Types Of Plots Research Articles

Research on Crop Planting based on Linear Programming and Multiple Regression Functions

The purpose of this paper is to explore how to optimize crop planting strategies through linear programming and multiple regression functions to help rural revitalization and agricultural modernization. In the study, we consider a variety of factors such as crop planting seasons, plot types, and potential planting risks. By analyzing the crop suitability of different plots and combining constraints such as arable land area limitations and crop rotation requirements, we established a linear programming model with the objective of maximizing economic benefits. At the same time, for the two cases of stagnant and wasteful marketing and selling at a reduced price when the yield exceeds the expectation, binary decision variables are used to find the optimal solution. In addition, this paper uses multiple regression functions to predict the growth rate of sales of major crops such as corn and wheat and predicts the future price growth of edible mushrooms through a gray prediction model (GM (1,1)). In the course of the study, we also discuss the impact of extreme weather due to monsoon climate in the northern region and give the optimal planting scheme based on these perturbation factors. Through gray correlation analysis, this paper further explores the correlation coefficients between planting cost and selling price relative to expected sales volume and combines the principles of complementarity and substitutability to derive the highest yielding planting strategy. Finally, the stability of the model is verified by sensitivity analysis, and its adaptability in other agricultural scenarios is explored.

Particulate emissions from cooking: emission factors, emission dynamics, and mass spectrometric analysis for different cooking methods

Abstract. Since most people, especially in developed countries, spend most of their time indoors, they are heavily exposed to indoor aerosols, which can potentially lead to adverse health effects. A major source of indoor aerosols are cooking activities, which release large quantities of particulate emissions (in terms of both number and mass), often with complex compositions. To investigate the characteristics of cooking emissions and what influences these emissions, we conducted a comprehensive study by cooking 19 dishes with different ingredients and cooking methods. The emissions were monitored in real time with several online instruments that measured both physical and chemical particle properties as well as trace gas concentrations. The same instrumentation was used to study the influence of cooking emissions on the ambient aerosol load at two German Christmas markets. In contrast to previous studies, which often focus on individual aspects or emission variables, this broad and coherent approach allows a comparison of the influence of different parameters (e.g., ingredients, cooking method, cooking temperature, cooking activities) on the emissions. We found an influence of cooking emissions on six variables: number concentration of smaller (particle diameter dp > 5 nm) and larger (dp > 250 nm) particles, particulate matter (PM: PM1, PM2.5, PM10), black carbon (BC), PAHs (polycyclic aromatic hydrocarbons), and organic aerosol mass concentration. In general, similar emission characteristics were observed for dishes with the same cooking method, mainly due to similar cooking temperature and use of oil. The temporal dynamics in the emissions of the aforementioned variables, as well as the sizes of the emitted particles, were mainly influenced by the cooking temperature and the activities during cooking. Emissions were quantified using emission factors, with the highest values for grilled dishes, 1 to 2 orders of magnitude lower for oil-based cooking (baking, stir-frying, deep-frying), and the lowest for boiled dishes. For the identification of cooking emissions with the Aerodyne aerosol mass spectrometer (AMS), and more generally for the identification of new AMS markers for individual organic aerosol types, we propose a new plot type that takes into account the mass spectral variability for individual aerosol types. Combining our results and those of previous studies for the quantification of cooking-related organic aerosols with the AMS, we recommend the use of relative ionization efficiency values higher than the default value for organics (RIEOrg = 1.4): 2.17 ± 0.48 for rapeseed-oil-based cooking and 5.16 ± 0.77 for soybean-oil-based cooking.

Intraspecific plant chemodiversity at the individual and plot levels influences flower visitor groups with consequences for germination success

Abstract Chemodiversity, the diversity of specialised (secondary) metabolites, plays a crucial role in mediating interactions between plants and animals, including insect herbivores and mutualists. Chemodiversity can be observed at both the individual and the population level. However, the impacts of chemodiversity at these two levels on interactions between plants and floral visitors, mainly pollinators and floral herbivores (florivores), are only poorly understood. This study aimed to investigate the effects of chemodiversity at both individual (chemotype) and plot level on pollinators and florivores, examining their mutual interactions. To investigate these questions, we used individuals of the perennial Tanacetum vulgare differing in their terpenoid composition, representing different chemotypes. We planted individuals of five distinct chemotypes in a common garden design with homogeneous (five plants of the same chemotype) and heterogeneous (five different chemotypes) plots and observed flower visits in dependence of individual chemotype and plot type. Seeds were collected from a subset of plants and germination rates determined. Our findings revealed that chemodiversity at the plot level significantly influenced pollinator visitation, with more visits on plants of heterogeneous plots. We also observed marginally more pollinators on one of the chemotypes grown in homogeneous plots. In contrast, chemotype but not plot type had a significant effect on florivore visits. Pollinator and florivore species richness did not vary with plot type. Furthermore, a negative correlation was observed between pollinator and florivore visits in 1 year. Germination rates were positively correlated with pollinator visits and affected by chemotype but not by florivore visits or plot type. Synthesis. Our study emphasises the significance of the spatial level at which plant chemistry is perceived by flower visitors, potentially influencing the germination success of plants. Exploring the ecology of these visitors and the varying selection pressures they exert on floral chemistry can help to elucidate the evolutionary processes that maintain chemodiversity in natural environments. Read the free Plain Language Summary for this article on the Journal blog.

Experimenting with artificial shelters to assist habitat restoration for medium‐sized ground‐dwelling mammals

Many terrestrial vertebrates require microhabitat shelter structures for survival. Where anthropogenic or environmental disturbances have degraded or depleted shelter, artificial shelters are increasingly used to provide supplementary habitat for various taxa. However, their application to medium‐sized ground‐dwelling mammals (MGMs) remains largely unexplored. We installed rudimentary artificial shelters in a conservation reserve to emulate the vegetative cover used as refuge by three Australian MGMs: the long‐nosed (Perameles nasuta) and northern brown bandicoots (Isoodon macrourus), and the vulnerable long‐nosed potoroo (Potorous tridactylus). We used multi‐method occupancy modeling and behavioral analysis to compare the detections and behaviors of the target species with those of four non‐target species. Our study design included three plot types (treatments)—artificial shelter, baited lure, and disturbance control—enabling unambiguous evaluation of responses to the shelters. The bandicoots showed no difference in detection among treatments, whereas detection of the potoroo was highest at control plots. Detection of non‐target species was generally highest at baited plots. The target species demonstrated a much higher willingness to enter the shelters compared to the non‐target species. The use of the structures appeared to be exploratory, with no evidence that individuals remained in shelters during the day. There was limited evidence that the shelters reduced the target species' perceptions of predation risk and no evidence that predators were attracted to the shelters. The high availability of natural shelter and our small sample size likely influenced these findings. Nevertheless, they lay the foundation for research and refinement into more effective shelter designs.

Use of deep learning to improve seismic data quality analysis

Seismic data are influenced by various types of noise, which are typically categorized into two primary classes: anthropogenic and environmental. However, the detection of instrumental noise or malfunctioning stations also plays a crucial role in ensuring the data quality and the efficiency of a seismic network. The visual inspection of seismic spectral diagrams (e.g. power spectral density) enables us to identify issues that could potentially compromise data quality, thereby affecting subsequent calculations such as Magnitude or Peak Ground Acceleration (PGA). However, this process is time-consuming and demands significant human expertise due to the complexity of the diagrams, compounded by the sheer number of stations requiring examination. Therefore, in this paper, we explore the feasibility of transferring human expertise into an artificial intelligence system to create an automated system capable of rapidly performing such detection. More specifically, in the first part of this paper, we use Probability Density Function (PDF) diagrams, enabling an initial assessment of station performance via visual inspection. We describe this plot type and provide examples that reveal whether a station is functioning correctly or if technical issues exist. A table containing the main evaluation criteria is provided. In the second part of this paper, we demonstrate that these plots can serve as input for a neural network, allowing the development of the aforementioned automated system. Through extensive testing under various conditions, we have observed that the trained network consistently achieves an accuracy rate exceeding 85% across all four conductedtests. In the latest and most significant test, the achieved accuracy is approximately 87%.

Soil pH enhancement and alterations in nutrient and Bacterial Community profiles following Pleioblastus amarus expansion in tea plantations

BackgroundThe expansion of bamboo forests increases environmental heterogeneity in tea plantation ecosystems, affecting soil properties and microbial communities. Understanding these impacts is essential for developing sustainable bamboo management and maintaining ecological balance in tea plantations.MethodsWe studied the effect of the continuous expansion of Pleioblastus amarus into tea plantations, by establishing five plot types: pure P. amarus forest area (BF), P. amarus forest interface area (BA), mixed forest interface area (MA), mixed forest center area (TB), and pure tea plantation area (TF). We conducted a comprehensive analysis of soil chemical properties and utilized Illumina sequencing to profile microbial community composition and diversity, emphasizing their responses to bamboo expansion.Results(1) Bamboo expansion significantly raised soil pH and enhanced levels of organic matter, nitrogen, and phosphorus, particularly noticeable in BA and MA sites. In the TB sites, improvements in soil nutrients were statistically indistinguishable from those in pure tea plantation areas. (2) Continuous bamboo expansion led to significant changes in soil bacterial diversity, especially noticeable between BA and TF sites, while fungal diversity was unaffected. (3) Bamboo expansion substantially altered the composition of less abundant bacterial and fungal communities, which proved more sensitive to changes in soil chemical properties.ConclusionThe expansion of bamboo forests causes significant alterations in soil pH and nutrient characteristics, impacting the diversity and composition of soil bacteria in tea plantations. However, as expansion progresses, its long-term beneficial impact on soil quality in tea plantations appears limited.

Measuring the impact of plot types on physical change: A diachronic analysis of urban form evolution in New York, Melbourne and Barcelona

Plots are hypothesised as the most influential determinant of urban form evolution yet remain understudied. Existing morphological studies exploring plots' influential role lack quantitative methods, while more recent quantitative urban form studies remain largely synchronic, analysing urban form at a single timeframe without offering diachronic frameworks. Addressing this gap, we investigate the relationship between plot types and physical change in three international case studies (New York, Melbourne and Barcelona) over two centuries. Employing a novel longitudinal spatial database generated from historical maps, we present a methodology to measure the configurational character of plot structures and identify multi-variable plot typologies using k-means clustering. Statistical analysis of the relation between plot types and physical change reveals that finer-grained, narrower, and more compact plot types exhibit significantly greater resistance to building replacement compared to coarser-grained, broader, and less compact plot types. Our findings demonstrate the robustness of plot structures' configurational character in explaining physical change dynamics in cities. These data-driven findings can guide policymakers in strategic land subdivision decisions to guide future preservation and development needs and patterns, ultimately promoting more resilient and adaptive urban environments.

Structural assessment and petrophysical evaluation of the pre-Cenomanian Nubian sandstone in the October Oil Field, central Gulf of Suez, Egypt

The low quality of the seismic resolution of the studied Cambrian Pre-Cenomanian formations, which rest directly on the basement in the October Field in the Gulf of Suez, requires study, and the structure pattern controlling these formations is uncertain. The poor quality of the seismic data resolution in the Gulf of Suez is due to the presence of thick sequences of evaporites represented by the South Gharib and Zeit formations. Therefore, the current study used seismic reflection data integrated with well-log data to define the structural-stratigraphic setting of the pre-Cretaceous Nubian reservoir sequence. The study aims at locating and delineating zones having excellent reservoir potential within the Nubian sequence horizons (Nubian Transition, main Nubian, Nubian marker-1, and Nubia marker-2, referred to as NT, MN, M1 and M2, respectively) through the integration of the 3D static modelling and the petrophysical parameters deduced from the well-log data processing. A detailed petrophysical analysis, based on the wireline logs of some wells, was performed to determine the lithological units using two types of cross plots (Neutron-Density and M-N plots), and the different petrophysical parameters that characterize the various Nubian horizons were also computed. 3D modelling was used to visualise the lateral and vertical changes of the reservoir characteristics. The seismic mapping reveals that the Nubian structure is controlled by an NW-SE trending (Clysmic trend) of an NE-plunging asymmetrical anticlinal feature unconformably resting on a basement horst. The main structure is affected by two major normal faults, which trend NW, andis cut by two smaller sub-parallel faults that disturb the core of the structure, which is unaffected by the easterly oriented faults of the Aqaba trend. The petrophysical analyses indicate that the Nubian sandstones have intervals of good reservoir quality, with a total net-pay thickness of about 500 m, net sand ratios (60–90 %), effective porosity (10–25 %), and hydrocarbon saturation (85%), which may encourage further drilling, especially in the southeast portion. The result of this study can be extended to the other Nubia sandstones resting on the basement complex in the Gulf of Suez.

Exploring rational vegetation configuration to relative increase runoff, reduce erosion and soil organic carbon loss in gully-slopes on the Chinese Loess Plateau

In order to solve the water shortage, uncoordinated runoff-sediment relationship, and prevent carbon loss in the Yellow River Basin, there is an urgent need to explore the rational vegetation configuration in order to relative increase runoff, reduce sediment and prevent soil organic carbon loss in the gully-slopes on the Loess Plateau. To solve these problems, the simulated rainfall experiments with an intensity of 60 mm·h−1 were conducted in four types of plots: shrub-grass (SG), tap root grasses (GT), fibrous root grasses (GF) and bare land (CK). Four types of plots were built on one gully-slope with a slope of 35°–40° in situ. Compared with CK (mean runoff rate: 0.61 mm·min−1), the runoff reduction benefits of SG (0.27 mm·min−1), GT (0.04 mm·min−1) and GF (0.17 mm·min−1) plots were 54.9 %, 71.7 %, 92.2 %. Compared with GT and GF plots, the total runoff of SG plots was 1.6–5.8 times. Compared with CK, the sediment reduction benefits of three vegetation plots were more than 98 %. Shrub-grass is a more suitable vegetation combination for soil and water conservation: reducing sediment and relative increasing runoff. The soil organic carbon loss has been well alleviated through vegetation restoration, and vegetation plots all prevented over 98 % of soil organic carbon loss compared with the bare plot. Soil organic carbon loss equation based on runoff and sediment was established and validated. The R2, P and NSE results of the equations were 0.92–0.95, <0.001, 0.85–0.86, respectively, indicating that the fitted equations can be considered acceptable. The soil organic carbon loss in the gully-slopes was mainly from sediment (more than 85 %) compared with runoff. Therefore, controlling sediment is more effective than controlling runoff in preventing soil organic carbon loss in the gully-slopes on the Loess Plateau. These results can provide a basis for decision-making of high-quality development of contemporary soil and water conservation on the Loess Plateau.

Spatiotemporal dynamics and similarity in soil moisture in shallow soils on karst slopes

Understanding the spatiotemporal dynamics and similarity of soil moisture on shallow slopes is important for inferring soil hydrological processes and for vegetation restoration. In karst areas, the spatial distribution patterns and dynamic changes in shallow soil moisture are particularly complex; however, whether there is spatiotemporal similarity in shallow soil moisture on karst slopes has not been fully determined. This work investigated the spatiotemporal dynamic variations in shallow soil moisture in three types of karst slope plots (abandoned land, peanut and Zanthoxylum bungeanum). Wavelet coherence analysis was used to evaluate the spatiotemporal similarity and factors influencing shallow soil moisture under different vegetation types and slope positions. The results indicate that the alternation between dry and wet conditions and spatiotemporal heterogeneity were significant in the shallow soils of slopes. Comparatively, the dry-wet cycle in the shallow soil of abandoned land occurred faster than that in the shallow soil, and the shallow soil for planting vegetation had a better water holding capacity. The terrain and slope position controlled the distribution and dynamic variations in soil moisture on shallow slopes. Compared with those in the middle and upper slopes, the soil moisture in the bottom slopes was greater, and the coefficient of variation was lower. The average coherence between the soil moisture in the different plots was greater than 0.90, and the significant area was greater than 93.0%. The coherence and significant area in the rainy season were significantly greater than those in the dry season. Due to the influence of vegetation types and meteorological conditions, the drought interval after rainfall events led to a decrease in the spatiotemporal similarity of soil moisture. This study indicates that shallow soil moisture in karst slopes exhibits temporal stability and dynamic similarity. The alternation of dry-wet conditions controls the similarity of shallow soil moisture on the slope.

Start-Ups and Entrepreneurship in Renewable Energy: Investments and Risks

Advances in renewable energy technologies, particularly in solar, wind, energy storage, and grid integration solutions, are accelerating the growth of in startups in this sector. Despite the promising outlook, renewable energy startups face several risks, including technological, regulatory, financial and market risks. The article carries out a bibliometric analysis of scientific publications related to the problem of investment and risks associated with the development of entrepreneurship and start-ups in the field of renewable energy. After multi-level filtering of the dataset, the research base consists of 82 publications by 232 scientists for 2005-2023, indexed by Scopus, and the analysis tools used are Biblioshiny and Excel. In 2005-2016, the number of publications grew annually at a rate of 10.47%, with peaks in 2006, 2007, and 2016; in 2017-2023, the number of papers increased (the dependence is described by a third-degree polynomial trend). The article examines 3 different types of Three-field plots in the topic of the investments and risks of the startups and entrepreneurship in renewable energy: 1) “References – Authors – Keywords”, 2) “Countries – Institutions – Authors”, 3) “Authors – Sources – Keywords”. A quantitative and qualitative analysis of the scientific journals that make the largest / periodic but noteworthy / minimal contribution to the dissemination of knowledge in this area was carried out, the top 10 authors and papers were analysed by the levels of local and global influence, the most powerful research networks (based on the results of the analysis of joint citations) were identified both in terms of authors and countries, and the leading countries were identified in terms of the volume of research output of their scientists and the intensity of citation of these works. Building clouds of the most used keywords allowed us to identify priority thematic areas of research, as well as to analyse the structural and logical relationships between different thematic blocks in the research landscape. With the help of multiple correspondence analysis (factorial analysis) and longitudinal thematic map analysis, the scientific landscape in this area is clustered and evolutionary changes and interdependence of individual topics are identified.

Soil fungal and bacterial communities reflect differently tundra vegetation state transitions and soil physico-chemical properties.

Strong disturbances may induce ecosystem transitions into new alternative states that sustain through plant-soil interactions, such as the transition of dwarf shrub-dominated into graminoid-dominated vegetation by herbivory in tundra. Little evidence exists on soil microbial communities in alternative states, and along the slow process of ecosystem return into the predisturbance state. We analysed vegetation, soil microbial communities and activities as well as soil physico-chemical properties in historical reindeer enclosures in northernmost Finland in the following plot types: control heaths in the surrounding tundra; graminoid-dominated; 'shifting'; and recovered dwarf shrub-dominated vegetation inside enclosures. Soil fungal communities followed changes in vegetation, whereas bacterial communities were more affected by soil physico-chemical properties. Graminoid plots were characterized by moulds, pathotrophs and dark septate endophytes. Ericoid mycorrhizal and saprotrophic fungi were typical for control and recovered plots. Soil microbial communities inside the enclosures showed historical contingency, as their spatial variation was high in recovered plots despite the vegetation being more homogeneous. Self-maintaining feedback loops between plant functional types, soil microbial communities, and carbon and nutrient mineralization act effectively to stabilize alternative vegetation states, but once predisturbance vegetation reestablishes itself, soil microbial communities and physico-chemical properties return back towards their predisturbance state.

Seasonal variability of scavenger visitations is independent of carrion predictability

In temperate regions, larger mammalian carrion naturally occurs in terrestrial landscapes as a pulsed resource towards the end of the winter through enhanced ungulate mortality due to starvation or exhaustion. The return of large carnivores in Central Europe provides carrion more equally throughout the year and the active enhancement of carrion for biodiversity by game managers has increased, raising the question of how different scavengers respond to the temporal variation in carrion supply. To address this question, we experimentally deployed 106 cervid carcasses throughout the year in a temperate forest of south-eastern Germany on two types of plots: permanent (i.e., site with multiple subsequent deployments) or random (i.e., site with unique deployment), and reported vertebrate scavenger visitations by camera trapping. Deployment on random or permanent sites did not affect carrion use by any single species. Generalized additive modelling revealed that vertebrate scavenging peaked in the winter season and summer independent of carrion supply. Still, different scavenger species showed different temporal patterns. While wild boar as ungulate omnivores did not display any seasonal patterns, avian scavengers showed significant variation in visitation rates. The mesopredator red fox consumed carrion significantly more often from late winter to summer, while pine marten was present at carrion only during winter. Finally, the specialist large carnivore Eurasian lynx, visited carrion sites most frequently in late winter and early spring. Our results suggest that global warming might impact some groups of vertebrate scavengers more strongly than others by reducing carrion availability in late winter, while returning carnivores could mitigate these impacts.

The Art of Brainwaves: A Survey on Event-Related Potential Visualization Practices

Electroencephalography (EEG) and event-related potentials (ERPs) have been analyzed for more than 70 years. Yet, we know little about how practitioners visualize the results of their analyses. Here, we designed an online survey (n=213) targeting M/EEG practitioners from novice to expert level. Our primary goal is to better understand the visualization tools currently in use, the challenges researchers face, and their experiences and opinions on how best to display their brain data. Finally, we explored whether researchers are aware of more general visualization issues related to visualization of uncertainty and color maps. In this paper, we provide an overview of the most popular ERP visualization tools. Additionally, we found that the community does not have a unique nomenclature to refer to some plot types, and we propose a set of recommendations to name the most popular ERP plot types. Finally, we provide an analysis of practitioner feature preferences for software developers and conclude with further recommendations for ERP practitioners.

Scientific figures interpreted by ChatGPT: strengths in plot recognition and limits in color perception

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting basic bioinformatics data analyses. The recent feature of accepting image inputs by ChatGPT, also known as GPT-4V(ision), motivated us to explore its efficacy in deciphering bioinformatics scientific figures. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when color perception and quantitative analysis of visual elements were involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

Sea stack plots: Replacing bar charts with histograms.

Graphs in research articles can increase the comprehension of statistical data but may mislead readers if poorly designed. We propose a new plot type, the sea stack plot, which combines vertical histograms and summary statistics to represent large univariate datasets accurately, usefully, and efficiently. We compare five commonly used plot types (dot and whisker plots, boxplots, density plots, univariate scatter plots, and dot plots) to assess their relative strengths and weaknesses when representing distributions of data commonly observed in biological studies. We find the assessed plot types are either difficult to read at large sample sizes or have the potential to misrepresent certain distributions of data, showing the need for an improved method of data visualisation. We present an analysis of the plot types used in four ecology and conservation journals covering multiple areas of these research fields, finding widespread use of uninformative bar charts and dot and whisker plots (60% of all panels showing univariate data from multiple groups for the purpose of comparison). Some articles presented more informative figures by combining plot types (16% of panels), generally boxplots and a second layer such as a flat density plot, to better display the data. This shows an appetite for more effective plot types within conservation and ecology, which may further increase if accurate and user-friendly plot types were made available. Finally, we describe sea stack plots and explain how they overcome the weaknesses associated with other alternatives to uninformative plots when used for large and/or unevenly distributed data. We provide a tool to create sea stack plots with our R package 'seastackplot', available through GitHub.

CERN生物长期样地背景和植被分类特征本底数据集

This dataset is a comprehensive integration of 95 long-term plots from 22 natural ecosystem stations. We first sorted out the background information such as the geographical location, establishment time, area and representativeness of the long-term plot of ecological station. Drawing from the survey data of plant communities at the beginning of the plot establishment and adhering to the latest Chinese vegetation classification system, we then meticulously delineated the vegetation formation group, vegetation formation and vegetation subformation of each sample plot’s plant community. Based on the list of dominant species found in each sample plot, we identified and named the alliance and association of the vegetation in the plot. The construction of this dataset went through multiple rounds of expert review-station verification-expert review-station acceptance, etc. The dataset comprises station code, station name, plot code, plot name, plot type, plot representativeness, geographical location, altitude, plot area and shape, plot establishment time and design service life, vegetation formation group, vegetation formation, vegetation subformation, alliance, association, dominant species and remarks. It is expected to provide data support for the studies on flora, vegetation resource distribution, and biodiversity conservation.

Color Quest: An interactive tool for exploring color palettes and enhancing accessibility in data visualization.

Data visualization plays a vital role in modern scientific communication across diverse domains, shaping the understanding of complex information through color choices. However, the significance of color palette selection goes beyond aesthetics and scientific communication, encompassing accessibility for all, especially individuals with color vision deficiencies. To address this challenge, we introduce "Color Quest," an intuitive Shiny app that empowers users to explore color palettes for data visualization while considering inclusivity. The app allows users to visualize palettes across various types of plots and maps envisioning how they appear to individuals with color blindness. In addition, it enables users to visualize palettes on their own custom-uploaded images. This short communication presents the app's design, interactive interface, and transformative potential in enhancing data visualization practices. Developed using open-source standards, Color Quest aligns with accessibility discussions, offering a practical tool and platform for raising awareness about inclusive design. Its open-source nature fosters transparency, community collaboration, and long-term sustainability. Color Quest's practicality renders it indispensable for scientific domains, simplifying palette selection and promoting accessibility. Its impact extends beyond academia to diverse communication settings, harmonizing information dissemination, aesthetics and accessibility for more impactful scientific communication.

Dynamical stricture of optical soliton solutions and variational principle of nonlinear Schrödinger equation with Kerr law nonlinearity

The aim of this paper is to discover some new exact solutions for two kinds of nonlinear Schrödinger equation (NLSE), including the (2+1)-dimensional NLSE and the derivative NLSE, through the use of the variational principle method and amplitude ansatz method. We will find the solutions to these equations by selecting a trial function with a single nontrivial variational parameter, and it is continuous at all intervals in three cases from a region of a rectangular box, then using this trial function to obtain the functional integral and the Lagrangian of the system without any loss. After that, we approximate this trial function by quadratic polynomials with two free parameters rather than a piecewise linear ansatz function. Similarly, this trial function will be approximated by the tanh function. Additionally, we accept several new types of soliton solutions, including bright solitons, dark solitons, bright–dark solitary wave solutions, rational dark–bright solutions, and periodic solitary wave solutions. Also, conditions for the stability of the solutions will be proposed. These explanations are of great importance in the fields of applied science and engineering. The results will be shown through different types of graphs, including 2D, 3D, and contour plots.

Traceability Analysis and Environmental Quality Assessment of Soil Heavy Metal Pollution in West Hunan Province

In order to explore the status of soil heavy metal pollution and environmental quality in west Hunan, relevant areas of Phoenix County were selected as the study area. Using data from 440 soil samples collected in the study area from June to August 2022, the pH value of the soil and contents of eight heavy metal elements, namely, As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were analyzed. The PMF model was used for traceability analysis and geochemical evaluation of soil environmental quality. The results showed that the average values of soil heavy metals ω(Zn), ω(Cr), ω(Pb), ω(Ni), ω(Cu), ω(As), ω(Cd), and ω(Hg) were 81.02, 64.67, 31.63, 29.27, 25.52, 9.93, 0.28, and 0.13 mg·kg-1, respectively. The soil in the study area was mainly weakly acidic, and the contents of the Cd and Hg elements were relatively high compared to the national soil background values and were highly variable. The contents of the Hg and Cd elements in forest land were higher than that in other land uses. The PMF model results showed that the contribution rates of heavy metal pollution sources in the study area were mining sources (37.4%), atmospheric sedimentation sources (7.7%), natural sources (41.1%), and agricultural activity sources (13.8%) and provided suggestions on pollution control measures according to the spatial distribution of the four types of pollution sources. Through the comprehensive assessment of soil environmental geochemistry, the study area was divided into three types of plots, namely, non-risk areas (94.27 km2), accounting for 76.38%; risk-controllable areas (27.45 km2), accounting for 22.24%; and high-risk areas (1.7 km2), accounting for 1.38%. This study provided data support for the prevention and control measures of land pollution in the research area, as well as the delineation of the prevention and control scope.