Sankey Diagram Research Articles

Consistency of P53 immunohistochemical expression between preoperative biopsy and final surgical specimens of endometrial cancer.

The aim of this study is to explore the consistency of P53 immunohistochemical expression between preoperative biopsy and final pathology in endometrial cancer (EC), and to predict the prognosis of patients based on the 4-tier P53 expression and classic clinicopathological parameters. The medical data of patients with stage I-III EC who received preoperative biopsy and initial surgical treatment in two medical centers was retrospectively collected. The consistency of P53 immunohistochemistry expression between preoperative biopsy and final pathology was compared using Cohen's kappa coefficient and Sankey diagram, then 4-tier P53 expression was defined (P53wt/P53wt, P53abn/P53wt, P53wt/P53abn, and P53abn/P53abn). Univariate and multivariate Cox regression analysis was used to determine the correlation between 4-tier P53 expression and the prognosis of patients. On this basis, the nomogram models were established to predict the prognosis of patients by combining 4-layer P53 expression and classic clinicopathological parameters, then risk stratification was performed on patients. A total of 1186 patients were ultimately included in this study through inclusion and exclusion criteria. Overall, the consistency of P53 expression between preoperative biopsy and final pathology was 83.8%, with a kappa coefficient of 0.624. ROC curve suggested that the AUC of 4-tier P53 expression to predict the prognosis of patients was better than AUC of P53 expression in preoperative biopsy or final pathology alone. Univariate and multivariate Cox regression analysis suggested that 4-tier P53 expression was an independent influencing factor for recurrence and death. On this basis, the nomogram models based on 4-tier P53 expression and classical clinicopathological factors were successfully established. ROC curve suggested that the AUC (AUC for recurrence and death was 0.856 and 0.838, respectively) of the models was superior to the single 4-tier P53 expression or the single classical clinicopathological parameters, which could provide a better risk stratification for patients. The expression of P53 immunohistochemistry had relatively good consistency between preoperative biopsy and final pathology of EC. Due to the discrepancy of P53 immunohistochemistry between preoperative biopsy and final pathology, the prognosis of patients can be better evaluated based on the 4-layer P53 expression and classic clinical pathological parameters.

Mapping the road to biologics in psoriasis and psoriatic arthritis: A nationwide drug utilization study

AbstractBackgroundLimited research has been conducted on whether advances in novel biologics and biosimilars have improved the treatment journey preceding biologics.ObjectivesTo map the overall treatment journey preceding the initiation of first biologic therapy in patients with psoriasis (PsO) and psoriatic arthritis (PsA), as well as the changes over time.MethodsUsing Danish nationwide registries, we included all patients treated with a first‐time biologic (2010–2018) for either PsO or PsA and reported the medical treatment journey. We used Sankey diagrams to illustrate the flow of treatment series.ResultsThe study included 2082 patients with PsO (62.5% male) and 1831 patients with PsA (42.3% male). Before biologics, 49.5% treated for PsO and 36.8% treated for PsA received ≥2 type therapies and 59.3% with PsO and 25.5% with PsA received ≥3 treatment series. Median time from first systemic therapy to a biologic was 3.9 years (Q1–Q3, 1.3–4.1) for PsO and 2.1 years (Q1–Q3, 0.6–5.8) for PsA. The majority of patients with PsO (1174 [56.4%]) received multiple treatment series with the same drug, while almost a third of patients with PsA (572 [31.2%]) did the same. Twelve percent of patients with PsO and 6.4% of patients with PsA repeated treatment with a drug they had already stopped for an alternative treatment.ConclusionsAlthough most patients are adequately managed, our findings suggest the possibility of a yet too long and complicated treatment journey before starting biologics.

Dynamic simulation of a triple-mode multi-generation system assisted by heat recovery and solar energy storage modules: Techno-economic optimization using machine learning approaches

Intelligent design and operation optimization allow energy systems to take advantage of the flexibility that multi-generation provides. This study proposes a basic solar-driven system integrated with thermal energy storage for round-the-clock energy harvesting. A modified configuration is then designed incorporating innovative multi-heat recovery approaches to increase the capacity and product diversity of the basic system. The modified system is able to cover vital urban utilities such as electricity, fresh water, cooling, and hydrogen throughout the day. To overcome the time-consuming procedure of dynamic techno-economic simulation as well as the limitation of commercial engineering equation solvers for tri-objective optimization, a deep learning approach is developed to reduce the computational complexity and improve the analysis accuracy. In this regard, the trained neural networks play an intermediary role in coupling the developed code with the MATLAB optimization toolbox. A comparison between the modified and conventional configurations indicates that implementing the multi-heat recovery approach results in a 29% increase in power generation while only increasing the overall system cost by 1.97%. From an economic perspective, the Sankey diagram depicts that the storage unit with a cost rate of 12.25 $/h accounts for 6.77% of the plant's cost rate, which enables the system to operate continuously. According to the sensitivity analysis and contour plots, the number of collectors significantly affects the total cost rate and fresh water production capacity while it has no tangible effect on the exergy efficiency.

Safeguarding Biodiversity and Promoting Sustainable Development: Assessing the Energy–Water Nexus of San Andrés Island, Colombia

This article provides an extensive examination of the interconnectedness between energy and water in island regions, particularly those heavily reliant on tourism, as exemplified by the present case. This study explores the present state and trends of research in this field with the objective of attaining a sustainable system in future scenarios. Specifically, this analysis delves into the water–energy–CO2 nexus of the Colombian island of San Andrés. Currently, there is no energy generation from the water sector, with 76.18% of water consumption directed towards the cooling of thermal power plants and a mere 1.54% of the energy employed for water extraction, desalination, and purification. In 2019, the island’s total energy consumption reached 138 ktoe (kilotons of oil equivalent), and renewable energies have yet to contribute to the system. These findings emphasize the necessity for the island to implement measures that will bolster its sustainability, self-sufficiency, and resilience. This entails mitigating and managing the intensity of resource consumption, particularly in areas experiencing economic growth. According to the Sankey diagram obtained, some political implications and recommendations have been listed.

The optimal design of solid oxide and molten carbonate fuel cells integration with a CO2 recycling unit: An attempt to reach a clean transition process

High-temperature Solid Oxide Fuel Cell (SOFC) technology has great potential as a clean and effective energy source. However, several issues have prevented their widespread adoption, like high operating costs, difficulty integrating with other components, and being sensitive to fuel contamination. In order to address these challenges, the main novelties of the present work are carbon capture and utilization for clean energy production, using the flue gas condensation process as a cost-effective and energy-efficient strategy, and the combination of Molten Carbonate Fuel Cells (MCFC) for increased energy efficiency and most effective component integration. The proposed novel system is also equipped with a gasifier and vanadium chloride unit for syngas and clean hydrogen production. The system's practicality is evaluated by analyzing the key performance indicators from thermodynamic, exergo-economic, exergo-environmental, and sustainability viewpoints. Also, the Sankey diagram is presented to investigate each component's effectiveness from the exergy destruction facet. According to the findings, at the most optimum design condition, the acceptable energy and exergy efficiencies of 61.06% and 50.66%, respectively, are achieved, revealing the system's effectiveness. The suggested system is also financially attractive since it achieves a reasonable levelized power cost of 17.6 $/MWh at a total cost of 44.1 $/h. The findings show that carbon dioxide recovery is crucial in reducing the pollutants due to the low emission index of 5.01 kg/GWh. Finally, the exergo-environmental index, environmental damage effectiveness, and exergy stability factor have equivalent values of 0.012, 0.59, and 0.54.

A Multi-level Resource Circularity Index based in the European Union’s Circular Economy Monitoring Framework

Purposeto propose two enhancements for the European Union’s Circular Material Use rate (CMU): inclusion of Preparation for Reuse (PfR) flows and enhanced reproducibility across lower levels of analysis.MethodsPfR flows are added to the material flow Sankey Diagram. The Local Circularity Rate (LCR) is based in the CMU and is broke down in three waste-related ratios: recovered-to-treated (RCV-to-TRT), treated-to-end-of-life and end-of-life-to-overall-material-use (EoL-to-OMU). LCR, CMU and CMU’, an alternate version of CMU, are computed and compared in the macro-level for EU27 member states and in the meso-level for Germany’s sixteen states. LCR is computed and broke down for regions in Belgium, The Netherlands and Greece. In the micro-level, LCR is computed for a network modelled around a Textile Sorting Centre (TSC) in Amsterdam.ResultsLCR showed closer average results to CMU in comparison to CMU’. Considering RCV-to-TRT and EoL-to-OMU, The Netherlands and Luxembourg are the best performing countries in the EU27. Eight countries performed worse than 0.4 in both ratios. In total, twelve German regions showed negative results, either for CMU or CMU’. Saxony-Anhalt is the most circular region in Germany, while Berlin is the less circular. The Amsterdam textiles’ network features an LCR of 12%, with the TSC contributing to 63% of all textiles recovered.ConclusionThe revised circular Sankey Diagram comprehensively illustrates the circularity gap. LCR’s three ratios enhances in-depth analysis, allowing better prioritisation of public policies. Limitations remain in data availability and harmonisation across regional and national databases.Graphic

Did the Long-Term Care Physician Workforce Change During the Pandemic? Describing MRP Trends in Ontario, Canada.

To examine the practice patterns and trends of long-term care (LTC) physicians between 2019 and 2021 in Ontario, Canada. Population-level descriptive time trend study. Most responsible physicians (MRPs) of LTC residents of publicly funded LTC homes in Ontario, Canada, from September 2019 to December2021. We examined the number of MRPs in publicly regulated Ontario LTC homes before and during the COVID-19 pandemic using population-level administrative databases. Characteristics of MRPs and practice patterns were generated at baseline and across distinct time periods of the pandemic in descriptive tables. We created a Sankey diagram to visualize MRP practice changes over time. More than one-quarter of pre-pandemic MRPs were no longer MRPs by the end of 2021, although most continued to practice in non-LTC settings. There was a decrease from 1444 to 1266 MRPs over time. Other characteristics of MRPs remained stable over the pandemic time periods. At baseline, LTC physicians were MRP for an average of 57.3 residents. By the end of 2021, this caseload decreased to 53.3 residents per MRP. MRPs increasingly billed monthly management compensation fees over the fee-for-service model across the pandemic time periods. The number of MRPs working in an LTC home shifted to fewer MRPs per home. MRP demographic characteristics did not change over the course of the pandemic. The observed shifts in practice patterns showed a reduction in the overall LTC MRP workforce, who delivered care to fewer residents on average in LTC homes with fewer colleagues to rely on. Future work can study how changes to LTC MRPs' practice patterns impact physician coverage, access and continuity of care, and health services and quality outcomes among residents.

A supply chain allocation method for environmental responsibility based on fossil energy as the anchor for carbon responsibility

Fossil fuel energy consumption is still dominant, supporting economic development and influencing environmental and climate change, both immediately and over time (e.g., carbon emissions). In this study, the concept of using fossil fuel energy (or fossil energy–based sources) as the anchor for determining carbon responsibility was proposed, which can more directly and adequately quantify and reflect the environmental responsibility of each stage of the energy economic system and further advance research on the extension of responsibility allocation to the front and back ends. Two key parameters, the primary energy consumption responsibility conversion factor and the value-added allocation factor, were introduced to couple both the energy and economic systems around carbon responsibility allocation and to complete the tracking and calculation of primary energy consumption responsibility in the entire energy supply chain. The relevant calculation data were used to map the responsibility using Sankey diagrams. Based on these parameters, we selected the Chinese energy supply system from 2002 to 2020 as a case study, calculated the allocation profile of primary energy consumption responsibility in the energy supply chain, and analyzed the evolution and allocation of primary energy consumption responsibility in the economic/residential sectors, final commodities, and final use categories. The results showed that energy-intensive industries (e.g., smelting and pressing of metals and manufacturing of chemicals) and energy-intensive products (e.g., construction commodities) are still important carrier sectors and commodities of primary energy consumption responsibility in China. Gross fixed capital formation remains the largest expenditure category of primary energy consumption responsibility. However, with the development and transformation of the national economy, the distribution of primary energy consumption responsibilities among the various stages of the energy system had subtly changed.

Humanizing Big Data and Detailing Social Determinants of Health via Information Visualizations.

The pandemic has had devastating impacts on humanity and the global healthcare sector. An analysis into the social determinants of health, in particular racial and ethnic disparities may explain why certain population groups have been disproportionately affected by COVID-19. The objective of this study is to humanize and personify numerical data. Additionally, COVID-19 population data will be stratified via three data visualization tools (i.e., a persona, a journey map, Sankey diagram) to create a Visualized Combined Experience (VCE) Diagram to illustrate the micro, and macro, perspectives of marginalized individuals across the continuum of care.

Energy, exergy and economic analysis of an integrated ground source heat pump and anaerobic digestion system for Co-generation of heating, cooling and biogas

This study designed and simulated a feasible polygeneration system, which integrated with a ground source heat pump and anaerobic digestion units to co-generate cooling, heating, and biogas for buildings as well as to utilize biomass residues in rural areas. The quantitative investigation of the energy, economics, and exergy of such a system was conducted in a village in Chongqing, China. The results indicated that by incorporating an anaerobic digestion unit, the integrated system could save 21.6% and 32.2% of primary energy, as well as 35.6% and 34.4% of annual costs, when compared to the separated and current systems, respectively. A Sankey diagram of exergy flow showed that exergy efficiency was 32.2%, and the anaerobic digester and heat pump units were the main exergy destruction components. Increasing the operating supplied temperature of the heat pump for the anaerobic digester from 45 °C to 60 °C improved exergy efficiency from 32.2% to 40.7% but decreased the overall energy efficiency ratio from 4.09 to 3.83. In addition, increasing the coefficient of performance (COP) of heat pump units was an effective way to enhance energy and exergy efficiency. The study may aid designers and decision-makers in optimizing the system and its components.

Spatiotemporal change and prediction of land use in Manasi region based on deep learning

The Manasi region is located in an arid and semi-arid region with fragile ecology and scarce resources. The land use change prediction is important for the management and optimization of land resources. We utilized Sankey diagram, dynamic degree of land use, and landscape indices to explore the temporal and spatial variation of land use and integrated the LSTM and MLP algorithms to predict land use prediction. The MLP-LSTM prediction model retains the spatiotemporal information of land use data to the greatest extent and extracts the spatiotemporal variation characteristics of each grid through a training set. Results showed that (1) from 1990 to 2020, cropland, tree cover, water bodies, and urban areas in the Manasi region increased by 855.3465 km2, 271.7136 km2, 40.0104 km2, and 109.2483 km2, respectively, whereas grassland and bare land decreased by 677.7243 km2 and 598.5945 km2, respectively; (2) Kappa coefficients reflect the accuracy of the mode’s predictions in terms of quantity. The Kappa coefficients of the land use data predicted by the MLP-LSTM, MLP-ANN, LR, and CA-Markov models were calculated to be 95.58%, 93.36%, 89.48%, and 85.35%, respectively. It can be found that the MLP-LSTM and MLP-ANN models obtain higher accuracy in most levels, while the CA–Markov model has the lowest accuracy. (3) The landscape indices can reflect the spatial configuration characteristics of landscape (land use types), and evaluating the prediction results of land use models using landscape indices can reflect the prediction accuracy of the models in terms of spatial features. The results indicate that the model predicted by MLP-LSTM model conforms to the development trend of land use from 1990 to 2020 in terms of spatial features. This gives a basis for the study of the Manasi region to formulate relevant land use development and rationally allocate land resources.

Impact of adverse drug reactions on the treatment pathways of early rheumatoid arthritis patients: a prospective observational cohort study

ABSTRACT Background Several patient characteristics may be of influence on treatment pathways of rheumatoid arthritis (RA) patients in clinical practice. The aim of this study is to analyze treatment pathways of early RA patients stratified for gender and adverse drug reaction (ADR) occurrence. Research design and methods Treatment pathways of patients included in the DREAM-RA treat-to-target cohort I between 16th of July 2006–30th of April 2020 were assessed. Treatment pathways were visualized in Sankey diagrams. Follow-up time, duration per treatment and the number of treatments received were stratified for gender and ADR occurrence and analyzed. Independent t-tests and chi-square tests were performed where applicable. Results Treatment pathways of 372 patients (follow-up: 2488.4 years, mean 6.7 ± 3.7 years) were analyzed. The Sankey diagrams visualize that treatment pathways became increasingly varied and complex over time. No significant differences were found when comparing female patients and male patients. However, the average treatment duration was shorter in patients with ADRs (1.8 vs. 2.7 years, p < 0.05), and the number of treatments higher (3.5 vs. 2.5, p < 0.05). Conclusions Treatment pathways increase in complexity over time. Differences were found between patients with and without ADRs, with patients that experience ADRs receiving more and shorter treatments.

Biophysical economic interpretation of the Great Depression: A critical period of an energy transition

AbstractThe objective of this paper is to explain the cause and proceedings of the 1930s Great Depression from a biophysical economic perspective. The Depression was a painful episode in the socio‐technological transition from a coal/railroad regime to one based on hydrocarbons, motor vehicles, and electricity. The beginning—the Great Crash of October 1929—corresponded with drastic cuts in oil prices and announcement of oil supply certainty, following discovery of huge oilfields in the US Southwest. The Depression principally centered on a change from railroads to motor‐vehicle‐based transportation, but was long and drawn‐out due to the hegemonic power that the railroads held over the US economy. The late 1920s saw increased use of hydrocarbon‐based technologies, but the emerging technologies were still reliant on the old technological system. Methods of biophysical economics, mapping energy flows to capital formation, show the critical role of railroads in the Depression. In 1929, railroads accounted for 24% of the non‐residential capital stock; they delivered between 70% and 76% of energy needs; and 69% of energy required for capital formation. Thus a hypothesis emerges that dwindling investment in the railroads was a major constraint on the economy. In biophysical terms, the US economy's main energy delivery system—coal carried by railcars—was hamstrung. Energy flow Sankey diagrams for 1929 and 1939 show the gradual change in energy systems that occurred over the Depression.

THE NATURAL COURSE OF HYPERTENSIVE PHENOTYPES OVER TIME – THE HELIUS STUDY

Objective: Hypertension can be classified into different phenotypes according to systolic and diastolic blood pressure (BP). We assessed the natural course of BP phenotypes over time in younger adults and identified risk factors predisposing to the development of sustained hypertension in a diverse population. Design and method: We used baseline and follow-up data from all participants aged below 40 years without antihypertensive medication at baseline from the ongoing multi-ethnic HEalthy LIFe in an Urban Setting (HELIUS) study. Participants were stratified according to baseline office BP: normotensive (NT; &lt; 140/&lt; 90 mmHg), isolated systolic hypertension (ISH; &gt; = 140/&lt; 90 mmHg), isolated diastolic hypertension (IDH; &lt; 140/&gt; = 90 mmHg) and combined systolic and diastolic hypertension (SDH; &gt; = 140/&gt; = 90 mmHg). Sankey diagrams were created stratified by sex to visualise change in phenotypes over time and risk of sustained hypertension (defined as BP &gt; = 140/90 mmHg or use of antihypertensive medication) was assessed using logistic regression models adjusted for age, sex, ethnicity and follow-up time. In further adjusted models we added BMI, smoking, baseline eGFR, glucose, and total cholesterol levels to assess risk factors. Results: We included 2,818 participants aged 30.1 years (SD 6.0), 44% male, who attended the follow-up visit with a median follow-up time of 6.2 years (SD 1.1). Of all participants, 91.5% was normotensive at baseline, whereas 2.8%, 2.8% and 2.9% had ISH, IDH and SDH, respectively. In males the prevalence of ISH decreased over time, while in females the prevalence increased (figure). Compared to normotensive individuals, the adjusted odds ratios for developing sustained hypertension were 4.5 (95% CI 2.5 – 7.9) for ISH, 17.4 (95% CI 10.7 - 28.4) for IDH and 33.5, (95% CI 19.7 – 58.9) for SDH. Higher BMI was the most important predictor for development of sustained hypertension. Conclusions: Participants with SDH had the highest risk for developing sustained hypertension, followed by participants with IDH. The risk for sustained hypertension in individuals with ISH was much lower and differed between males and females, suggesting differences in pathophysiology and management.

Design and evaluation of a novel plan for thermochemical cycles and PEM fuel cells to produce hydrogen and power: Application of environmental perspective

In the present article, a green and efficient multi-generation system equipped with proton exchange membrane (PEM) fuel cells as the main mover is presented and thoroughly examined. The proposed novel approach dramatically reduces the amount of carbon dioxide produced by using biomass as the primary energy source for PEM fuel cells. The waste heat recovery method is offered as a passive energy enhancement strategy for efficient and cost-effective output production. It uses the extra heat generated by the PEM fuel cells to produce cooling through the chillers. In addition, the thermochemical cycle is included to recover the waste heat from syngas exhaust gases and produce hydrogen, which will significantly help the process of going green transition. The suggested system's effectiveness, affordability, and environmental friendliness are assessed via a developed engineering equation solver program code. Additionally, the parametric analysis assesses the impact of major operational factors on the model's performance from thermodynamic, exergo-economic, and exergo-environmental indicators. According to the results, the suggested efficient integration achieves an acceptable total cost rate and environmental impact while obtaining high energy and exergy efficiencies. The results further reveal that the biomass moisture content is significant since it highly impacts the system's indicators from various aspects. From the conflictive changes between the exergy efficiency and exergo-environmental metrics, it can be concluded that choosing a proper design condition satisfying more than one aspect is highly important. According to the Sankey diagram, the worst equipment from the energy conversion quality is gasifier and fuel cells, with the highest irreversibility rate of 8 kW and 6.3 kW, respectively.

Carbon reduction of plastic’s circular strategies: tracking the effects along supply chains with waste input–output modeling

Plastic is a material associated with various Greenhouse Gas (GHG) emissions along the life cycles of different products. Many economies have adopted or planned for strategies to reduce, reuse, and recycle plastic goods and materials. The benefits of reductions in waste generation and GHG emissions need to be evaluated for setting the priority to select policy instruments for managing various plastic materials, products, and wastes. Several studies have made evaluations for the circulation of plastic using different models. However, many models for the circular economy focused on the effect on the macroeconomy rather than the detailed supply chain effects of an individual policy proposal. The reason could be the lack of an environmental assessment model with sufficient clear resolutions in the sectors, waste types, and waste treatments. In addition, the structure of the models limits many studies in modeling the scenarios diverting end-of-life products from waste treatments to recycling and reuse as secondary materials. To bridge this gap, this study adopted the waste input–output analysis methodology and compiled the models of baseline and four scenarios using the material flow and waste stream data of Taiwan with reference to a classification of four kinds of circular intervention from a review paper. We provide the details about the modeling results and settings for diverting plastic to the solid recovered fuel for power generation, closing the loops of plastic bags, extending the life of plastic cabinets and other plastic products, and improving the plastic products supply chain’s resource efficiencies. In the illustration of the results of GHG reductions in the supply chains and waste treatment activities, we present Sankey diagrams, which make the analysis of supply chains more straightforward. The developed method to render the Sankey diagram from the modeling result of an input–output-based model is presented in this article.

Thermodynamic analysis and techno-economic assessment of fluid catalytic cracking unit in the oil refining process

Fluid catalytic cracking is an important, expensive, and energy-consuming unit that produces light olefins, gases, and naphtha from heavy residues. This study aims to increase light products and reduce heavy products at the FCC unit, simulated using Aspen HYSYS software. Exergoeconomic analysis using the Sankey diagram was performed for the first time for this unit, which provides the possibility of determining the important quantities in the process from a thermodynamic and thermo-economic perspective. Based on the results, the atmospheric tower consumes the most energy (about 64%) and is the most destructive unit which is responsible for 61% of exergy destruction. In terms of energy consumption, the FCC unit is ranked second with 16%. However, the FCC unit with 11% share is the third destructive unit, but an exergy efficiency of 98% was observed in this unit. A total of 267 MW of the tower's exergy was destroyed, making it the second most destructive unit in the plant. Compared to other process units, the FCC unit accounts for 9% of the total cost, while the fractionator tower is the most expensive unit in the process at 48%. The Sankey chart shows crude oil has the highest cost stream at $744,145 per hour. The FCC unit has the highest exergoeocomic factor, while the cooler has the lowest exergoeconomic factor, with 2.4 M$/h cost of exergy destruction, as well as the lowest exergy efficiency.

NeatSankey: Sankey diagrams with improved readability based on node positioning and edge bundling

Sankey diagrams are widely used to visualize event sequence data. However, when the data volume is large, its readability is affected by dense edge crossings, excessive swing amplitude, and small crossover angles, while it is computationally intensive to obtain an optimal layout. In this paper, we propose NeatSankey, a balanced method that generates Sankey diagrams smoothly. It can be laid out quickly with good readability when Sankey diagrams are very complex. At the same time, to comprehensively evaluate the readability of Sankey diagrams, we use three evaluation metrics: crossing number, swing amplitude, and layout coverage. Firstly, we use a heuristic layout algorithm and a force-directed algorithm to adjust the node layout to minimize the edge crossings and swing amplitude with edge widths considered. Secondly, to better reduce the dense confusion caused by edge crossings, we introduce a edge bundling algorithm based on attribute similarity. We present three evaluations: a comprehensive comparison of our results with state-of-the-art techniques, user studies with thirty volunteers, and a case study of two datasets. Our evaluations demonstrate the effectiveness and practicability of the NeatSankey.

Spatial response of urban land use change and ecosystem service value in the lower reaches of the Yangtze River: A case study of Tongling, China

Exploring the impact of urban land use change (LUC) on ecosystem services is significant for ensuring urban ecological security and realizing regional economic development. This study used land use data from 1985, 2000, 2014, and 2020 of Tongling city and the CA–Markov model to predict the LUC in 2025 and 2030. The spatio-temporal distribution characteristics of LUC during 1985–2030 were analyzed using the land use dynamics model and Sankey diagram. The vegetation-corrected ecological services value (ESV) equivalent was used to quantify the impact of LUC on ESV. Estimating the profit/loss value and spatial autocorrelation revealed ESV’s spatial and temporal dynamics in Tongling city. The results show that: 1) The most obvious LUC in the study area during 1985–2030 is the conversion of cultivated land to built-up land, in which the proportion of cultivated land decreased by 9.6%, and built-up land increased by 12.2%. 2) During 1985–2030, the ESV in Tongling showed an increasing trend at the beginning and then decreased, reaching a maximum value of 274.74 billion yuan in 2000. Regarding individual ecosystem service functions, the hydrological regulation function significantly contributed to ESV changes. The area change in paddy fields and built-up land had the most significant impact on ESV. 3) The total addition of ESV in Tongling during 1985–2030 was 5.98 billion yuan; the total loss was 18.59 billion yuan, and the net loss was 12.6 billion yuan. The proportion of area with ESV gains relative to the whole city is getting smaller, and the proportion of area with ESV losses is growing. The spatial autocorrelation shows the presence of high aggregation in ESV profit and loss areas. Simulating future LUC in Tongling and exploring ESV’s response is beneficial to developing new landscape patterns and ecological protection. It also provides a scientific basis for the extensive promotion of sustainable urban development in the future.

Self-efficacy trajectories of individuals newly diagnosed with multiple sclerosis.

The first year following a new multiple sclerosis (MS) diagnosis may be a critical time for individuals as they learn to manage their disease. Effective self-management of MS likely requires healthy self-efficacy levels, yet little is known about self-efficacy in the postdiagnosis period. This study aims to improve our understanding of self-efficacy in individuals newly diagnosed with MS by examining self-efficacy trajectories and identifying patient characteristics associated with trajectories in the first postdiagnosis year. Newly diagnosed adults with MS/clinically isolated syndrome (CIS) (N = 230) completed a battery of questionnaires, including the University of Washington Self-Efficacy Scale, at 1, 2, 3, 6, 9, and 12 months, postdiagnosis. Sankey diagrams characterized self-efficacy trajectories and a multiple regression model tested patient characteristics as predictors of self-efficacy change scores. Mean self-efficacy T-scores ranged from 50.79 to 52.04 (SD = 9.40 and 10.12, respectively) across the postdiagnosis year. MS diagnosis (vs. CIS), higher disability levels, and higher MS symptom severity were associated with lower self-efficacy levels at baseline. Baseline symptom severity predicted change in self-efficacy levels from baseline to month 12 (B = -0.05, p = .030). Self-efficacy remains relatively stable in the first year following a MS diagnosis, though high symptom severity is associated with decreased self-efficacy at 12-months postdiagnosis. Clinical characteristics (e.g., MS diagnosis, disability level) also appear to play a role in setting the course of self-efficacy in this postdiagnosis year. Timely interventions that enhance self-efficacy and/or improve certain clinical characteristics may promote healthy self-management of MS that carries forward in disease course. (PsycInfo Database Record (c) 2023 APA, all rights reserved).