble sugar and proline) in the tip part responded to dehydration, and the base part mainly responded by upregulation of protein, soluble sugar, and proline content to resist stress. S. thunbergii, located in the high and middle tide zones, is more likely to be stressed by high temperatures, strong light, and dehydration, and the physiological and biochemical characteristics of different parts of the thallus are also variable due to differences in external morphology. Algae mainly reduce damage to the photosynthetic system caused by a lack of water through a non-regulatory energy dissipation mechanism. The water retention capacity of the base was better than branch tips during dry exposure, and the damage to algal cells was low. The main roles are as heat shock proteins, soluble sugars, proline, and other small molecules, which can pass stress response, osmotic regulation, and anti-oxidation resists damage to cells caused by stress. The water retention capacity of the top cells was weak, and the stress was relatively strong. Antioxidant enzymes such as ASAFR and SOD in algae and non-antioxidant enzymes such as soluble sugars and proline, work together to resist dry exposure stress, reduce cell damage and maintain cell viability. In summary, under the stress of dry exposure, the antioxidant enzymes, antioxidant substances, and non-regulatory energy dissipation mechanisms of S. thunbergii play a role in maintaining cell activity. This study provides important guidance for exploring the ecological adaptability of S. thunbergii in resisting environmental stress.

Macrocystis pyrifera is a large perennial brown alga used as a raw material in the chemical, energy, and medicine industries. It is also a high-quality material for the construction of seaweed beds with extremely high economic and ecological value. In the 1980s, M. pyrifera was introduced to China, and many experiments on its seedling and cultivation technologies were undertaken. However, research on its ecological adaptability is relatively challenging, and the aquaculture industry has not yet developed due to bottleneck problems. In the present study, the MaxEnt model was used to predict the suitability and potential invasion risk of M. pyrifera in China to lay a foundation for M. pyrifera culture industry development and marine ecological construction. Parameter optimization showed that the predictive performance of the model was the best when the feature combination was product, quadratic, and hinge features and the regularization multiplier was 0.8. Considering the correlation between environmental attributes and their contribution to the model, six environmental factors were selected to construct a prediction model for the suitability of M. pyrifera. Among these, light intensity and temperature produced the greatest impact on the natural distribution of M. pyrifera. For high suitable growth probability, the optimal light intensity was > 2 μmol/(m2·s) and the optimum temperature range was 10.5~17℃. Combined with ArcGIS, the modeling results showed that the suitable habitats for M. pyrifera in China are mainly distributed in the Yellow Sea and Bohai Sea, accounting for approximately 13.17% of the sea area, with a marginal suitability of 5.46%, low suitability of 2.85%, moderate suitability of 1.20%, and high suitability of 3.66%. Furthermore, Liaodong Bay and Bohai Bay are suitable sea areas for the introduction and cultivation of M. pyrifera as well as the construction of M. pyrifera farms. Some areas in Liaodong Bay are highly suitable, indicating a certain risk of invasion. Therefore, ecological safety evaluations should be strengthened if M. pyrifera cultivation is promoted near this area.

Coal dust is one of the seven disasters in coal mine. It affects the health of workers and causes coal dust explosion. The wetting effect of coal has a great influence on dust removal. Studies have shown that the wetting effect of coal is related to the wettability, surface roughness and surfactants of coal. In order to effectively solve the problem of coal dust under the mines, which selects hydrophilic Hami lignite, hydrophobic Anyang coking coal and weakly hydrophilic anthracite of Zhaogu No.2 mine as the research objects. The mean square roughness of the three coal samples were measured by the optical contact angle morphology combined instrument, the intrinsic contact angles of the three coal samples were measured, the two-dimensional physical model was constructed by COMSOL numerical software, the simulation conditions were set, the simulation parameters were adjusted, the experimental and simulation values were analyzed and compared, the feasibility of COMSOL numerical simulation was verified, and the influence of coal surface roughness on coal surface contact angle was studied. The results show that the droplet spreading process, the droplet spreading velocity and the droplet spreading shape of numerical simulation are similar to those of experiment, but the simulated contact angle is larger than that of experiment. With the increase of coal surface roughness, the contact angle of lignite decreases from 60.7° to 50.9°, the variation range is about 10°, the contact angle of coking coal increases from 96.5° to 112.7°, the variation range is about 16°, and the contact angle of anthracite decreases from 89.7° to 78.3°, and the variation range is about 11°. The simulated and experimental values of contact angle of three kinds of coal samples with the same surfactant have the same change trend, but the simulated value is larger than the experimental value. It is feasible to study the influence of coal surface roughness on coal surface contact angle by numerical simulation. The wetting of coal surface affected by roughness conforms to Wenzel model. The existence of surfactant does not change the variation of contact angle with surface roughness of three coal samples.

In the context of urban expansion and climate change, the world is under pressure from multiple ecological risks. Key ecological protection areas play a pivotal role in preserving ecological stability and promoting development. Due to its unique geographical conditions, the Yellow River basin has been facing huge ecological risk pressure. In the affected area of the Lower Yellow River (AALYR) as an agricultural hub, ecological protection has gradually become a key factor restricting the development of cities and agriculture. Taking AALYR as an example, the landscape ecological risk assessment (LERA) system is established based on three aspects “natural environment—human society—landscape pattern”. We construct a comprehensive cumulative resistance surface based on the risk assessment results as the basis for the future study. Ecological corridors are identified by minimum cumulative resistance (MCR) models to establish and optimize Ecological security pattern (ESP) in the AALYR. We found that the landscape ecological risks (LER) in the study area show a uniform spatial distribution, with a slightly higher distribution in the northeast than the southwest. The ecological risk levels are generally high in AALYR, indicating a more severe risk problem in this area. A total of 56 ecological sources were identified, with a total area of 21176 km2. The ecological sensitivity of AALYR was high, and 99 ecological corridors and 59 ecological nodes were extracted. Ecological corridors and nodes were consistently and densely distributed throughout the study area. The network analysis method improves the stability of the network structure after optimization. Based on the key components of the ESP, with the combination of geographical characteristics and local policy planning guidance, we constructed the “One Belt and One Axis, Two Cores and Two Corridors, Four zones” ESP. The study results may offer guidance and suggestions for the construction of ESP and ecological environment protection system in the world’s major river basins, and may also provide information for ecological planning of other similar river basins in the world.

Quantifying the relationship between land use change and landscape pattern (LP) is crucial in responding global challenges such as climate change, food security, and even biodiversity loss. Here, we used multi-period land data to quantify the spatiotemporal trends in built-up land expansion (BLE) and LP in the Yellow River Basin (YRB) during 1980–2018. We fitted the correlations between these two variables using LP Index, Landscape Expansion Indices (LEI) and the Multiscale Geographically Weighted Regression (MGWR) model. We found that regional BLE was highly variable, BLE was the main driver of landscape fragmentation, and the relationship between BLE and LP scale varies, especially in terms of the edge BLE. Landscape fragmentation and aggregation spatially varies and temporally increases in complexity. The MGWR model effectively disclosed a scale effect between BLE and LP. The control variables differed in terms of their relative impact on LP evolution. The present study demonstrated the complexity of the relationship between BLE and LP change and highlighted the importance of variable selection, spatiotemporal scale, and spatial dimension in the quantification of these relationships.

Carbon dioxide emission is an important driving factor of global warming and it has threatened the ecological environment and human survival. Among them, land use has led to significant carbon emissions that profoundly affect climate system change. The Yellow River Basin (YRB) is one of the regions with the most concentrated contradictions in population, resources, and environment in China; thus, studying the current situation and land use carbon emissions (LUCE) is significant for mitigating global warming, promoting coordinated emission reduction among different regions in the basin, and achieving ecological conservation and high-quality development of the YRB. This study based on land use and socio-economic data, and is carried out from the perspective of social network analysis. The spatiotemporal variation of LUCE in the YRB was analyzed using the carbon emission coefficient method. The spatial spillover effects of LUCE were discussed using social network analysis methods. The PLUS model was used to simulate the differences in LUCE under different scenarios. The results indicate that: (1) The LUCE in the YRB showed an increasing trend during the study period, with significant differences in spatial distribution. (2) There is a significant spatial spillover effect and correlation between cities in the YRB LUCE network, and cities with superior economic had a greater impact on other cities. (3) In 2030, under the ecological protection scenario, the LUCE in the YRB were the lowest, with a reduction of 2.7 × 106 tons compared to the natural development scenario, further illustrating the importance of ecological land. Compared with previous studies, this study explores the spatial correlation between LUCE in various cities of the YRB from a new perspective of social network analysis. On the other hand, it makes land use prediction for 2030 by setting different land use development scenarios. The research results have broadened the application scope of social network analysis methods, and have important practical significance for promoting carbon reduction in major river basins and scientifically formulating land use policies.

Ecosystems offer a wide array of benefits to support human livelihoods and enhance the quality of life. Quantitative evaluation of ecosystem services (ESs) is crucial for achieving the goal of sustainable development. The Yellow River Basin has a large population, and there are contradictions and conflicts in ecological protection, resource utilization, and economic development, among which the downstream region is the most prominent. However, the ESs selected in the existing research are not comprehensive enough, and there are also few studies that further focus on the effects of urbanization on this basis. This article calculated seven types of ESs based on the InVEST model and related methods, and then constructed a composite ecosystem service index (CESI), and studied its spatiotemporal evolution and response to urbanization indicators through bivariate spatial autocorrelation and spatial metrological models. We found that from 1990 to 2020, the CESI fluctuated and decreased with time, with a significant positive spatial correlation but showed a weakening trend. There were differences in the evolution process of the spatial correlation between the CESI and population density, economic density, and land development degree, but ultimately the spatial correlation changed from positive to negative. In terms of spatial spillover effect, population density had a significant positive effect on the CESI, land development had a significant negative effect, and economic density had a weak spillover effect. This article provides a certain reference basis for governments at all levels to formulate relevant strategies for environmental protection and economic development.

Abstract Aims Observational studies showed that low thyroid function may perturb liver function. We aimed to evaluate the association of low thyroid function with both metabolic dysfunction-associated fatty liver disease (MAFLD) and advanced hepatic fibrosis. Methods Participants who underwent abdominal ultrasonography and thyroid function test in a Chinese hospital from 2015 to 2021were enrolled. Fibrosis-4 index (FIB-4) > 2.67 and/or non-alcoholic fatty liver disease fibrosis score (NFS) > 0.676 were used to define advanced fibrosis. Descriptive analyses were performed to characterize the epidemiology of MAFLD according to levels of thyroid-stimulating hormone (TSH). The logistic regression model was applied to estimate the association of low thyroid function with MAFLD and advanced fibrosis. Results A total of 19,946 participants (52.78% males, mean age: 47.31 years, 27.55% MAFLD) were included, among which 14,789 were strict-normal thyroid function, 4,328 were low-normal thyroid function, 829 were subclinical hypothyroidism. TSH levels were significantly higher in MAFLD patients with a FIB-4 > 2.67 and /or NFS > 0.676 than their counterparts. The logistic regression model adjusted for age and sex showed that low-normal thyroid function increased the risk of MAFLD (odds ratio [OR] = 1.09; 95% confidence interval [CI] 1.01–1.18). Multivariable regression model adjusted for age, sex, body mass index, type 2 diabetes, and hypertension showed low-normal thyroid function increased the risk of advanced fibrosis in patients with MAFLD (FIB-4 > 2.67: OR = 1.41, 95% CI 1.02–1.93; NFS > 0.676: OR = 1.72, 95% CI 1.08–2.72). Conclusion Elevated TSH concentrations are associated with advanced hepatic fibrosis, even in the euthyroid state.

Bangia fuscopurpurea is a widespread intertidal seaweed that is commercially cultured in China. This seaweed is frequently exposed to hyposalinity stress, but little is known about the adaptation mechanisms. Ascorbate−glutathione (AsA−GSH) cycle plays important roles in many organisms under a variety of abiotic stress, including hyposaline stress. In this study, we investigated the response of key metabolites and enzymes involved in the AsA−GSH cycle of B. fuscopurpurea under hyposalinity, with the addition of exogenous GSH and Lbuthionine-sulfoximine (BSO). The quantification of BfAPX gene expression was assessed across varied treatment regimens. And the putative interaction proteins of BfAPX were screened by yeast two hybrid system. It was found that under hyposalinity (15 and/or 0 psu), the content of reduced glutathione (GSH), total glutathione (GSH+ oxidized glutathione, GSSG) and cysteine, the ratio of GSH/GSSG and ascorbic acid (AsA)/ dehydroascorbic acid (DHA), and the activity of ascorbic acid peroxidase (APX) and monodehydroascorbate reductase (MDHAR) was significantly up-regulated. The hyposality-promoted GSH/GSSG was weakened while the glutathione reductase (GR) activity was promoted by adding exogenous GSH and BSO. The hyposality-promoted AsA/DHA ratio was strengthened by exogenous GSH but weakened by BSO. The dehydroascorbate reductase (DHAR) activity had no significant changes either with or without exogenous GSH under all salinities, while DHAR activity together with DHA content was enhanced by BSO. The expression of APX gene markedly increased under hyposalinity+BSO treatment. Putative interacting proteins of APX, including glutamate dehydrogenase 1a and fructose diphosphate aldolase, were identified through screening. The results indicated that the AsA−GSH cycle was involved in response of B. fuscopurpurea to hyposalinity by means of increasing GSH/GSSG ratio (through promoting GSH biosynthesis pathway and GSH regeneration from GSSG by GR catalyzation) and AsA/DHA ratio (promoting AsA regeneration through MDHAR). These findings would contribute to improve the aquaculture of this promising economic species and unveil how intertidal seaweeds address the global climate challenges.

Studies on carbon emissions associated with land use and cover change (LUCC) are key to understanding the impact of human activities on regional sustainability. In this study, we analyzed the temporal and spatial changes in carbon emissions associated with LUCC for production, living, and ecological spaces in Zhengzhou City of China. Landsat remote sensing images were used to classify the land use and land cover (LULC) types in Zhengzhou City in 1988, 2001, 2009, and 2015. Carbon emissions associated with LUCC were evaluated using a spatial gradient model and the niche mechanism. It was found that during 1988–2015, carbon emissions associated with LUCC in Zhengzhou City increased by 17.1 ​× ​106 ​t, while the carbon sink resulted from cultivated land, forests, water bodies, and unused land decreased significantly. Most of the increase in carbon emissions associated with LUCC occurred in the center of the city. The peak carbon emissions were located in the northeastern, southeastern, northwestern, and southwestern regions of Zhengzhou City, and carbon emissions varied considerably in the different spatial gradient rings over time. Among the three spaces, carbon emissions associated with LUCC were mainly affected by the living space. The population size and population urbanization rate were negatively correlated with the ecological space and positively correlated with the production and living spaces. Our results highlight that Zhengzhou City should take the new urbanization path of urban transformation development and ecological civilization construction to ensure the realization of the promised carbon emission reduction targets.

Surface roughness has an important effect on the wettability and surface energy of coal. Although the predecessors had studied the effect of surface roughness on the wettability of coal, there were few researches on the effect of surface energy of coal, and the relationship between wettability and surface energy had not been thoroughly studied. This paper aimed to study the effect of surface roughness on the wettability and surface energy of coal, and revealed the relationship between the wettability and surface energy of coal. Based on the surface roughness of coal, this paper selected Hami lignite, Anyang coking coal and Zhaogu anthracite as the research objects, used the experimental methods to measure the surface roughness and experimental contact angle of coal under different conditions to study the effect of surface roughness on the wettability, and then applied the OWRK method to calculate the surface energy of coal to study the effect of surface roughness on the surface energy. The experimental results showed that the wettability of hydrophilic coal became better and the surface energy increased with the increase of surface roughness, while the results of hydrophobic coal were opposite. There was a positive correlation between the wettability and surface energy of coal, and the wettability of coal could be analyzed from the perspective of surface energy. Surfactant could change the wettability of coal, but unchanged the law of wettability with surface roughness.

Macroalgae host diverse epiphytic bacterial communities with potential symbiotic roles including important roles influencing morphogenesis and growth of the host, nutrient exchange, and protection of the host from pathogens. Macroalgal cell wall structures, exudates, and intra-cellular environments possess numerous complex and valuable carbohydrates such as cellulose, hemi-cellulose, mannans, alginates, fucoidans, and laminarin. Bacterial colonizers of macroalgae are important carbon cyclers, acquiring nutrition from living macroalgae and also from decaying macroalgae. Seaweed epiphytic communities are a rich source of diverse carbohydrate-active enzymes which may have useful applications in industrial bioprocessing. With this in mind, we constructed a large insert fosmid clone library from the metagenome of Laminaria digitata (Ochrophyta) in which decay was induced. Subsequent sequencing of a fosmid clone insert revealed the presence of a gene encoding a bifunctional phosphomannomutase/phosphoglucomutase (PMM/PGM) enzyme 10L6AlgC, closely related to a protein from the halophilic marine bacterium, Cobetia sp. 10L6AlgC was subsequently heterologously expressed in Escherichia coli and biochemically characterized. The enzyme was found to possess both PMM and PGM activity, which had temperature and pH optima of 45°C and 8.0, respectively; for both activities. The PMM activity had a Km of 2.229 mM and Vmax of 29.35 mM min−1 mg−1, while the PGM activity had a Km of 0.5314 mM and a Vmax of 644.7 mM min−1 mg−1. Overall characterization of the enzyme including the above parameters as well as the influence of various divalent cations on these activities revealed that 10L6AlgC has a unique biochemical profile when compared to previously characterized PMM/PGM bifunctional enzymes. Thus 10L6AlgC may find utility in enzyme-based production of biochemicals with different potential industrial applications, in which other bacterial PMM/PGMs have previously been used such as in the production of low-calorie sweeteners in the food industry.

Land use change are essential for sustaining human wellbeing, but empirical studies have shown that the urban development requires built-up land, yet, the disorderly expansion of built-up land poses a threat to sustaining the stability of landscape patterns. Reconciling these seemingly conflicting results requires better understanding how the built-up land expansion and the landscape patterns change relationship varies with space and scales. Here we systematically analyzed the landscape pattern and expansion mode of built-up land in the affected area of the Lower Yellow River on three spatial scales (i.e., 5 km, 10 km, 15 km), using landscape pattern analysis, the landscape expansion index and the Multiscale Geographically Weighted Regression (MGWR) model. Our results indicated that: (1) infilling has been the dominant mode of built-up land expansion, and the spreading tendency become more obvious with a decrease in scale; (2) Rapid expansion of built-up land had led to the significant spatial differences in landscape fragmentation and agglomeration at different scales and the complexity of the landscape shape gradually increased; (3) the MGWR model can explain the relationship between the built-up land expansion and landscape pattern more than the Ordinary Least Squares model (OLS), and shows that the dependence of the two is increasing with the increase of scale, Further, the effect of control variables on the landscape pattern evolution differed. This study provides a valuable reference for sustainable development in other large river basins experiencing similar ecological landscape pattern changes (landscape elements, spatial locations and connections that are critical to the health and security of ecological processes).

Salinity is a serious threat to most land plants. Although seaweeds adapt to salty environments, intertidal species experience wide fluctuations in external salinities, including hyper- and hypo-saline stress. Bangia fuscopurpurea is an economic intertidal seaweed with a strong tolerance to hypo-salinity. Until now, the salt stress tolerance mechanism has remained elusive. Our previous study showed that the expression of B. fuscopurpurea plasma membrane H+-ATPase (BfPMHA) genes were the most upregulated under hypo-salinity. In this study, we obtained the complete sequence of BfPMHA, traced the relative expression of this BfPMHA gene in B. fuscopurpurea under hypo-salinity, and analyzed the protein structure and properties based on the gene’s sequence. The result showed that the expression of BfPMHA in B. fuscopurpurea increased significantly with varying hypo-salinity treatments, and the higher the degree of low salinity stress, the higher the expression level. This BfPMHA had typical PMHA structures with a Cation-N domain, an E1-E2 ATPase domain, a Hydrolase domain, and seven transmembrane domains. In addition, through the membrane system yeast two-hybrid library, three candidate proteins interacting with BfPMHA during hypo-saline stress were screened, fructose–bisphosphate aldolase (BfFBA), glyceraldehyde 3-phosphate dehydrogenase (NADP+) (phosphorylating) (BfGAPDH), and manganese superoxide dismutase (BfMnSOD). The three candidates and BfPMHA genes were successfully transferred and overexpressed in a BY4741 yeast strain. All of them significantly enhanced the yeast tolerance to NaCl stress, verifying the function of BfPMHA in salt stress response. This is the first study to report the structure and topological features of PMHA in B. fuscopurpurea and its candidate interaction proteins in response to salt stress.

Global changes have significant impacts on changes in ecosystem services (ESs) and their interrelationships. The Yellow River Basin (YRB) is an important ecological barrier in China, and it is important for ecological decision-making and management in the basin by quantitatively assessing the trends and drivers of ESs and analyzing the trade-offs and synergies among them. In this study, the food production model, InVEST model, and RUSLE model were used to quantitatively assess three ESs (food production, water yield, and soil conservation) in the YRB from 2000 to 2018. The spatio-temporal trends and future trends were quantified using Theil-Sen Median trend analysis and Hurst exponent. Correlation analysis was used to determine the main influencing factors of the spatio-temporal changes of ESs and analyze the trade-offs and synergies among ESs. The research results show that during 2000–2018, in terms of spatial distribution, food production in the YRB gradually decreases from east to west, water yield gradually decreases from south to north, and the dominant areas of soil conservation are mainly distributed in the plateau areas in the upper and middle reaches of the basin; in terms of temporal changes, food production shows a continuous increase, while water yield and soil conservation generally show an increasing trend in fluctuation. Excluding areas with no significant change and random change, food production will mainly show improvement in the future, and water yield and soil conservation will show some degree of decline in the future. Food production is mainly influenced by the type of land use, water yield is mainly influenced by precipitation, and soil conservation is influenced by a combination of slope and land use type. ESs in the YRB were generally dominated by synergy but locally dominated by trade-offs. Our results will provide reference for policymakers in ecological construction, and analyze trade-offs and synergies of regional ESs in a holistic and local context based on the assessment results and change trends of ESs, thus providing a basis for formulating scientific and reasonable ecological protection policies, and will promote the high-quality development of the YRB.

Land-use change is a global issue, and the built-up land expansion has affected the ecological landscape patterns of the major river basins in the world. However, measurement of the ecological risks of potential landscape and identification of the dynamic relationships by natural and human-driven built-up land expansion at different zoning scales are still less understood. Based on multi-period Landsat satellite image data, we combined remote sensing (RS) and geography information systems (GIS) technologies with Spatial Durbin Panel Model to quantitatively analyze the landscape ecological effects under the built-up land expansion in the Yellow River Basin. The results showed that there is spatial heterogeneity in the built-up land expansion and ecological security patterns, with the expansion gravity center gradually spreading from the downstream to the middle and upstream areas, and the most dramatic change in landscape patches of ecological safety patterns occurring around the year 2000. At different zoning scales, there is a spatial spillover effect on the interaction between built-up land expansion and ecological security, with the significance of the regression estimates decreasing from large sample sizes to small sample sizes. Our findings highlighted the importance of spatial heterogeneity at different zoning scales in identifying the dynamic relationship between built-up land expansion and ecological security, scientific planning of land resources, and mitigation of ecological and environmental crises.

With continuous urbanization and the fragmentation of green areas that affect human well-being, the establishment of a green infrastructure (GI) network is important in future urban planning. As a National Central City, Zhengzhou has a large population and is undergoing rapid economic development, resulting in an urgent demand for green space within the city in recent years. We selected the main urban area of Zhengzhou as the study area based on the two phases of Landsat 8 satellite remote sensing image data, for 2016 and 2021, and used the patch-generating land use simulation (PLUS) model to predict the spatial distribution of GI in the future; compared with traditional methods, this method identified green spaces from a future perspective. A GI network—consisting of an open space with vegetation as the main body—was designed for the main urban area of Zhengzhou using the traditional landscape ecological pattern theory, integrating morphological spatial pattern analysis (MSPA), the minimum cumulative resistance (MCR) model, circuit theory, and other methods. Evidently, the area of green space in Zhengzhou City in 2021 was 36 231.6 hm2. GI prediction results indicate that continuous expansion of the main urban area did not result in significant changes in the size of GI in the city. The GI within the urban area was relatively fragmented, forming 15 GI hubs, most of which were densely distributed along the edges of the main urban area. This study proposed the construction of a GI network with a target corridor and target points based on the existing corridor. This included the identification of seven target corridors and 15 target hubs; the total length of the corridor was 77.032 km, with a total of 31 target points. In summary, the GI network pattern of “one protection barrier, two lines, three loops and more points” was proposed. With new urban problems constantly emerging, this research could provide a theoretical reference basis for the planning of GI in the main urban area of the National Central City. The study provides concrete evidence on the optimum pattern for the construction of GI networks in cities with large populations.

Abstract Background As a unique sulfated polysaccharide, fucoidan is an important component of cell wall in brown seaweeds. Its biochemical properties are determined by the positions and quantity of sulfate groups. Sulfotransferases (STs) catalyze the sulfation process, which transfer the sulfuryl groups to carbohydrate backbones and are crucial for fucoidan biosynthesis. Nevertheless, the structures and functions of STs in brown seaweeds are rarely investigated. Results There are a total of 44 ST genes identified from our genome and transcriptome analysis of Saccharina japonica, which were located in the 17 scaffolds and 11 contigs. The S. japonica ST genes have abundant introns and alternative splicing sites, and five tandem duplicated gene clusters were identified. Generally, the ST genes could be classified into five groups (Group I ~ V) based on phylogenetic analysis. Accordingly, the ST proteins, which were encoded by genes within the same group, contained similar conserved motifs. Members of the S. japonica ST gene family show various expression patterns in different tissues and developmental stages. Transcriptional profiles indicate that the transcriptional levels of more than half of the ST genes are higher in kelp basal blades than in distal blades. Except for ST5 and ST28, most ST genes are down-regulated with the kelp development stages. The expression levels of nine ST genes were detected by real-time quantitative PCR, which demonstrates that they responded to low salinity and drought stresses. Conclusions Various characteristics of the STs allow the feasibilities of S. japonica to synthesize fucoidans with different sulfate groups. This enables the kelp the potential to adapt to the costal environments and meet the needs of S. japonica growth.

Soil erosion has a severe impact on habitat and productivity. It is considered to be a major environmental threat prevalent in ecosystems. However, few researchers have studied the spatial distribution of soil erosion intensity among different geographic environmental factors. The Qin River Basin is a geographical unit consisting of mountains, hills, and plains with significant regional characteristics, and it has a basin area of 14,810.91 km2. This study uses the Geographical Information Systems, Revised Universal Soil Loss Equation model to analyze the spatiotemporal changes in the soil-erosion intensity in the Qin River Basin from 1990 to 2018. Different environmental factors of land use, slope and altitude on erosion intensities of 19 secondary land types were analyzed. It can better reflect the soil erosion under different environmental factors and different land use types. Results show that the soil erosion modulus of Qin River Basin were 10.25 t hm-2 a-1, and it belong to slight erosion from 1990 to 2018. Soil erosion intensity is greater in grassland and woodland than in cropland. The strongest soil erosion occurred in the sparse forestland, and the lowest was in beach land. Soil erosion was the highest for a slope of 15~25° and an altitude of 1200~1500 m. Rainfall and slope are important factors lead to soil erosion, indicating weak water and soil conservation implemented in these areas. Therefore, priority should be given to these geomorphic units to formulate and implement soil-erosion control and ecological restoration policies in the Qin River Basin. This study provides a good reference for preventing and controlling soil erosion in river basins.

Climate is a dominant factor affecting the potential geographical distribution of species. Understanding the impact of climate change on the potential geographic distribution of species, which is of great significance to the exploitation, utilization, and protection of resources, as well as ecologically sustainable development. Betula platyphylla Suk. is one of the most widely distributed temperate deciduous tree species in East Asia and has important economic and ecological value. Based on 231 species distribution data points of Betula platyphylla Suk. in China and 37 bioclimatic, soil, and topography variables (with correlation coefficients < 0.75), the potential geographical distribution pattern of Betula platyphylla Suk. under Representative Concentration Pathway (RCP) climate change scenarios at present and in the 2050s and 2070s was predicted using the MaxEnt model. We analyzed the main environmental variables affecting the distribution and change of suitable areas and compared the scope and change of suitable areas under different climate scenarios. This study found: (1) At present, the main suitable area for Betula platyphylla Suk. extends from northeastern to southwestern China, with the periphery area showing fragmented distribution. (2) Annual precipitation, precipitation of the warmest quarter, mean temperature of the warmest quarter, annual mean temperature, and precipitation of the driest month are the dominant environmental variables that affect the potential geographical distribution of Betula platyphylla Suk. (3) The suitable area for Betula platyphylla Suk. is expected to expand under global warming scenarios. In recent years, due to the impact of diseases and insect infestation, and environmental damage, the natural Betula platyphylla Suk. forest in China has gradually narrowed. This study accurately predicted the potential geographical distribution of Betula platyphylla Suk. under current and future climate change scenarios, which can provide the scientific basis for the cultivation, management, and sustainable utilization of Betula platyphylla Suk. resources.

Abstract Background Alginate is an important cell wall component and mannitol is a soluble storage carbon substance in the brown seaweed Saccharina japonica. Their contents vary with kelp developmental periods and harvesting time. Alginate and mannitol regulatory networks and molecular mechanisms are largely unknown. Results With WGCNA and trend analysis of 20,940 known genes and 4264 new genes produced from transcriptome sequencing of 30 kelp samples from different stages and tissues, we deduced that ribosomal proteins, light harvesting complex proteins and “imm upregulated 3” gene family are closely associated with the meristematic growth and kelp maturity. Moreover, 134 and 6 genes directly involved in the alginate and mannitol metabolism were identified, respectively. Mannose-6-phosphate isomerase (MPI2), phosphomannomutase (PMM1), GDP-mannose 6-dehydrogenase (GMD3) and mannuronate C5-epimerase (MC5E70 and MC5E122) are closely related with the high content of alginate in the distal blade. Mannitol accumulation in the basal blade might be ascribed to high expression of mannitol-1-phosphate dehydrogenase (M1PDH1) and mannitol-1-phosphatase (M1Pase) (in biosynthesis direction) and low expression of mannitol-2-dehydrogenase (M2DH) and Fructokinase (FK) (in degradation direction). Oxidative phosphorylation and photosynthesis provide ATP and NADH for mannitol metabolism whereas glycosylated cycle and tricarboxylic acid (TCA) cycle produce GTP for alginate biosynthesis. RNA/protein synthesis and transportation might affect alginate complex polymerization and secretion processes. Cryptochrome (CRY-DASH), xanthophyll cycle, photosynthesis and carbon fixation influence the production of intermediate metabolite of fructose-6-phosphate, contributing to high content of mannitol in the basal blade. Conclusions The network of co-responsive DNA synthesis, repair and proteolysis are presumed to be involved in alginate polymerization and secretion, while upstream light-responsive reactions are important for mannitol accumulation in meristem of kelp. Our transcriptome analysis provides new insights into the transcriptional regulatory networks underlying the biosynthesis of alginate and mannitol during S. japonica developments.

Abstract Background Caulerpa lentillifera is one of the most important economic green macroalgae in the world. Increasing demand for consumption has led to the commercial cultivation of C. lentillifera in Japan and Vietnam in recent decades. Concomitant with the increase of C. lentillifera cultivation is a rise in disease. We hypothesise that epiphytes or other microorganisms outbreak at the C. lentillifera farm may be an important factor contributing to disease in C. lentillifera. The main aims are obtaining differences in the microbial community structure and diversity between healthy and diseased C. lentillifera and key epiphytes and other microorganisms affecting the differences through the results of high-throughput sequencing and bioinformatics analysis in the present study. Results A total of 14,050, 2479, and 941 operational taxonomic units (OTUs) were obtained from all samples using 16S rDNA, 18S rDNA, and internal transcribed spacer (ITS) high-throughput sequencing, respectively. 16S rDNA sequencing and 18S rDNA sequencing showed that microbial community diversity was higher in diseased C. lentillifera than in healthy C. lentillifera. Both PCoA results and UPGMA results indicated that the healthy and diseased algae samples have characteristically different microbial communities. The predominant prokaryotic phyla were Proteobacteria, Planctomycetes, Bacteroidetes, Cyanobacteria, Acidobacteria, Acidobacteria and Parcubacteria in all sequences. Chlorophyta was the most abundant eukaryotic phylum followed by Bacillariophyta based on 18S rDNA sequencing. Ascomycota was the dominant fungal phylum detected in healthy C. lentillifera based on ITS sequencing, whereas fungi was rare in diseased C. lentillifera, suggesting that Ascomycota was probably fungal endosymbiont in healthy C. lentillifera. There was a significantly higher abundance of Bacteroidetes, Cyanobacteria, Bacillariophyta, Ulvales and Tetraselmis in diseased C. lentillifera than in healthy C. lentillifera. Disease outbreaks significantly change carbohydrate metabolism, environmental information processing and genetic information processing of prokaryotic communities in C. lentillifera through predicted functional analyses using the Tax4Fun tool. Conclusions Bacteroidetes, Cyanobacteria, Bacillariophyta, Ulvales and Tetraselmis outbreak at the C. lentillifera farm sites was an important factor contributing to disease in C. lentillifera.

To solve problems of low accuracy and fewer types of human motion state recognized by current smart phones,a method to do hierarchical recognition by using acceleration sensors and gravity sensors was proposed.Firstly,linear acceleration in inertial coordinate system and independent of phone direction was calculated by using the relation between acceleration and gravity acceleration.Secondly,according to the span of human motion frequency and linear acceleration vector,positions of peak and trough of footsteps were determined.Finally,feature vector of linear acceleration in time domain was extracted and human motion states were recognized hierarchically by using hierarchical support vector machine (H-SVM).The experiment shows the method can recognize six usual human motion states,while accuracy rate up to 93.37%.

Aureochrome (AUREO) is a kind of blue light photoreceptor with both LOV and bZIP structural domains, identified only in Stramenopiles. It functions as a transcription factor that responds to blue light, playing diverse roles in the growth, development, and reproduction of Stramenopiles. Most of its functions are currently unknown, especially in the economically important alga S. japonica farmed on a large scale. This study provided a comprehensive analysis of the characteristics of AUREO gene families in seven algae, focusing on the AUREOs of S. japonica. AUREO genes were strictly identified from seven algal genomes. Then AUREO phylogenetic tree was constructed from 44 conserved AUREO genes collected. These AUREO genes were divided into five groups based on phylogenetic relationships. A total of 28 genes unnamed previously were named according to the phylogenetic tree. A large number of different cis-acting elements, especially bZIP transcription factors, were discovered upstream of AUREO genes in brown algae. Different intron/exon structural patterns were identified among all AUREOs. Transcriptomic data indicated that the expression of Sj AUREO varied significantly during the different development stages of S. japonica gametophytes. Periodic rhythms of light induction experiments indicate that Sj AUREO existed in a light-dependent circadian expression pattern, differing from other similar studies in the past. This may indicate that blue light affects gametophyte development through AUREO as a light signal receptor. This study systematically identified and analyzed the AUREO gene family in seven representative brown algae, which lay a good foundation for further study and understanding of AUERO functions in agal growth and development.

Land use change plays a crucial role in global environmental change. Understanding the mode and land use change procedure is conducive to improving the quality of the global eco-environment and promoting the harmonized development of human–land relationships. Large river basins play an important role in areal socioeconomic development. The Yellow River Basin (YRB) is an important ecological protective screen, economic zone, and major grain producing area in China, which faces challenges with respect to ecological degradation and water and sediment management. Simulating the alterations in ecosystem service value (ESV) owing to land use change in the YRB under multiple scenarios is of great importance to guaranteeing the ecological security of the basin and improve the regional ESV. According to the land use data of 1990, 2000, 2010, and 2018, the alterations in the land use and ESV in the YRB over the past 30 years were calculated and analyzed on the basis of six land use types: cultivated land, forestland, grassland, water area, built-up land, and unused land. The patch-generating land use simulation (PLUS) model was used to simulate the land use change in the study area under three scenarios (natural development, cultivated land protection, and ecological protection in 2026); estimate the ESV under each scenario; and conduct a comparative analysis. We found that the land use area in the YRB changed significantly during the study period. The ESV of the YRB has slowly increased by ~USD 15 billion over the past 30 years. The ESV obtained under the ecological protection scenario is the highest. The simulation of the YRB’s future land use change, and comparison and analysis of the ESV under different scenarios, provide guidance and a scientific basis for promoting ecological conservation and high-quality development of river basins worldwide.

This study investigates the recovery of oily sludge using ultrasound-assisted rhamnolipids and uses oil recovery yield as an evaluation index. The Box–Behnken response surface method was employed to investigate the individual and interactive effects of four different operating factors: frequency, dosage, liquid–solid ratio, and stirring speed. The model optimization results showed that the order of degree of influence of these four factors is frequency > liquid–solid ratio > dosage > stirring speed. The mathematical model predicted the highest oil recovery yield as 92.27%, which was highly accurate (in the 95% confidence interval) as from the experimental results, the highest oil recovery yield was 89.95% under optimal reaction conditions (frequency = 25.58 kHz, dosage = 150.45 mg/L, liquid–solid ratio = 4.1:1 mL/g, and stirring speed = 407 rpm). Thus, the deviation from the prediction model was only 2.32%, indicating that this method provides a theoretical basis for the treatment of oily sludge and can be implemented for practical application in Huaidong in the Xinjiang Province.

Urbanization is causing profound changes in ecosystem functions at local and regional scales. The net primary productivity (NPP) is an important indicator of global change, rapid urbanization and climate change will have a significant impact on NPP, and urban expansion and climate change in different regions have different impacts on NPP, especially in densely populated areas. However, to date, efforts to quantify urban expansion and climate change have been limited, and the impact of long-term continuous changes in NPP has not been well understood. Based on land use data, night light data, NPP data, climate data, and a series of social and economic data, we performed a comprehensive analysis of land use change in terms of type and intensity and explored the pattern of urban expansion and its relationship with NPP and climate change for the period of 2000–2015, taking Zhengzhou, China, as an example. The results show that the major form of land use change was cropland to built-up land during the 2000–2015 period, with a total area of 367.51 km2 converted. The NPP exhibited a generally increasing trend in the study area except for built-up land and water area. The average correlation coefficients between temperature and NPP and precipitation and NPP were 0.267 and 0.020, respectively, indicating that an increase in temperature and precipitation can promote NPP despite significant spatial differences. During the examined period, most expansion areas exhibited an increasing NPP trend, indicating that the influence of urban expansion on NPP is mainly characterized by an evident influence of the expansion area. The study can provide a reference for Zhengzhou and even the world's practical research to improve land use efficiency, increase agricultural productivity and natural carbon sinks, and maintain low-carbon development.

Abstract China has been suffering from air quality degradation since its ascension into the World Trade Organization in 2001. The unequal exchange that occurs with international trade—that is, developed countries obtaining larger shares of trade‐related value added relative to the shares of trade‐related air pollution incurred locally—may obstruct the greening of global supply chains. In this study, we conduct a multi‐regional input‐output analysis to examine the change in the distribution of economic benefits and sulfur dioxide emissions underlying China's international trade from 2002 to 2015. The results show that both net trade‐related economic benefits and SO2 emissions in China rapidly increased from 2002 to 2007 and then decelerated after 2007 due to changes in China's green development strategy. In the past 13 years, China has suffered from economic‐environmental inequality due to trade with most developed countries, for example, the United States, the European Union, East Asia, and Canada. East Asia, particularly Japan and South Korea, became both an economic and environmental winner while trading with China in 2015. China has also outsourced emissions to less developed regions, such as Sub‐Saharan Africa. We propose policy implications to further reduce the economic‐environmental inequality underlying China's international trade.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the recently emerged virus responsible for the COVID-19 pandemic. Clinical presentation can range from asymptomatic disease and mild respiratory tract infection to severe disease with lung injury, multiorgan failure, and death. SARS-CoV-2 is the third animal coronavirus to emerge in humans in the 21st century, and coronaviruses appear to possess a unique ability to cross borders between species and infect a wide range of organisms. This is somewhat surprising as, except for the requirement of host cell receptors, cell–pathogen interactions are usually species-specific. Insights into these host–virus interactions will provide a deeper understanding of the process of SARS-CoV-2 infection and provide a means for the design and development of antiviral agents. In this study, we describe a complex analysis of SARS-CoV-2 infection using a genome-wide CRISPR-Cas9 knock-out system in HeLa cells overexpressing entry receptor angiotensin-converting enzyme 2 (ACE2). This platform allows for the identification of factors required for viral replication. This study was designed to include a high number of replicates (48 replicates; 16 biological repeats with 3 technical replicates each) to prevent data instability, remove sources of bias, and allow multifactorial bioinformatic analyses in order to study the resulting interaction network. The results obtained provide an interesting insight into the replication mechanisms of SARS-CoV-2.

Ni-Cr-Mo-based superalloy is widely used as a key component in many critical environments. To ensure that the manufacturing process does not impact the long-term service performance of these components, the aging precipitation behavior at different temperatures and its effect on intergranular corrosion (IGC) resistance and wear resistance of a Ni-Cr-Mo-based C276 superalloy were investigated. The equilibrium phase diagram was calculated first using thermodynamic software to confirm the potential phases. Carbides of M6C were found to be formed at grain boundaries after aging at 800–850 °C for short-term treatment. The other two phases (μ phase and P phase) indicated in the phase diagram were not observed for the samples after aging treatment up to 15 h. Furthermore, double loop electrochemical potentiokinetic reactivation (DL-EPR) tests were conducted to examine the IGC resistance. The degree of sensitization increased with the aging time and severe corrosion was found to occur at grain boundaries. For the first time, the influence of aging treatment on the wear behavior of this superalloy has been specifically studied. Concerning the hot processing of Ni-Cr-Mo-based C276 superalloy, these results indicate the importance of avoiding high-temperature heat treatment for long periods.

The microstructure evolution of 316L stainless steels subjected to torsion deformation and its corrosion resistance in 1 M H _2 SO _4 solutions were studied. Microstructure evolution of the annealed and torsion-processed samples was characterized by x-ray diffraction and electron backscatter diffraction techniques. The results showed that no martensitic transformation occurred during torsion deformation, while dynamic recrystallization occurred within the samples slowing down the tendency of increasing dislocation density and storage energy. Electrochemical tests including potentiodynamic polarization tests and electrochemical impedance spectroscopy (EIS) were used in the 1 M H _2 SO _4 solution to evaluate the corrosion resistance of the annealed and torsion-processed samples. The results illustrated that small deformation (torsion for 1 turn) could enhance the corrosion resistance of the 316L stainless steels by increasing the stability of the passive film, the medium deformation (torsion for 3 turns) will deteriorate the corrosion resistance due to high-density dislocations formed during torsion deformation, while large deformation (torsion for 5 turns) could improve the corrosion resistance compared with the medium deformation due to the occurrence of dynamic recrystallization and the high-density deformation twins formed.

Land use change is the second largest source of greenhouse gas emissions after fossil combustion, which can hurt ecological environment severely. Intensive study on land use carbon emissions is of great significance to alleviate environmental pressure, formulate carbon emission reduction policy, and protect ecological development. The lower Yellow River area is an important area of economic development, grain cultivation, and agricultural production in China. Land use change has significant economic, environmental, and ecological impacts in this region. Deep study of land used carbon emissions and its influencing factors in the lower Yellow River area is not only of great significance to the environmental improvement in the Yellow River basin, but also can provide references for the research of other basins. Based on this, this paper studies the land use carbon emissions of 20 cities in the lower Yellow River area from 1995 to 2018. The results showed that from 1995 to 2018, the land use change was characterized by the decrease of the ecological land and the increase of the built-up land significantly. The overall carbon emission of the lower Yellow River area is increasing, and the built-up land is the main factor that leads to the increase of carbon emission, which can be also proven by the analysis of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The economic contributive coefficient (ECC) and ecological support coefficient (ESC) of carbon emission in the lower Yellow River area show a trend of high in Zhengzhou, Jinan, and Zibo and low in Zhoukou, Shangqiu, and Heze, and there was no significant changes during the study period, which indicates that each city did not achieve the coordinated development of the ecological economy. Finally, analysis results of the STIRPAT model indicated that the area of built-up land had the greatest impact on land use carbon emissions, followed by tertiary industry, whereas per capita gross domestic product (GDP) had the smallest impact. For every 1% increase in the area of built-up land, carbon emissions increased by 1.024%. By contrast, for every 1% increase in the contribution of tertiary industry to the GDP and per capita GDP, carbon emissions decreased by 0.051% and 0.034%, respectively. According to the study, there are still many problems in the coordinated development of economy and ecology in the lower Yellow River area. The lower Yellow River area should control the expansion of built-up land, afforestation, development of technology, reduction of carbon emissions, and promotion of the high-quality development of the Yellow River Basin.

Attaining accurate precipitation data is critical to understanding land surface processes and global climate change. The development of satellite sensors and remote sensing technology has resulted in multi-source precipitation datasets that provide reliable estimates of precipitation over un-gauged areas. However, gaps exist over high latitude areas due to the limited spatial extent of several satellite-based precipitation products. In this study, we propose an approach for the reconstruction of the Tropical Rainfall Measuring Mission (TRMM) 3B43 monthly precipitation data over Northeast China based on the interaction between precipitation and surface environment. Two machine learning algorithms, support vector machine (SVM) and random forests (RF), are implemented to detect possible relationships between precipitation and normalized difference vegetation index (NDVI), land surface temperature (LST), and digital elevation model (DEM). The relationships between precipitation and geographical location variations based on longitude and latitude are also considered in the reconstruction model. The reconstruction of monthly precipitation in the study area is conducted in two spatial resolutions (25 km and 1 km). The validation is performed using in-situ observations from eight meteorological stations within the study area. The results show that the RF algorithm is robust and not sensitive to the choice of parameters, while the training accuracy of the SVM algorithm has relatively large fluctuations depending on the parameter settings and month. The precipitation data reconstructed with RF show strong correlation with in situ observations at each station and are more accurate than that obtained using the SVM algorithm. In general, the accuracy of the estimated precipitation at 1 km resolution is slightly lower than that of data at 25 km resolution. The estimation errors are positively related to the average precipitation.

Mannitol plays a crucial role in brown algae, acting as carbon storage, organic osmolytes and antioxidant. Transcriptomic analysis of Saccharina japonica revealed that the relative genes involved in the mannitol cycle are existent. Full-length sequence of mannitol-2-dehydrogenase (M2DH) gene was obtained, with one open reading frame of 2,007 bp which encodes 668 amino acids. Cis-regulatory elements for response to methyl jasmonic acid, light and drought existed in the 5'-upstream region. Phylogenetic analysis indicated that SjM2DH has an ancient prokaryotic origin, and is probably acquired by horizontal gene transfer event. Multiple alignment and spatial structure prediction displayed a series of conserved functional residues, motifs and domains, which favored that SjM2DH belongs to the polyol-specific long-chain dehydrogenases/reductase (PSLDR) family. Expressional profiles of SjM2DH in the juvenile sporophytes showed that it was influenced by saline, oxidative and desiccative factors. SjM2DH was over-expressed in Escherichia coli, and the cell-free extracts with recombinant SjM2DH displayed high activity on D-fructose reduction reaction. The analysis on SjM2DH gene structure and biochemical parameters reached a consensus that activity of SjM2DH is NADH-dependent and metal ion-independent. The characterization of SjM2DH showed that M2DH is a new member of PSLDR family and play an important role in mannitol metabolism in S. japonica.

In this paper, an adaptive collaborative Gaussian Mixture Probability Hypothesis Density (ACo-GMPHD) filter is proposed for multi-target tracking with automatic track extraction. Based on the evolutionary difference between the persistent targets and the birth targets, the measurements are adaptively partitioned into two parts, persistent and birth measurement sets, for updating the persistent and birth target Probability Hypothesis Density, respectively. Furthermore, the collaboration mechanism of multiple probability hypothesis density (PHDs) is established, where tracks can be automatically extracted. Simulation results reveal that the proposed filter yields considerable computational savings in processing requirements and significant improvement in tracking accuracy.