In order to achieve accurate computer-aided diagnosis of Alzheimer’s disease (AD)and mild cognitive impairment (MCI) patients, this paper proposes a multimodal Alzheimer’s multi-class diagnostic framework (MAMDF) that uses an asymmetric cross-attention mechanism for multimodal fusion to better reveal the relationship between clinical data and medical imaging data. Moreover, to address the two MCI subtypes that are rarely mentioned in previous computer-aided diagnosis work, we combined frequency-domain transformers and Transformers to propose a novel deep feature extraction module for feature fusion. This method captures the internal connections of fused features and obtains richer multimodal joint representations, thus improving the diagnostic performance of the model on the two MCI subtypes. Experimental results on the ADNI dataset show that the proposed model achieves higher accuracy and F1 scores, compared with similar works. Thus the model can more effectively handle multimodal data fusion and mine the deep feature relationships between different modal medical data, thereby better integrating and analyzing the multimodal information of AD patients. 

This paper examines the working conditions and advantages of artificial intelligence (AI) and human intelligence (HI) concerning task input, processing, output, and constraints, leading to the identification of eleven AI-HI task characteristics. Based on these characteristics, we develop four AI-HI indices: AI Usability Index, AI Superiority Index, HI Superiority Index, and HI Safety Index. These indices inform a proposed typology of four task types: AI Non-Usable, AI Superior, AI-HI Collaborative, and HI Superior. This framework underpins a novel AI-HI task characteristic-classification model. Finally, taking accounting tasks as a case, the model is applied to analyze nineteen core accounting tasks, and assess their AI-HI characteristics, indices, and resultant classifications. The result can provide a rigorous analysis of the division of labor and substitution between AI and HI, offering a theoretical foundation for a transition from adversarial to symbiotic collaboration.

This paper constructed a dataset of China’s abandoned farmland from 2000 to 2020, and analyzed the evolution characteristics and leading factors of the spatial pattern. The findings are as follows. 1) From 2000 to 2020, the abandoned area and abandonment rate showed a continuous growth trend, with the abandoned area increasing from 255.96×10⁴ hm² to 3113.03×10⁴ hm², and the abandonment rate increasing from 1.29% to 14.08%. The areas with a higher abandonment rate were concentrated in the west side of the Hu Line. 2) There was a significant spatial autocorrelation of farmland abandonment. The “high-high” agglomeration area continued to expand and was concentrated on both sides of the Hu Line, while the “low-low” agglomeration area was mainly distributed in the eastern plain area. Meanwhile, as the abandonment rate continued to rise, a phenomenon of polarization emerged within agricultural regions. 3) In 2020, five factors, including soil type, population density, elevation, rural population proportion and geomorphic type, had strong explanatory power to the spatial differentiation of farmland abandonment. The results of two-factor detection showed nonlinear or double-factor enhancement, and the synergistic driving effect within the natural environmental factor group was stronger. On the basis of natural environmental factors, the explanatory power of socio-economic factors was obviously enhanced.

In order to actively promote the construction of low-carbon universities, taking the Yanyuan Campus of Peking University as a case study, we utilized the carbon emission factor method to calculate the total campus carbon emissions for 2023. The results are as follows. Firstly, total carbon emissions of Peking University main campus for 2023 exceeded 250000 tons, with Scope 1 (direct emissions) accounting for 17.20%, Scope 2 (indirect emissions from purchased energy) for 55.31%, and Scope 3 (other indirect emissions) for 27.49%. Secondly, compared with the carbon emissions in 2009, Scope 1 and Scope 2 carbon emissions increased by 16.76%, while per capita carbon emissions decreased by 19.10%. Based on the calculated carbon emission scenarios, we propose carbon reduction recommendations targeting the three major sources of carbon emissions at Peking University main campus — energy consumption, transportation, and food consumption. It is estimated that the potential to reduce carbon emissions in energy consumption is more than 30%, more than 5% in transportation, and more than 3% in food consumption. The total carbon reduction potential in these three areas is close to 40%, equivalent to over 120000 tons of carbon emissions annually. 

Based on 30 m horizontal resolution digital elevation models and remote sensing images, this study extracted 7th stream-order river network of 32 endorheic rivers in the Junggar Basin and analyzed the hierarchical river network structure of endorheic sub-basins under different underlying surface conditions (glacier-dominated and desert-dominated types) in arid climate. The results indicate that although the sub-basins in the Junggar Basin generally conform to the self-similarity law of river network structure across stream orders 1 to 4, the glacier-dominated sub-basins exhibit higher bifurcation ratios and drainage densities than the desert-dominated sub-basins, due to their greater precipitation and higher vegetation coverage. Further analysis reveals that the structural parameters of river networks in glacier-dominated basins are primarily controlled by temperature, potential evapo-transpiration, and soil water content, whereas in desert-dominated basins, these parameters correlate more closely with oasis area and vegetation characteristics.

Citric acid was used as the carbon source, and three phenylenediamine isomers — o-phenylenediamine, m-phenylenediamine, and p-phenylenediamine — served as nitrogen sources to synthesize carbon quantum dots (CQDs) via a hydrothermal method. The resulting CQDs exhibited distinct colors: orange-yellow (o-phenylenediamine), light yellow (m-phenylenediamine), and purple (p-phenylenediamine). The CQDs were subsequently modified with oleylamine to introduce hydrophobic surface properties. Structural and optical properties before and after modification were characterized using Fourier transform infrared spectroscopy (FT-IR), fluorescence spectroscopy (FS), and ultraviolet-visible spectroscopy (UV-vis). The results indicate that the CQDs derived from m-phenylenediamine showed the most enhanced hydrophobicity after oleylamine modification, with significantly improved solubility in toluene, which is attributed to strengthened hydrocarbon interactions.

In order to study the differences, seasonal variations and influencing factors of soil CO₂ concentration in different ecosystems, we conducted annual fixed-point monitoring of soil CO₂ concentration, oxygen (O₂) levels, enzyme activities, and labile carbon/nitrogen indicators across suburban wasteland, forestland, and grassland ecosystems from March 2023 to February 2024. The results revealed that the grassland had the highest average annual CO₂ concentration, followed by the forest, with the wasteland having the lowest. The subsurface soil CO₂ concentration of each ecosystem was higher than that of surface layer. The soil CO₂ concentration of the three ecosystems was high in summer and low in winter, and was in the middle in spring and autumn. There were disparities in soil physical and chemical properties, carbon and nitrogen contents, and hydrolase activities among different ecosystems. In all ecosystems, the soil CO₂ concentration increased exponentially with rises in air temperature, soil temperature and water content, yet displayed an exponential negative correlation with oxygen concentration.

A measurement tool for environmental sensitivity among Chinese college students was developed, and its reliability and validity were tested. An initial questionnaire was compiled through interviews, with reference to existing scales. In Sample 1, 2416 college students were selected as participants, with item analysis and exploratory factor analysis performed using SPSS. Sample 2 included 3605 college students, who completed the initial College Student Environmental Sensitivity Scale and a criterion tool. For this sample, SPSS, AMOS and Mplus were used to conduct confirmatory factor analysis, criterion-related validity analysis and measurement equivalence test, yielding a final 18-item scale with four dimensions. The confirmatory factor analysis results showed good model fit and satisfactory construct validity. The Cronbach’s α coefficient was 0.86, indicating good internal consistency. Using the total score of the SCL-90 scale and some dimension scores as criteria, a significant positive correlation was found. The College Student Environmental Sensitivity Scale demonstrates cross-gender and cross-grade equivalence, with good reliability and criterion validity among college students. It can thus be used to evaluate and study environmental sensitivity in Chinese college students.

For a spherical layered Earth model, by assuming that the medium parameters in each layer follow specific variation laws and introducing earth flattening transformation, the ordinary differential equations (ODEs) with variable coefficients in the spherical model are transformed into ODEs with constant coefficients that can be solved using the generalized reflection-transmission coefficient method (GRTCM), and the theoretical seismograms are calculated. Numerical results show that the generalized reflection-transmission coefficient method is accurate and efficient for computing theoretical seismograms at epicentral distances within 100 degrees. The error of the method will be significantly reduced as the layer thickness of spherical model is reduced. 

In order to explore the effects of different malts on the flavor of beer after fermentation, the differences between 5 barley malts and 5 wheat malts on beer composition were analyzed by using metabolomics methods. The effects of different malts on the metabolic pathway of Saccharomyces cerevisiae during beer fermentation were explained at the metabolic level. After liquid chromatography-mass spectrometry (LC-MS) detection, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis were performed to screen out the key metabolites that had the greatest impact on beer flavor. After linking the key metabolites to the flavor of beer, pathway enrichment was carried out. The results determined that barley malt mainly affects Purine metabolism, Pyrimidine metabolism, Arginine and proline metabolism, Alanine, aspartic acid and glutamate metabolism, Arginine biosynthesis, β-Alanine metabolism, Nicotinate and nicotinamide metabolism, Galactose metabolism and other pathways. Wheat malt mainly affects Purine metabolism, Pyrimidine metabolism, Arginine and proline metabolism, and Glutathione metabolism. These metabolic pathways have a key impact on the flavor of beer, which provides some theoretical guidance for the regulation of flavor substances in beer.

Using water-sediment microcosms and 16S rRNA and 18S rRNA sequencing analyses, phenanthrene (PHE) was selected as a representative compound of PAHs to explore its effects on water quality, as well as on the diversity, structure, and function of sediment microbial communities. The results indicated that PHE pollution affected both the magnitude and stability of water quality parameters. PHE was predominantly adsorbed onto the sediment, with a degradation efficiency of 99% observed on day 56 in the PHE treatment group. Significant differences were found in bacterial communities (R_ANOSIM = 0.293, P = 0.002) and fungal communities (R_ANOSIM = 0.147, P = 0.031) among different treatment groups. The relative abundance of many bacteria, archaea, and fungi associated with PHE degradation was higher in the PHE treatment groups than that in the control group. Compared with the control and low-dosage (PHE(L)) groups, microbial networks in the medium-dosage (PHE(M)) and high-dosage (PHE(H)) groups exhibited higher average clustering coefficients and positive correlations. Functional processes such as carbon fixation, nitrogen metabolism, and sulfur metabolism had lower relative abundance in the later incubation stages in the PHE(M) and PHE(H) groups, while methane metabolism had higher relative abundance. pH was identified as the key factor influencing the structures and functions of bacterial, archaeal, and fungal communities, followed by NH₄⁺-N. 

Existing Twitter bot detection methods often overlook the structural and temporal information of users’ dynamic social history, as well as the noise accumulation resulting from feature fusion. In order to address these limitations, this paper constructs STKG (social temporal knowledge graph) and proposes a Twitter bot detection method STKGBot (STKG for Twitter bot detection). In the STKG, STKGBot uses RE-GAT (heterogeneity-enhanced graph attention network) to learn the static social relationship feature, TE-GCN (temporal-enhanced graph convolutional network) to learn the dynamic social history feature, and a bilinear model for the feature fusion. In addition, STKGBot employs contrastive learning to alleviate the noise aggravation in the process of feature fusion. Experimental results on two public datasets demonstrate that STKGBot outperforms state-of-the-art models.

Based on the household survey data of 734 relocated migrants in Guizhou Province, this study selects 17 indicators from five major livelihood capitals, namely, natural capital, physical capital, financial capital, human capital and social capital, to construct a livelihood capital evaluation index system for relocated migrants. Using the system, we evaluate the dynamic change of migrants’ livelihood capital in the relocation project for poverty alleviation, to analyze the mechanism of the impact of the livelihood capital on the selection of livelihood strategies. The results show that, 1) Different types of resettlement sites lead differences in the changes of livelihood capital of immigrant families in the process of poverty alleviation and relocation. Among them, the improvement effect of the livelihood capital of the immigrants in the county settlement is the most obvious. From 2019 to 2022, the number of immigrant families with better and above levels of livelihood capital increased by 55.04%; 2) Social capital is the largest contribution dimension affecting the comprehensive change of livelihood capital, with a minimum impact of 38.87%; natural capital and material capital are the biggest obstacle dimensions, with the highest impact of 12.78% and 6.71%, respectively, and are also the factors that migrants need to pay attention to and take into account when they choose their livelihood strategies. 3) According to the characteristics of livelihood strategy type transformation and the difference of per capita income of immigrant families, it is found that the livelihood strategies adopted by migrants in the market town lead to the fastest growth in their per capita income, which reaches 59.05%, while the overall improvement of migrants’ families in the county town is more stable. Accordingly, the paper puts forward some optimization countermeasures, such as increasing the protection of cultivated land in central villages, promoting the consumption of migrants in market towns, strengthening the management of livelihood capital of migrants in county towns. 

This paper analyzes the characteristics and impact factors of spatial assimilation of the floating population from the neighborhood scale, using the 2015 population data in the Shenzhen managed population database. The results show that the floating population is the main group of residents in Shenzhen and clearly differentiated, and consists of a large proportion of rural migrants. Rental housing, marriage, education, and the proportion of residents with agricultural hukou have significant positive effects on spatial assimilation, but the duration of residence has no significant influence. Compared with public housing, commercial housing and restricted property housing are easier for the floating population to realize spatial assimilation. It is necessary for the government to improve the management of the rental housing market and increase the proportion of urban housing owned by the floating population in order to promote their socio-spatial integration. 

Based on field outcrop observations in the north Tarim Basin and thin-section observations of typical drilling wells, we accurately established a sedimentary model and finely characterized the spatiotemporal distribution patterns of high-energy mound and shoal facies. The results show that a carbonate ramp is developed in Xiaoerbulake Formation in Tarim Basin. The types of sedimentary facies include mixed tidal flat, inner-ramp (dolomite-flat, lagoon and shoal), middle-ramp (inner zone, outer zone, microbial mounds, and shoal) and outer ramp-basins. By characterizing the spatiotemporal distribution of sedimentary facies within the isochronous stratigraphic framework, an internal depression and distally steepening carbonate ramp model was established. The high-energy mound and shoal facies deposits with high-quality reservoirs are mainly affected by the original paleogeomorphy and fluctuation of relative sea level. The middle-ramp shoals are developed in Tazhong area, the middle-ramp mounds and shoals are developed in Bachu area and Keping area, and the middle-ramp shoals are developed in the high paleogeomorphy of Lunnan area.

The introduction to Bayesian methods is presented from the perspective of inversion modeling, outlining the fundamental principles, computational techniques, development history, and current research status. Various methods and their applications across different fields of geology and geochemistry are analysed in detail. Finally, the future development directions and challenges are discussed.

Vanadium slag (VS) and vanadium tailing slag (DVS) were used as raw materials, respectively. Metal elements in them were leached out with sulfuric acid (as the active components of the catalysts), co-precipitated with NaOH, and then two types of vanadium slag-type catalysts (CVS and CDVS) were prepared via hydrothermal synthesis for the catalytic combustion of toluene. X-ray fluorescence (XRF), Brunauer-Emmett-Teller (BET), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS) were used to characterize and analyze the vanadium slag catalysts, including their elemental composition, textural property, surface morphology, and surface electronic environment. The results showed that the vanadium slag catalysts prepared by this method were mainly iron-containing oxides with a well-developed mesoporous structure. The specific surface area of CVS (derived from VS) was up to 190 m²/g, with a narrow pore size distribution and a pore volume of 0.33 cm³/g. CVS had a stronger adsorption capacity for oxygen species on its surface, which contributed to its good catalytic activity for toluene, with T₅₀ and T₉₀ of 202°C and 246°C, respectively.

Based on the output and energy consumption data of major industrial products in Henan Province (especially those related to coal), referring to the carbon emission guidelines of the IPCC and combining with multiple linear regression analysis, a carbon emission regression model for Henan Province was constructed. Factor analysis was conducted using SPSS 27.0 software to calculate the scores of high-quality development of prefecture-level cities, and a low-carbon, green and high-quality development model was established to explore the key driving factors affecting the high-quality development of prefecture-level cities. The following results were obtained. 1) Carbon emissions in Henan Province mainly come from production, transportation, construction and daily life. The eastern, northern and central regions of Henan are the main carbon sources, while carbon sinks are mainly concentrated in forest land and cultivated land, which makes the carbon sink storage in the western and southern regions of Henan relatively high. 2) The level of low-carbon, green and high-quality development in Henan Province is on the rise, with significant spatial differences in the calculated scores. Specifically, Zhengzhou City (253), Nanyang City (53) and Luoyang City (49) rank the top three. 3) Zhoukou City has a relatively high score (21) for low-carbon, green and high-quality development, but its total carbon emissions are relatively low (4.28×10⁶ t), and its carbon emissions per unit of energy are relatively high. It belongs to an industrial factor-driven development model. Pingdingshan City has a relatively low score (–25) in low-carbon, green and high-quality development, a high total carbon emission (1.16×10⁷ t), and a high carbon emission per unit of population. It belongs to a development model driven by population factors. 4) To promote high-quality regional development and provide a favorable external development environment, Henan Province should optimize the industrial structure, adjust the energy consumption structure, promote balanced regional development, optimize the industrial layout and improve the ecological compensation mechanism. 

Based on the river networks extracted from digital elevation models (DEMs) at 30 m resolution, combined with the remote sensing data, the hierarchical rules of the structural and morphological characteristics of the 6th–7th order river networks in the middle and upper Yellow River basin were analyzed. The results show that the river networks of the middle and upper Yellow River sub-basins present significant self-similar characteristics in the range of 1–5 orders. The middle reaches of the Yellow River sub-basins have higher bifurcation ratio (R_B=4.83), river width ratio (R_W=2.13) and average river length (L=4.80 km), while the upper reaches of the Yellow River basin have higher density (D=1.25 km⁻¹). In terms of river network structure, aridity index, soil water content and vegetation coverage are the main factors affecting the river network structure in the middle of the Yellow River sub-basins, while the river network structure in the upper reaches of the Yellow River sub-basins are more related to the average slope of the basin and soil erodibility. Further analysis of four typical sub-basins in the middle reaches of the Yellow River basin shows that although the typical sub-basins in the loess region have relatively higher sediment production capacity, their sediment transport capacities may be affected by the river network structure and channel morphology. This study reveals the role of river network structure and channel morphology as indicators of water and sediment transport characteristics, and emphasizes the necessity of differentiated river management measures for basins in the Yellow River basin with different underlying surface characteristics.

Utilizing high-precision shipborne multibeam bathymetry and gravity anomaly data, we analyzed the fault structures and magmatic characteristics of the Mid-Atlantic Ridge (MAR) segment between 30.00°N and 31.55°N. Firstly, based on the multibeam bathymetry data, slope, roughness, and curvature information in the study area, we identified two main geomorphological patterns: faults and volcanic features. The fault geomorphology was further divided into three typical fault styles: detachment faults, E-type faults, and C-type faults. In the entire region, E-type faults are mainly distributed within the area 20–50 km away from the ridge axis on both flanks, while C-type faults are more densely distributed in the near-axis region and the rift valley of the MAR, within 0–20 km from the axis. Subsequently, the horizontal fault heaves and tectonic strain rate (T) values were calculated based on 13 cross-axis profiles. The results indicate a significant asymmetric spreading phenomenon in the region. In areas with sufficient magma supply, or near the ridge axis and the rift valley, the T values are relatively small, typically forming a thicker oceanic crust and C-type faults with smaller horizontal fault offsets. In areas with depleted magma supply or farther away from the mid-ocean ridge, a thinner oceanic crust is often formed, with larger T values and more prevalent E-type faults and detachment faults with larger horizontal fault offsets.