Natural Scenarios Research Articles

Scenario Simulation of the Relationship between Land-Use Changes and Ecosystem Carbon Storage: A Case Study in Dongting Lake Basin, China.

High-frequency land-use changes caused by rapid economic development have become a key factor in the imbalance of carbon sequestration within regions. How to balance economic development and ecological protection is a difficult issue for regional planning. Studying the relationship between future land-use changes and ecosystem carbon storage (CS) is of important significance for the optimization of regional land-use patterns. The research used the gray prediction model and coupled the patch-generating land-use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model. On this basis, the evolution characteristics and spatial coordination between land-use changes and CS in the Dongting Lake Basin (DLB) in different scenarios in 2030 were simulated. The results show that: (1) The spatial distribution of CS remains stable in different scenarios, while land-use types with high carbon density in the periphery of cities are constantly invaded by construction land, which results in the greatest carbon loss in the urban areas. (2) Compared with the natural evolution scenario (NES), only 195.19 km2 of land-use types with high carbon density are transformed into construction land in the ecological protection scenario (EPS), generating a carbon sink gain of 182.47 × 104 Mg. Conversely, in the economic development scenario (EDS), a total of over 1400 km2 of farmland and ecological land are transformed into construction land, which weakens the carbon sequestration capacity of ecosystems, and more than 147 × 104 Mg of carbon loss occurs in the urban areas. (3) The planned development scenario (PDS) takes ecological protection and economic development both into consideration, which not only generates a carbon sink gain of 121.33 × 104 Mg but also reduces the carbon loss in urban areas by more than 50%. The PDS performs well in both land use and CS growth and can better motivate the effect of land-use changes in increasing the carbon sink, which is also proved by analysis of the coordination between land-use intensity (LUI) and CS. Therefore, the PDS better satisfies the future development demand of DLB and can provide a reference for sustainable land use in the basin.

Effect of wetland hydrological connectivity on runoff based on a basin comparison

Hydrological connectivity is of great significance to the protection of wetlands and the rational development of water resources. Climate change and overdevelopment have led to the reduction of the Zoige wetland area, the destruction of its ecosystem structure, and the severe degradation of wetland hydrological connectivity. This study proposes an analysis framework to explore the impact of hydrological connectivity on runoff based on the dynamic prediction of wetland spatial patterns and the quantification of wetland hydrological connectivity and nonlinear fitting; the Zoige wetland was selected for application and verification. Under the ecological protection scenario (Plan1), the wetland experienced an expansion of meadow wetland (MW); under the natural development scenario (Plan2), the degradation of shallow wetland (SW) is the most significant. The optimal threshold distances (TDs) for studying the hydrological connectivity in the Hei River basin (HRB) and Bai River basin (BRB) were 1200 m and 1800 m, respectively. The hydrological connectivity of the HRB was significantly greater, with a value that was approximately 30–50 times that of the BRB in the same year. The IIC and PC of the two basins gradually decreased during the historical period and showed increasing and decreasing trends under the Plan1 and Plan2 scenarios, respectively. The effect of wetland hydrological connectivity on runoff was significantly different in the two basins; wetlands developed extensively in the HRB, and connectivity had an inhibitory effect on the runoff and the runoff-generating efficiency of precipitation, while the wetland was even more fragmented in the BRB, and the increase in connectivity promoted the generation of runoff. Because biodiversity is sensitive to change, the patches in the middle reaches of the HRB and the lower reaches of the BRB are the areas that should receive the highest wetland protection priority in the future.

Forecast of the Evolution Trend of Total Vehicle Sales and Power Structure of China under Different Scenarios

Accurate forecasting of the power structure and sales volume of the automobile industry is crucial for corporate decision making and national planning. Based on the auto sales data from 2011 to 2022 compiled from the official website of the China Association of Automobile Manufacturers (CAAM), the total auto sales in China from 2023 to 2030 were firstly predicted using a combined GM (1,1), and quadratic exponential smoothing forecast model optimized by particle swarm algorithm. Subsequently, the vehicles were classified into the following four categories by power: traditional fuel vehicles, pure electric vehicles, plug-in hybrid vehicles, and hydrogen fuel cell vehicles. Then, based on vehicle sales data from 2015 to 2022, The Markovian model and the component data model based on hyperspherical transformation are used to predict the vehicle power structure from 2023 to 2030 under the natural evolution scenario and the consumer purchase intention dominant scenario, respectively. The results show that total vehicle sales in China are expected to reach 32.529 million units by 2030. Under the natural evolution scenario and the consumer purchase intention dominant scenario, China will achieve the planned target of 40% of the new car market in the sales of new energy vehicles in 2028 and 2026, respectively. By 2030, under the natural evolution scenario, the sales volume of traditional fuel vehicles in the new car market will be 54.83%, the proportion of pure electric vehicles will be 35.92%, the proportion of plug-in hybrid vehicles will be 9.23%, and the proportion of hydrogen fuel cell vehicles will be 0.02%. Under the consumer purchase intention dominant scenario, the proportions of the four power types are 36.51%, 48.11%, 15.28%, and 0.10%, respectively.

Simulating the impact of land use change on ecosystem services in agricultural production areas with multiple scenarios considering ecosystem service richness

Agricultural land is a complex seminatural and semiartificial ecosystem that is affected by both human activities and natural factors. Clarifying land use and ecological health conflicts in agricultural areas is important for maintaining ecosystem services. Thus, taking the Henan section of the Yellow River (HSYR) as the study area, this study constructed an ecosystem service index (ESI) assessment model to explore the impact of land use change on ecosystem services from 1980 to 2020. Then, the future land use simulation (FLUS) model was used to simulate the effects of different development patterns on ecosystem services heterogeneity in 2035. The results showed that, from 1980 to 2000, the ESI increased from 0.520 to 0.649, but then decreased to 0.509 by the end of 2020 in the HSYR. In any simulation scenarios, urban land expansion continued to encroach on cropland, resulting in the loss of ecosystem services. Especially in the natural development scenario (ND), the ESI may be reduced by up to 2.55%. The results also emphasized that ecosystem services can be protected in the cropland protection scenario (EC). The results of this study enrich the understanding of the impact of human activities on ecological services in agricultural areas and provide new insights into grasping regional food security and ecological stability.

Current and future characteristics of land use based on intensity analysis and PLUS model : a case study of Foshan city, China

Land use change drives urban pattern change. The development of urbanization will result in the diminution of ecological land and the extinction of ecological defense. Foshan is a highly typical city. Identifying the characteristics of dynamic land use changes and predicting the future land use pattern are crucial components of land use planning. Land use transfer matrix and intensity analysis model were utilized in this study. Three representative years, 2010, 2015, and 2020, were used to analyze the interval, category, and transition level characteristics for Foshan City. Then, based on the PLUS model and the Markov model, multiple scenarios for the land use of Foshan City in 2030 were developed. The results indicate the following: (i) According to the interval level intensity analysis, the general trend of land use intensity between 2010 and 2020 is first rapid and then gradual. At the category level, construction land demonstrates stable activity with increasing intensity, whereas dike-ponds demonstrate continuous activity with decreasing intensity. (ii) From 2020 to 2030, there is a slowing in the intensity of site conversion. The natural development scenario is more in line with the city's development. (iii) In simulations of future urban scenarios, the dike-pond has a decreasing trend over the scenario. At the future transition level, three possible land use conversion systems exist: "forestland—dike-pond," "water—dike-pond," and "dike-pond—construction land." With this study, Foshan City can serve as a case study for sustainable development and rational planning.Article HighlightsLand use change components, quantity, exchange and shift were estimated.The largest net change occurred in 2010–2015 due to human activities.Spatial reallocation were characterized by exchange and shift.The largest exchange occurred in 2010–2020 due to the dike-pond eroded.The dike-pond has a decreasing trend over the simulated scenario.

Habitat quality evolution characteristics and multi-scenario prediction in Shenzhen based on PLUS and InVEST models

Based on the PLUS model, research proposed a method to adjust the probability of land use transition to reduce the calculation error of the number of pixels. The refined algorithm is applied to simulate Shenzhen land use situation in 2030 under a progressive scenario using three periods of Shenzhen land use data in 2000, 2010 and 2020. Then, InVEST model was employed to evaluate the distribution situation and future trends of habitat quality in Shenzhen during the study period. Following are the conclusions: 1) The construction land in Shenzhen expanded rapidly and the ecological land gradually shrank during the research period. The proportion of artificial surface area increased by about 45.4% (304.98 km2) within 20 years. 2) By simulating the land use situation of Shenzhen in 2030, the results revealed that the land use change of Shenzhen in the future is mainly concentrated in the central and western regions. 3) The overall average habitat quality of Shenzhen was at a medium level, but the habitat quality showed a continuous degradation trend in each year throughout the study period. Spatially, the habitat quality degradation are mainly concentrated in Shenzhen’s central and western region. 4) Under the natural development scenario, Shenzhen’s habitat quality would experience a sharp decline by 2030. The habitat quality of the conservation area is guaranteed to a certain degree, but the artificial surface expansion outside the area will still affect the habitat quality in the boundary constraint scenario; Only in scenario of ecological priority, the habitat quality of Shenzhen has been restored and improved to a large extent. 5) In order to slow down the degradation trend and improve the regional ecological environment. It is necessary not only to strictly implement various protection boundaries delineated in the context of Territorial Spatial Planning, but also to implement the policy of “Clear waters and green mountains are as good as mountains of gold and silver” in the process of urban development. Government should reasonably control the scale of cities, optimize the ecological compensation mechanism, and implement ecological restoration policies such as returning farmland to forests and returning farmland to grassland.

Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China

Land use is a crucial factor affecting ecosystem service value (ESV), and forecasting future land use changes and ESV response can guide urban planning and sustainable development decisions. However, the traditional Cellular Automata (CA) model supposes that each cell has only one land use type at each time step, neglects the mixed structure and proportional distribution of land use units, does not take into account its quantitative continuous dynamic change, and lacks the exploration of land use quantity structure and spatial pattern optimization. This study employed a novel mixed-cell cellular automata (MCCA) approach, coupled with the system dynamics (SD) model to predict the spatiotemporal pattern of land use under the natural increase scenario (NIS), economic development scenario (EDS) and ecological protection scenario (EPS) in Xi’an, China, in 2030. The equivalent coefficient method was utilized to investigate the heterogeneity distribution and sensitivity of ESV. The results demonstrated that SD-MCCA exhibited remarkable prediction accuracy and robustness. The main changes in land use in 2000–2015 were due to urban expansion, the conversion of arable land into construction land, and the conversion between grassland and arable land. The total ESV increased from 19554.36×106 CNY in 2000 to 19618.39×106 CNY under the EPS in 2030, and the contribution of climate regulation and hydrological regulation to ESV was the highest. Spatial heterogeneity of ESV revealed a certain regularity, and the high value region was chiefly concentrated in woodland and grassland with favorable ecological conditions. Land use variations under NIS and EPS improved ESV, while the ESV had a negative response to land use transformations under the EDS. This research provides a new way to identify the relationship between future land utilization scenarios and ESV, which is of great significance for the management of land resources and formulation of ecological compensation standards.

Smart Sensors System Based on Smartphones and Methodology for 3D Modelling in Shallow Water Scenarios

The aim of the paper was the implementation of low-cost smart sensors for the collection of bathymetric data in shallow water and the development of a 3D modelling methodology for the reconstruction of natural and artificial aquatic scenarios. To achieve the aim, a system called GNSS > Sonar > Phone System (G > S > P Sys) was implemented to synchronise sonar sensors (Deeper Smart Sonars CHIRP+ and Pro+ 2) with an external GNSS receiver (SimpleRTK2B) via smartphone. The bathymetric data collection performances of the G > S > P Sys and the Deeper Smart Sonars were studied through specific tests. Finally, a data-driven method based on a machine learning approach to mapping was developed for the 3D modelling of the bathymetric data produced by the G > S > P Sys. The developed 3D modelling method proved to be flexible, easily implementable and capable of producing models of natural surfaces and submerged artificial structures with centimetre accuracy and precision.

Land Use Conflicts Assessment in Xiamen, China under Multiple Scenarios

The accelerated urbanization process has resulted in increasingly prominent conflicts in land resource utilization and caused numerous ecological and environmental issues. Simulating the evolutionary patterns of land use conflicts (LUCs) is the foundation for promoting sustainable land use. The Markov and GeoSOS-FLUS models were used to predict the land use patterns under three different development scenarios, and to analyze the spatio-temporal characteristics of LUCs in Xiamen, China in 2030. Results showed the following: (1) From 2010 to 2020, land use/cover in Xiamen has changed substantially, with an increase of 6.93% in area of construction land and a decrease of 5.40% in area of cropland. (2) In the natural development scenario, the area of construction land in Xiamen is projected to increase, while the areas of cropland and other land types reduce. In the policy intervention scenario, the area of cropland continues increasing and the growth of construction land is effectively controlled. Under the sustainable development scenario, cropland, grassland, and wetlands of high quality that serve important ecological functions have been effectively protected. (3) LUCs in Xiamen differ greatly under the three scenarios in 2030. The sustainable development scenario (SDS) balances the land use needs of both socio-economic development and regional ecological security with the least LUCs, which could be an optimum solution for the long-term sustainable development in Xiamen. The results of this study provide support for decisions about eco-city construction and geospatial planning.

Electronic–Vibrational Resonance Does Not Significantly Alter Steady-State Transport in Natural Light-Harvesting Systems

Oscillations in time-dependent two-dimensional electronic spectra appear as evidence of quantum coherence in light-harvesting systems related to electronic-vibrational resonant interactions. Nature, however, takes place in a non-equilibrium steady-state; therefore, the relevance of these arguments to the natural process is unclear. Here, we examine the role of intramolecular vibrations in the non-equilibrium steady-state of photosynthetic dimers in the natural scenario of incoherent light excitation. Specifically, we analyze the PEB dimer in the cryptophyte algae PE545 antenna protein. It is found that vibrations resonant with the energy difference between exciton states only marginally increase the quantum yield and the imaginary part of the intersite coherence that is relevant for transport compared to non-resonant vibrations in the natural non-equilibrium steady-state. That is, the electronic-vibrational resonance interaction does not significantly enhance energy transport under natural incoherent light excitation conditions.

Prior knowledge auxiliary for few-shot pest detection in the wild.

One of the main techniques in smart plant protection is pest detection using deep learning technology, which is convenient, cost-effective, and responsive. However, existing deep-learning-based methods can detect only over a dozen common types of bulk agricultural pests in structured environments. Also, such methods generally require large-scale well-labeled pest data sets for their base-class training and novel-class fine-tuning, and these significantly hinder the further promotion of deep convolutional neural network approaches in pest detection for economic crops, forestry, and emergent invasive pests. In this paper, a few-shot pest detection network is introduced to detect rarely collected pest species in natural scenarios. Firstly, a prior-knowledge auxiliary architecture for few-shot pest detection in the wild is presented. Secondly, a hierarchical few-shot pest detection data set has been built in the wild in China over the past few years. Thirdly, a pest ontology relation module is proposed to combine insect taxonomy and inter-image similarity information. Several experiments are presented according to a standard few-shot detection protocol, and the presented model achieves comparable performance to several representative few-shot detection algorithms in terms of both mean average precision (mAP) and mean average recall (mAR). The results show the promising effectiveness of the proposed few-shot detection architecture.

A meta-analysis for assessing the contributions of trypsin and chymotrypsin as the two major endoproteases in protein hydrolysis in fish intestine

For the majority of fish species, regardless of being gastric or agastric, trypsin and chymotrypsin are known as the two main alkaline proteases responsible for the initial stage of protein hydrolysis in the fish intestine. Although the critical role of these proteases for protein hydrolysis in fish intestine is without doubt, the relative input of each enzyme in protein hydrolysis is still unclear. Data used in the present study has been retrieved from a bibliographic search using the Dimensions application (https://app.dimensions.ai/discover/publication tool). Retrieved articles were carefully inspected to identify whether they contained the description of the development of ontogenetic activities for trypsin, chymotrypsin, and total alkaline proteases in fish intestine. From the list of consulted articles, 21 studies were chosen based on correlation coefficients (Pearson correlation test), and four groups of fish were identified with high significant correlation between 1) the activity of chymotrypsin and total alkaline proteases; 2) the activity of trypsin, chymotrypsin, and total alkaline proteases; 3) the activity of trypsin and total alkaline proteases, and 4) mainly negative correlation between trypsin, chymotrypsin, and total alkaline proteases. These results indicated that the relative inputs of trypsin and chymotrypsin in protein hydrolysis may vary significantly among different fish species, which is a crucial point for proper understanding of species-specific digestive traits in both natural and aquaculture scenarios.

Post-exposure Period as a key Factor to Assess Cadmium Toxicity: Lethal vs. Behavioral Responses

The exposure of animals to pollution in ecosystems is not always chronic. Toxicants can remain in aquatic ecosystems for a short-term. To improve the extrapolation of laboratory results to natural scenarios the inclusion of post-exposure periods is a relevant issue. The present study focuses on the assessment of cadmium toxicity on survival and behavior of the aquatic snail Potamopyrgus antipodarum (Tateidae, Mollusca) during exposure and post-exposure. Animals were exposed for 48 h to cadmium (0.05, 0.14, 0.44 and 1.34 mg Cd/L) and 168 h of post-exposure. During the post-exposure period an increase in mortality in all concentrations was observed. The effects observed during the post-exposure period on the LC50 and EC50 were significant. During the post-exposure, behavior showed a clear recovery in surviving animals exposed to 0.44 mg Cd/L. Animals exposed to 0.05 mg Cd/L did not show differences with control. Therefore, mortality after exposure should be included in the ecotoxicological bioassays for a more realistic estimation of the cadmium effects. To assess the degree of animal recovery after cadmium exposure, behaviour has been shown as an adequate parameter.

Accelerometer time series augmentation through externally driving a non-linear dynamical system

Coupled non-linear dynamical systems have gained attention not only as a ubiquitous occurrence in natural and artificial scenarios, but also as a basis for atypical computation paradigms. This paper introduces an approach to time series data augmentation involving driving a single low-dimensional entity, namely the Rössler system, with a physically-recorded sensor signal, and leveraging its responses to enhance the performance of a conventional classifier. A representative internet of things application in agriculture, namely cattle behavior recognition using a triaxial accelerometer, is investigated via a publicly-available dataset. Numerical simulations and experiments with an analog electronic circuit reveal that diversified responses to the external input are attainable, and the additional time series obtained from the driven system enhance the behavior classification accuracy. The advantage, down to the combined effects of its dynamical response and a static non-linearity transforming the driving signal, is appreciable both when using a small multi-layer perceptron network operating on elementary features and, albeit to a lesser extent, when feeding the time series directly to a convolutional neural network. One possibility is that the driven system translates non-linear dynamical features into linear signal properties that can be more easily extracted. Some considerations about the engineering implementation using either analog hardware or programmable logic on an edge device are given.

Soil Erosion Characteristics and Scenario Analysis in the Yellow River Basin Based on PLUS and RUSLE Models.

Soil erosion is an important global environmental issue that severely affects regional ecological environment and socio-economic development. The Yellow River (YR) is China's second largest river and the fifth largest one worldwide. Its watershed is key to China's economic growth and environmental security. In this study, six impact factors, including rainfall erosivity (R), soil erosivity (K), slope length (L), slope steepness (S), cover management (C), and protective measures (P), were used. Based on the revised universal soil loss equation (RUSLE) model, and combined with a geographic information system (GIS), the temporal and spatial distribution of soil erosion (SE) in the YR from 2000 to 2020 was estimated. The patch-generating land use simulation (PLUS) model was used to simulate the land-use and land-cover change (LUCC) under two scenarios (natural development and ecological protection) in 2040; the RUSLE factor P was found to be associated with LUCC in 2040, and soil erosion in the Yellow River Basin (YRB) in 2040 under the two scenarios were predicted and evaluated. This method has great advantages in land-use simulation, but soil erosion is greatly affected by rainfall and slope, and it only focuses on the link between land-usage alteration and SE. Therefore, this method has certain limitations in assessing soil erosion by simulating and predicting land-use change. We found that there is generally slight soil erosivity in the YRB, with the most serious soil erosion occurring in 2000. Areas with serious SE are predominantly situated in the upper reaches (URs), followed by the middle reaches (MRs), and soil erosion is less severe in the lower reaches. Soil erosion in the YRB decreased 11.92% from 2000 to 2020; thus, soil erosion has gradually reduced in this area over time. Based on the GIS statistics, land-use change strongly influences SE, while an increase in woodland area has an important positive effect in reducing soil erosion. By predicting land-use changes in 2040, compared to the natural development scenario, woodland and grassland under the ecological protection scenario can be increased by 1978 km2 and 2407 km2, respectively. Soil erosion can be decreased by 6.24%, indicating the implementation of woodland and grassland protection will help reduce soil erosion. Policies such as forest protection and grassland restoration should be further developed and implemented on the MRs and URs of the YR. Our research results possess important trend-setting significance for soil erosion control protocols and ecological environmental protection in other large river basins worldwide.

Particle dispersion and removal associated with kitchen range hood and whole house ventilation system

The objective of this study is to evaluate how the removal and dispersion of the cooking-generated particles in a residential unit vary with ventilation strategies. Computational fluid dynamics (CFD) simulations were performed to evaluate the particle removal and dispersion performance of six ventilation strategies with three make-up air supply scenarios and two kitchen range hood designs. The results showed that the particle capture efficiency ranged from 0.58 to 1.00 for 2.5 μm particles, and from 0.62 to 0.96 for 10 μm particles depending on the ventilation strategies. The peak particle number concentration of the breathing zone in the kitchen was the lowest when supplying the make-up air from the whole house ventilation system, which was only 0.07% of the peak concentration with supplying natural make-up air through a kitchen window. When using the make-up air from the whole house ventilation system, 1-h integrated exposure was decreased by 92.1% for the kitchen, 89.4% for the living room, and 98.7% for the bedroom, compared to the natural make-up air supply scenario. The results reveal that supplying make-up air from the living room and bedrooms while operating a typical range hood yields the largest particle removal, suggesting effective control of residential exposure to cooking-generated particles.

Landscape ecological risk assessment and its driving factors of multi-mountainous city

Urban land has been expanding under the background of rapid urbanization, which leads to the increasingly prominent problem of regional ecological security in multi-mountainous cities. In order to scientifically formulate land use policies and maintain regional ecological security pattern, it is necessary to assess regional landscape ecological risk (LER), explore its influencing factors, and simulate the LERs under different scenarios in the future. This study takes Guiyang, a typical mountainous city in the karst area of southwest China, as the study area. Based on the three-phase remote sensing images, the landscape pattern index and the Geodetector method (GDM) were used to assess LER and the corresponding driving factors from 2000 to 2020, and the PLUS model was used to simulate LER under different urban development scenarios in 2030. The results showed: (1) The average landscape ecological risk index (LERI) in 2000, 2010, and 2020 were 0.0341, 0.0320, and 0.0304, respectively. This shows that the overall LER of Guiyang is low and gradually decreases over time. (2) The LER pattern has significant positive spatial autocorrelation, but the autocorrelation decreases with the development of the city. (3) From 2000 to 2020, ecological driving factors were the main influencing factors of LER, but the impact of social driving factors on LER was growing with time. (4) The LER change of Guiyang in 2030 varies significantly under different scenarios, among which the area of the risk up zone in the natural development scenario is the largest, followed by the farmland protection scenario, and the ecological priority scenario is the smallest. This study will provide a scientific basis and reference for the overall development planning of multi-mountainous cities, regional ecological protection planning, and the formulation of relevant land use policies.

Magnetic Induction-Based Susceptometer: Calibration Procedure for Complex Susceptibility Measurement and Extended Application in Natural Scenarios

The fast and in situ measurement of the complex magnetic susceptibility stands a potential geological tool for enhanced characterization of rocks and comprehension of the geological context of the landing and exploration sites when used on board planetary rovers. The real part of susceptibility is related to the capability to acquire magnetization and the imaginary part, with resistivity and magnetic energy loss mechanism of rocks. Therefore, the determination of the rocks’ susceptibility provides key information as to the need for the presence of water in the formation of certain minerals, which can be used as one of the rocks selection criteria, in sample return missions. Previous work has been done in the conception of a novel portable instrument, based on magnetic induction, to measure the complex susceptibility of rocks in the context of planetary exploration. The next step is to create a comprehensive calibration procedure to extract magnetic properties information from the direct readings. This work describes a novel instrument calibration methodology. The calibration of the novel instrument comprises a comparative methodology with representative patterns for the real and the imaginary components of the susceptibility. Therefore, the work also includes calibration sample conception, manufacture, and characterization by different techniques.

Probability or time: Effect of presentation format on continuous risky decisions

Abstract Continuous risky decisions refer to decisions that involve trade-offs among options with persistent risks. People can use the probability of occurrence per unit time (e.g., ‘the probability of occurrence is 1% per month’) or the average time of risk occurrence (e.g., ‘the average occurrence time is 100 months’) to represent continuous risky options. In this study, we examined the effect of the presentation format (i.e., the probability of occurrence per unit time vs. the average time of risk occurrence) on continuous risky decisions in the gain domain and further explored the underlying mechanism. In Study 1 (N = 122), we demonstrated the effect of presentation format on continuous risky decisions and the moderating effect of the magnitude of probabilities. Specifically, when the probabilities were relatively low, compared with the probability of occurrence per unit time, using the average time of risk occurrence to present the continuous risky options led to more risk-averse decisions. However, when the probabilities were relatively high, compared with the probability of occurrence per unit time, the presentation format of the average time occurrence led to more risk-seeking decisions. In Study 2 (N = 136), we found that the moderating effect of the option probabilities on continuous risky decisions was mediated by the subjective attribute-wise difference judgment. In Study 3 (N = 221), we replicated the effect of presentation format on continuous risky decisions in more natural scenarios. The study offered a deep understanding of the mechanism of continuous risky decision-making, and the results were conducive to further developing theories in relevant fields.

Vision Transformer With Enhanced Self-Attention for Few-Shot Ship Target Recognition in Complex Environments

Ship target recognition is essential for maritime transportation, commercial trade, maritime security, and monitoring illegal activity. The majority of previous ship target recognition models are based on fully-supervised learning, which necessitates vast amounts of labeled training data. However, optical lenses capturing ship images in natural scenarios have numerous complex environments, making feature extraction difficult due to hardware, weather, light, waves, and other factors. Moreover, image annotation is also both expensive and time-consuming. How to effectively learn from unbalanced, limited, and sparsely annotated sample data is a significant challenge. In this paper, we propose a new vision transformer with enhanced self-attention(SAVT) that can locate ship targets in complex environments with just a few shots. SAVT consists of a novel enhanced self-attention(ESA) module and a novel measurement self-adjusting computation(MAC) module to differentiate unique ship classes in complex environments with few labeled samples. The ESA module focuses on the features of the target-region at each layer of the backbone network in order to ensure that the contour detailed features are extracted effectively from ship images with complex environments. The model is then enhanced in terms of speed and stability by utilizing the MAC module. CIB-ships and public MAR-ships datasets are used to evaluate the proposed method. In this paper, the results demonstrate that SAVT achieves good performance on few-shot labeled data under both 1-shot and 5-shot settings, while also providing valuable guidance for maritime ship target recognition with limited labeled samples.