Density Analysis Research Articles

WITHDRAWN: Multi-layers hexagonal hole MXene trap constructed by carbon vacancy defect regulation strategy enables high energy density potassium-ions storage

Due to the slow reaction kinetics of potassium-ions with large size radius in layered materials, the energy density of aqueous potassium-ion hybrid supercapacitors (PIHCs) is severely limited. At the same time, the treatment of defects is a "double-edged sword" in energy storage materials, which requires targeted and precise regulation. In order to solve this problem, multi-layers hexagonal hole MXene trap was constructed by using the carbon vacancy defect regulation strategy, and high specific capacitance and energy density potassium-ion storage was realized in PIHCs. The structure-activity relationship at the atomic level was elucidated in combination with the pseudo-capacitance effect caused by the change of valency of newly exposed titanium atoms in the inner wall of the hexagonal hole MXene trap. By density functional theory, the adsorption energy and kinetic analysis of multi-layers hexagonal hole MXene for potassium-ions were calculated, and the optimal position and quantity of potassium-ions were determined. By quantitative analysis of electron band structure and differential charge density, the internal mechanism of high conductivity and energy density of multi-layers hexagonal hole MXene PIHCs was revealed.

A Convolutional Neural Network Classifies Beat-to-Beat Arterial Pressure Spectrograms and Wavelet Transforms according to Age, Sex, and Metabolic State: Novel Frequencies for Cardiovascular Risk Appraisal

Hemodynamic homeostasis is under the control of multiple systems. Continuous blood pressure (BP) time series carry information relevant to the pathophysiological status of the cardiovascular system. Beside average BP, different measures of variability provide prognostic value for distinguishing between cardiovascular risk states. The latter are derived from time- and frequency- domain analysis of BP recordings and are limited by their capacity to provide cumulative risk appraisal among different risk groups. The prediabetic state is associated with cardiovascular risk which is often described to be age- and sex-specific. In this study, we sought to determine distinctive features of continuous arterial pressure (AP) time-series for risk appraisal in a pre-established prediabetic rat model. To overcome the shortcomings associated with conventional BP variability parameters, we trained a convolutional neural network (CNN) using spectrograms and scalograms generated from short-term Fourier- and Morlet wavelet- transforms of AP time series, respectively, from male and female prediabetic rats fed a mild hypercaloric diet for 12- or 24- weeks and their corresponding controls. The CNN consisted of 5 convolutional layers, separated by batch normalization, ReLU activation, and max pooling. The outcome of the fifth convolutional layer had 40% of the data dropped out and delivered to a fully-connected dense layer and then to a softmax function. The data was divided into 80% training, 10% validation, and 10% test sets. The model classified spectrograms and scalograms with test accuracy of 90%+ for the different binary and multi-class classification tasks. On backward propagation of model scores, different salient frequencies were identified as critical features for classification of AP time-series. The identified frequencies were much higher than those typically used in conventional power spectral density (PSD) analysis. Using 3-way ANOVA or principal component analysis for comparison and clustering of the different cardiovascular risk groups of age, sex, and metabolic disease, respectively, according to PSD at the identified peaks does not yield suffcient risk appraisal. This indicates that the CNN possibly captures non-linear relations which are undetectable using inherently linear methods.The results indicate sex- and age-specific patterns of cardiovascular deterioration in prediabetes. Use of artificial intelligence models for the identification of abnormal BP fluctuation patterns can provide suffcient risk appraisal needed for early intervention, particularly in at-risk patients lacking clinical signs of overt cardiovascular disease. None. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

On-machine frequency analysis of diamond turned surfaces with surface intrinsic mode decomposition

Evaluating surface frequency components in the fabrication process is critical for controlling the machined surface quality. The presence of anisotropic ripples on diamond-turned surfaces makes this challenging. A multiscale frequency evaluation method, referred to as Surface Intrinsic Mode Decomposition (SIMD), is proposed for evaluating on-machine surface measurement (OMSM) data. It decomposes continuous surface probing profiles, incorporating both temporal and spatial frequency information. In comparison to the conventional power spectral density (PSD) analysis method, the approach enriches frequency details over a wider range, which contributes to a more comprehensive understanding of surface quality and helps to identify mid-spatial frequency (MSF) errors.

Geothermal potential area analysis using Landsat 8 OLI/TIRS and digital elevation model images (case study: Lawu Mount, Central Java)

Mount Lawu is one of the volcanoes in Central Java Province with hidden geothermal potential. This research aims to identify geothermal potential areas, especially hydrothermal alteration areas, using Landsat 8 imagery in Mount Lawu, Central Java. Hydrothermal alteration serves as a crucial indicator in the exploration of geothermal potential in an area. Multispectral image processing methods of Landsat 8 are employed to map the distribution patterns of hydrothermal alterations in the study area, together with the anomaly of temperature and heatflux in the surface. This approach involves principal component analysis and spectral alteration indications that combine information from various image channels. Lithology and lineament density analysis strengthen the delineation and analysis of the geothermal potential area. The western-northwestern part of Mount Lawu is the most potential region for geothermal resources based on the distribution of hydrothermal alteration areas and the high density of faulted regions, which are also supported by geothermal manifestations such as hotspring sites in the area.

Research on intelligent sensor for industrial hazardous gases monitoring based on Tc doped C3N using density functional theory

With the ongoing global industrialization, a considerable amount of hazardous gases is emitted into the atmospheric environment. Achieving intelligent monitoring of industrial hazardous gases is a crucial pathway toward realizing the modernization of electronic information. In this study, the use of Tc doped C3N nanosheet for the intelligent online monitoring of industrial hazardous gases (CO, NO2, O3) is firstly proposed. The doping and modification mechanism of Tc nanoparticle on the C3N surface are revealed. Simultaneously, the adsorption and sensing mechanisms of the three target gases on the surface of pure C3N and Tc doped C3N nanosheet is deeply elucidated through density of states, band structure, and differential charge density analysis. The results indicate that Tc particle can stably bind to the C3N surface, providing numerous active sites for the adsorption of target gases, enabling selective capture and scavenging of hazardous gases. Furthermore, the adsorption type for all three gases shifts from physical adsorption to physicochemical adsorption, with significant changes in the electronic signals during surface reactions, manifested by drastic alterations in the band structure and enhanced electron mobility. The adsorption capacity order for the three gases is O3 > NO2 > CO. The achievements of this work not only provide a theoretical foundation for the design and preparation of Tc doped C3N nanosensors, but also offer a new direction for environmental protection and intelligent detection in industrial applications.

Investigating the Effect of Contextual Cueing with Face Stimuli on Electrophysiological Measures in Younger and Older Adults.

Extracting repeated patterns from our surroundings plays a crucial role in contextualizing information, making predictions, and guiding our behavior implicitly. Previous research showed that contextual cueing enhances visual search performance in younger adults. In this study, we investigated whether contextual cueing could also improve older adults' performance and whether age-related differences in the neural processes underlying implicit contextual learning could be detected. Twenty-four younger and 25 older participants performed a visual search task with contextual cueing. Contextual information was generated using repeated face configurations alongside random new configurations. We measured RT difference between new and repeated configurations; ERPs to uncover the neural processes underlying contextual cueing for early (N2pc), intermediate (P3b), and late (r-LRP) processes; and multiscale entropy and spectral power density analyses to examine neural dynamics. Both younger and older adults showed similar contextual cueing benefits in their visual search efficiency at the behavioral level. In addition, they showed similar patterns regarding contextual information processing: Repeated face configurations evoked decreased finer timescale entropy (1-20 msec) and higher frequency band power (13-30 Hz) compared with new configurations. However, we detected age-related differences in ERPs: Younger, but not older adults, had larger N2pc and P3b components for repeated compared with new configurations. These results suggest that contextual cueing remains intact with aging. Although attention- and target-evaluation-related ERPs differed between the age groups, the neural dynamics of contextual learning were preserved with aging, as both age groups increasingly utilized more globally grouped representations for repeated face configurations during the learning process.

Impact of channel thickness on device scaling in vertical InGaZnO channel charge-trap memory transistors with ALD Al2O3 tunneling layer

This study investigates the impact of channel thickness (TCH) variation on memory performance and its physical origins in vertical channel charge trap memory (V-CTM) using InGaZnO (IGZO) channels for X–Y scaling. When the TCH decreased, the subthreshold slope (SS) increased from 0.21 to 0.30 V/dec, while the minimum program voltage decreased from 12 to 8 V, indicating a performance trade-off. The analysis of bulk trap density extracted by SS, density of states distribution, and x-ray photoelectron spectroscopy confirmed an increase in the number of trap states and hydrogen-related defects in the IGZO channel when a thin TCH is employed. As a result, it was expected that the barrier height at the active layer/TL would be lowered during program operations at relatively thin channel. However, the SS would also be degraded due to an increase in sub-gap states, such as OH- and VOH, induced by hydrogen incorporation. The V-CTM with an optimal TCH of 7 nm had a maximum memory window of 5.7 V. The program/erase states were maintained for 106 s before experiencing a 50 % charge loss, and 5-level memory states were verified to be available within a memory window of 3.2 V for 108 s with little degradation. It was noteworthy that the long-term reliability and multilevel implementation could be secured for the V-CTM with a TCH as thin as 7 nm, demonstrating the sound feasibility of its X–Y scaling. This work presents new key parameters and understanding of device integration issues for future 3D structured memory transistors, and aims to contribute to the advancement of memory technologies using oxide semiconductor channels.

Unveiling the mechanism and selectivity of the [3 + 2] cycloaddition reactions of nitrone with acetylene derivatives leading to anticancer 4-isoxazoline derivatives from the MEDT perspective

The [3 + 2] cycloaddition reactions of N-methyl-C-(2-furyl) nitrone (a) with a series of acetylene derivatives (4b), (5b), and (6b) have been studied at the B3LYP-D3/6-31G(d) computational level within the framework of Molecular Electron Density Theory. Topological analysis allows classifying the nitrone (a) as a zwitterionic (zw-) three-atom component (TAC) associated with high energy barrier. These 32CA reactions follow a one-step mechanism under kinetic control with highly asynchronous bond formation. Bonding Evolution Theory (BET) analysis indicates that no new covalent CO and CC bonds form at the transition states (TSs). Interestingly, the global electron density transfer (GEDT) between 0.08 and 0.18 e predicts low polar character of forward electron density transfer (FEDF) type with the electronic flux from the nitrone (a) to the acetylene derivatives. Electron localization function (ELF) and atom-in-molecules (AIM) topological analysis of the electron density at the TS structures characterize the non-concerted nature of these one-step zw-type 32CA reactions.

A Study on the Density Analysis of Multi-objects Using Drone Imaging

A Study on the Density Analysis of Multi-objects Using Drone Imaging

Kajian Kelayakan Kecamatan Salahutu Sebagai Calon Ibu Kota Kabupaten Kepulauan Ambon

The issue of territorial expansion that has been discussed in Maluku is about the division of Leihitu and Salahutu sub-districts into a new regency named Ambon Islands Regency. Problems that occur such as the difficulty of administrative management such as identity cards, the lack of supporting facilities for settlement activities, the distance between the sub-district control and the Regency Capital, and various other problems that occur. The purpose of this study is to determine the feasibility of Salahutu District to become a candidate for the New Autonomous Region of the Ambon Islands Regency as well as a suitable location to become the center of its capital city. This research uses qualitative methods with data collection techniques through direct surveys. The analysis used is human development index analysis, land suitability analysis and population density analysis. The results obtained are the human development index in Salahutu District, which is 61.99, which means that the category is medium / middle to upper. Then for the cultivation area, there are 14,409 ha or 98.94% of the total area of Salahutu District, so there is still plenty of room for construction and development of infrastructure and facilities. For the center of the capital city, the results were obtained that Tulehu State became a priority or the top choice because it had the highest density level of 10.44 people / ha. The importance of the results of this research is as a basis for the expansion of new sub-districts in Central Maluku Regency based on problems that have occurred to create plans that are beneficial to the community

Si/InP direct wafer bonding: A first-principles study

The direct bonding mechanism of Si/InP is systematically investigated using first-principles calculations. Charge density analysis reveals that Si can be bonded with either In or P and is polar covalent. The single Si-P bond is stronger than the Si-In bond and has a shorter bond length, the Si-P bond length is 2.356 Å compared to 2.590 Å for the Si-In ones, as it involves the sharing of electron pairs and a large transfer and redistribution of electrons. Notably, molecular dynamics simulations show that the interfacial strength of Si bonded to In is greater at room temperature. This is because, after sufficient relaxation, although the average strength of the Si-P bonds is still greater than that of Si-In, the number of Si-In bonds is approximately four times that of the Si-P bonds. The radial distribution function of the atoms in the interfacial layer further confirms that the terminal interface is stronger than the P-terminal interface. Appropriate annealing treatment can effectively increase the number and strength of bonds at the interface. Finally, the bonding mechanism of the oxygen plasma activation is studied using reaction kinetics. These findings contribute to the precise control and optimization of bonding processes, ultimately improving the reliability of optoelectronic integration.

Chordoma cancer stem cell subpopulation characterization may guide targeted immunotherapy approaches to reduce disease recurrence.

Cancer stem cells (CSCs), a group of tumor-initiating and tumor-maintaining cells, may be major players in the treatment resistance and recurrence distinctive of chordoma. Characterizing CSCs is crucial to better targeting this subpopulation. Using flow cytometry, six chordoma cell lines were evaluated for CSC composition. In vitro, cell lines were stained for B7H6, HER2, MICA-B, ULBP1, EGFR, and PD-L1 surface markers. Eighteen resected chordomas were stained using a multispectral immunofluorescence (mIF) antibody panel to identify CSCs in vivo. HALO software was used for quantitative CSC density and spatial analysis. In vitro, chordoma CSCs express more B7H6, MICA-B, and ULBP1, assessed by percent positivity and mean fluorescence intensity (MFI), as compared to non-CSCs in all cell lines. PD- L1 percent positivity is increased by >20% in CSCs compared to non-CSCs in all cell lines except CH22. In vivo, CSCs comprise 1.39% of chordoma cells and most are PD-L1+ (75.18%). A spatial analysis suggests that chordoma CSCs cluster at an average distance of 71.51 mm (SD 73.40 mm) from stroma. To our knowledge, this study is the first to identify individual chordoma CSCs and describe their surface phenotypes using in vitro and in vivo methods. PD-L1 is overexpressed on CSCs in chordoma human cell lines and operative tumor samples. Similarly, potential immunotherapeutic targets on CSCs, including B7H6, MICA-B, ULBP1, EGFR, and HER2 are overexpressed across cell lines. Targeting these markers may have a preferential role in combating CSCs, an aggressive subpopulation likely consequential to chordoma's high recurrence rate.

Association of serum sclerostin levels with marrow adiposity in postmenopausal women with glucocorticoid-induced osteoporosis

BackgroundGlucocorticoids and sclerostin act as inhibitors of the Wnt signaling pathway, thereby hindering bone formation. Given the pathway's intricate association with mesenchymal stem cells, the hypothesis suggests that heightened sclerostin levels may be intricately linked to an augmentation in marrow adiposity induced by glucocorticoids. This study endeavored to delve into the nuanced relationship between circulating sclerostin and bone marrow adipose tissue in postmenopausal women grappling with glucocorticoid-induced osteoporosis (GIO).MethodsIn this cross-sectional study, 103 patients with autoimmune-associated diseases underwent glucocorticoid treatment, boasting an average age of 61.3 years (standard deviation 7.1 years). The investigation encompassed a thorough assessment, incorporating medical history, anthropometric data, biochemical analysis, and dual-energy X-ray absorptiometry measurements of lumbar and femoral bone mineral density (BMD). Osteoporosis criteria were established at a T-score of -2.5 or lower. Additionally, MR spectroscopy quantified the vertebral marrow fat fraction.ResultsBMD at the femoral neck, total hip, and lumbar spine showcased an inverse correlation with marrow fat fraction (r = –0.511 to – 0.647, P < 0.001). Serum sclerostin levels exhibited a positive correlation with BMD at various skeletal sites (r = 0.476 to 0.589, P < 0.001). A noteworthy correlation emerged between circulating sclerostin and marrow fat fraction at the lumbar spine (r = –0.731, 95% CI, –0.810 to –0.627, P < 0.001). Multivariate analysis brought to light that vertebral marrow fat fraction significantly contributed to sclerostin serum concentrations (standardized regression coefficient ß = 0.462, P < 0.001). Even after adjusting for age, body mass index, physical activity, renal function, BMD, and the duration and doses of glucocorticoid treatment, serum sclerostin levels maintained a significant correlation with marrow fat fraction.ConclusionsCirculating sclerostin levels exhibited a noteworthy association with marrow adiposity in postmenopausal women grappling with GIO.

Разработка и реализация протокола поведенческого эксперимента для оценки когнитивных способностей и социального поведения мышей после стресса в раннем возрасте

&lt;p style="text-align: justify;"&gt;This manuscript presents a protocol designed for the comprehensive investigation of early life stress (ELS) outcomes and a feasibility study conducted with this protocol. ELS alters normal development by interfering at various levels: hormonal changes, brain cellular architecture, epigenome, and chromosomal structural elements. The protocol combines classic behavioral tests with advanced molecular techniques to obtain comprehensive data and thus uncover the underlying mechanisms of ELS. In this protocol, the main source of stress is maternal separation. Briefly, a group of C57Bl/6 mice undergoes maternal separation; then, mice perform the radial maze test and the resident-intruder test. As a control, another group of mice stays undisturbed and performs the same behavioral tests in the same timeframe. After the behavioral tests, biosamples are collected, including urine for corticosterone measurements, peripheral blood, hippocampus, amygdala, and prefrontal cortex tissues for DNA isolation and its downstream analyses (DNA methylation profiling and telomere length measuring), and whole brains for immunohistochemistry analysis of the glucocorticoid receptor density. This protocol was successfully tested as a feasibility study for a large-scale investigation that addresses potential flaws to establish a robust methodology. This paper reports on a comprehensive approach to examining multiple aspects of development that interrogates a holistic analysis of multilayer and multidimensional data and may contribute valuable insights for both animal and human studies.&lt;/p&gt;

Spatiotemporal Evolution and Causal Analysis of Rural Tourism Popularity in Jilin Province Based on Multiple Data

The digital age provides greater possibilities for quantitative research on rural tourism. This article examines Jilin Province as a case and analyzes the interannual, monthly, and holiday characteristics of rural tourism heat using big data. Using A-level rural tourism operating units as research samples, a mathematical model is constructed to evaluate the rural tourism heat from 2016 to 2021. Through a trend surface analysis and kernel density analysis, the spatiotemporal differentiation characteristics are explored; additionally, the spatial evolution law of the rural tourism hot and cold pattern is analyzed using counties as units. The research results show the following: (1) As an important component of the Jilin tourism industry, temporally, rural tourism has an overall trend of increasing popularity, with clear seasonal and holiday distribution patterns. Simultaneously, the periodic sporadic occurrence of the COVID-19 epidemic caused an obvious vulnerability in rural tourism fever. (2) Spatially, the structure of rural tourism shows an evolutionary process of “single core → multi core” and a diffusion trend of “central → eastern” and “central → western”. (3) Regarding the influencing factors, transportation conditions and resource endowments are dominant, and the impact of the economic development level is gradually weakening, while the impact of the ecological environment and industrial foundation is gradually increasing.

The dynamics of research in customer retention: A bibliometric analysis

Customer retention is crucial for businesses because it ensures the ongoing operation of a company's activities. Hence, companies must adopt suitable and inventive tactics to maintain customer retention. This study employed bibliometric analysis spanning the past decade to identify factors associated with customer retention that can be observed through data visualization networks, overlays, and density maps. The study involved analyzing a compilation of pertinent journals and scientific publications using the software tools Publish or Perish and VOSviewer. A total of 200 research articles were acquired from Google Scholar and subjected to analysis using the Publish or Perish tool. During the period from 2013 to 2023, there was a variable pattern observed in CR, as evidenced by fluctuations in both the quantity of research articles published and the number of citations received. The network visualization results indicate a strong correlation between customer retention and factors such as customer satisfaction, customer loyalty, and customer relationships. The overlays' results for price, product, and cost exhibit the darkest colors, specifically purple. Conversely, keywords such as strategy, experience, and corporate image are represented by lighter colors, notably yellow. At that time, the colors that stood out the most were associated with density analysis, such as customer retention and customer satisfaction. In contrast, keywords such as competition, effort, price, challenge, success, and brand appeared less prominent.

Integrated anti-vascular and immune-chemotherapy for colorectal carcinoma using a pH-responsive polymeric delivery system

Colorectal carcinoma (CRC) has become one of the most prevalent malignant tumors and exploring a potential therapeutic strategy with diminished drug-associated adverse effects to combat CRC is urgent. Herein, we designed a pH-responsive polymer to efficiently encapsulate a stimulator of interferon genes (STING) agonist (5,6- dimethylxanthenone-4-acetic acid, termed ASA404) and a common clinically used chemotherapeutic agent (1-hexylcarbamoyl-5-fluorouracil, termed HCFU). Investigations in vitro demonstrated that polymer encapsulation endowed the system with a pH-dependent disassembly behavior (pHt 6.37), which preferentially selected cancerous cells with a favorable dose reduction (dose reduction index (DRI) of HCFU was 4.09). Moreover, the growth of CRC in tumor-bearing mice was effectively suppressed, with tumor suppression rates up to 94.74%, and a combination index (CI) value of less than one (CI = 0.41 for CT26 cell lines), indicating a significant synergistic therapeutic effect. Histological analysis of the tumor micro-vessel density and enzyme-linked immunosorbent assay (ELISA) tests indicated that the system increased TNF-α and IFN-β levels in serum. Therefore, this research introduces a pH-responsive polymer-based theranostic platform with great potential for immune-chemotherapeutic and anti-vascular combination therapy of CRC.

Gas-Sensitive Performance Study of Metal (Au, Pd, Pt)/ZnO Heterojunction Gas Sensors for Dissolved Gases in Transformer Oil.

An oil-immersed transformer is a critical electrical device for power delivery. Online monitoring of transformer operation is the key to ensuring the regular operation of power systems. This paper proposes Au/ZnO, Pd/ZnO, and Pt/ZnO heterojunctions as new gas-sensitive materials and investigates their gas-sensitive performance to dissolved gases (C2H4, CO, and H2) in transformer oil. Upon theoretical density functional theory (DFT) calculations, the analysis of the total density of states (TDOS), partial density of states (PDOS), molecular orbital theory, and charge deformation density reveals that Au, Pd, and Pt form heterojunctions with ZnO, which enhance the electrical conductivity of the system. Meanwhile, intrinsic ZnO is unsuitable for gas detection and adsorption, while the Au/ZnO heterojunction suits C2H4 detection. In contrast, the Pd/ZnO heterojunction is suitable for H2 detection, and the Pt/ZnO heterojunction is suitable for C2H4 and CO detection. The electrical conductivity of the adsorption models is changed to varying degrees after gas adsorption. The different change rate electrical conductivity just serves as a theoretical foundation for determining the type and concentration of dissolved gases in transformer oil. The research results act as a theoretical foundation for constructing gas sensors with a ZnO-based material.

Electrochemical versus Photoelectrochemical Water Oxidation Kinetics on Bismuth Vanadate (Photo)anodes.

This study reports a comparison of the kinetics of electrochemical (EC) versus photoelectrochemical (PEC) water oxidation on bismuth vanadate (BiVO4) photoanodes. Plots of current density versus surface hole density, determined from operando optical absorption analyses under EC and PEC conditions, are found to be indistinguishable. We thus conclude that EC water oxidation is driven by the Zener effect tunneling electrons from the valence to conduction band under strong bias, with the kinetics of both EC and PEC water oxidation being determined by the density of accumulated surface valence band holes. We further demonstrate that our combined optical absorption/current density analyses enable an operando quantification of the BiVO4 photovoltage as a function of light intensity.

Using Deep Learning Approaches to Quantify Landscape Preference of the Chinese Grand Canal: An Empirical Case Study of the Yangzhou Ancient Canal

Landscape preference emerges from the dynamic interaction between individuals and their environment and plays a pivotal role in the preservation and enhancement of the Chinese Grand Canal’s scenery. As a vast linear heritage, employing conventional methods for analyzing landscape preferences can be resource-intensive in terms of both time and labor. Amid the rapid advancement of Big Data and Artificial Intelligence (AI), a cognitive framework for understanding the Chinese Grand Canal’s landscape preferences has been developed, encompassing two primary aspects: the characteristic features of landscape preference and its spatial organization. Geotagged photographs from tourism media platforms focused on the Yangzhou Ancient Canal were utilized, and the EasyDL deep learning platform was employed to devise a model. This model assesses current landscape preferences through an analysis of photographic content, element composition patterns, and geospatial distribution, integrating social network and point density analyses. Our findings reveal that the fusion of Yangzhou Ancient Canal and classical gardens creates a sought-after ‘Canal and Watercraft Remains’ landscape. Tourists’ preferences for different landscape types are reflected in the way the elements are combined in the photographs. Overall, landscape preferences are dense in the north and sparse in the south. Differences in tourists’ perceptions of the value of and preferences for heritage sites lead to significant variations in tourist arrivals at different sites. This approach demonstrates efficiency and scalability in evaluating the Chinese Grand Canal landscape, offering valuable insights for its strategic planning and conservation efforts.