Subjects: Psychology >> Cognitive Psychology Subjects: Computer Science >> Computer Application Technology submitted time 2024-08-02
Abstract： Cognitive modeling involves instantiating theoretical or model-based knowledge of cognitive processes into computational models and validating these theories by fitting behavioral and/or neuroimaging data. It enhances our understanding of human cognition through quantitative analysis and aids in the study of individual differences. Despite the ability of theory-driven computational models to generate simulated data, their complexity makes it difficult to determine the likelihood function, hindering the estimation of model parameters and comparisons between models based on observed data. This challenge is known as the inverse problem of generative modeling, and in response to the dilemma that the likelihood function is impossible or difficult to compute, which in turn gave rise to likelihood-free inference.
likelihood-free inference, a case of simulation-based inference, which uses simulated data to approximate or circumvent the calculation of the likelihood function. This method enables the fitting and evaluation of the model. Approximate Bayesian Computation (ABC) and Probability Density Approximation (PDA) are two common techniques used in likelihood-free inference. ABC compares simulated data to observed data, while PDA uses a kernel density estimator to approximate the likelihood function. Both methods are powerful tools for model selection and parameter estimation, particularly when the likelihood function is intractable or unknown. However, these methods may suffer from the curse of dimensionality, as the number of model parameters increases, the computational cost and complexity of the simulation-based approaches grow exponentially, which can make the methods impractical for high-dimensional data and models.
Advances in deep learning and neural network technologies have led to the emergence of a new neural simulation-based inference (NSBI). NSBI leverages the power of deep learning to address the limitations of traditional simulation-based methods. NSBI possesses an amortization property, which allows the generation of a large amount of simulated data to be integrated into the training process. Consequently, once the neural network is trained, the inference step can be performed without the need for generating additional simulated data, significantly reducing computational overhead. Furthermore, with the advancement of neural conditional probability density estimation techniques, such as Normalizing Flows, NSBI can easily train models to estimate likelihood functions and posterior distribution functions. Neural posterior estimation methods, which offer a departure from conventional ABC techniques, directly sample from the posterior distribution using input data. Similarly, neural likelihood estimation methods, a substitute for PDA, compute likelihood values by leveraging both input data and prior parameters. These techniques enable the construction of flexible and complex cognitive models, making NSBI a promising approach for likelihood-free inference in high-dimensional settings.
NSBI has gained significant attention in the field of cognitive modeling and has been applied to various scenarios, including likelihood estimation, posterior estimation, and model comparison. For instance, neural likelihood networks such as LANs and MNLE are employed to estimate the likelihood function for intricate cognitive models, with MNLE being particularly adept at handling mixed data types with both continuous and discrete variables. In parameter inference for cognitive models, Bayesflow stands out as a neural posterior network capable of tackling a diverse array of complex models. For model comparison, Evidence Networks and Hierarchical Evidence Networks are utilized, with the Hierarchical variant being well-suited for nested data structures. Tools such as LANs, sbi, and Bayesflow are continuously optimizing the workflow of neural network-based simulation inference. These advancements have enabled NSBI to be applied to large-scale studies involving over a million data points, allowing for the construction of complex models that were previously difficult to build. This approach not only facilitates rapid validation of models and theories but also helps identify flaws and optimize performance, making NSBI a transformative technique with the potential to revolutionize the understanding and analysis of intricate systems.
While these new technologies show promise in cognitive modeling, this paper also discusses their limitations and offers constructive guidance for their use. The paper discusses the trade-offs of neural network training costs and model accuracy, the integration of NSBI methods for comprehensive analysis, and the importance of effective training for reliable models. It also emphasizes the potential for these technologies to enhance interdisciplinary collaboration, particularly between neuroscience, cognitive modeling, and other fields, to deepen our understanding of the mind and brain.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2024-08-01
Abstract： In daily life and business operations, individuals often overlook potential “high-probability, large-loss” risks, leading to irreparable consequences. To explore the underlying scientific issues of this phenomenon, this project introduces the novel concept of "myopic risk ignorance". Specifically, this concept refers to the difficulty decision-makers encounter in accurately perceiving or assessing the interdependencies among repeated similar decisions due to myopic evaluations and cognitive limitations. As a result, driven by the pursuit of immediate gains in individual decisions, decision-makers often sacrifice global optimal goals and gradually ignore long-term risks. Thus, myopic risk ignorance attitude can be viewed as a specific form of myopic risk attitude within the context of sequential decision making. Sequential decision making characterizes a dynamic process where individuals, groups, or organizations make a series of interconnected decisions over time to achieve an optimal overall goal. Despite the prevalence of sequential decision making in real-life scenarios, current behavioral decision-making research predominantly focuses on one-shot decisions, overlooking genuine behavioral patterns in sequential decision making. This oversight has limited the exploration of myopic risk ignorance. To address this gap, the project aims to reveal the patterns and key characteristics of myopic risk ignorance within the framework of sequential decision making. Furthermore, it will develop a tailored research paradigm to measure attitudes towards myopic risk ignorance and investigate its underlying mechanisms within decision processes and objectives. The findings are expected to complement and broaden the field of behavioral decision-making research and provide a theoretical foundation for the future development of sequential decision support systems.
Subjects: Psychology >> Management Psychology submitted time 2024-07-31
Abstract：
The wave of intelligence has injected new impetus for China to transform from a manufacturing power to a manufacturing powerhouse and for the intelligent transformation of enterprises. However, at the same time, knowledge workers in the manufacturing industry face the challenge of reshaping the labor process with artificial intelligence. This paper innovatively proposes the dynamic concept of technical hollowing out in the context of artificial intelligence to reflect the impact of the development and application of artificial intelligence technology on the labor process of knowledge workers in the manufacturing industry. This paper has three research purposes: First, to explore the definition, dimensional structure, and measurement scale of technical hollowing out based on the temporal dynamic perspective of sensemaking theory; second, based on the “cognition-behavior” interaction chain, we construct a two-stage model of “executive skill hollowing out” and “conceptual skill hollowing out” for the technical hollowing out of knowledge workers, and further explore the catalytic role of situational factors at the enterprise and employee levels; third, based on the capability-building perspective, the impact of technical hollowing out on knowledge workers’ dual innovation behavior and sustainable career development is explored. The research conclusions can not only enrich the theoretical research on technical hollowing out in the context of artificial intelligence, but also provide practical inspiration for the establishment of harmonious and stable labor relations, and the realization of long-term development and shared prosperity of enterprises and employees during the intelligent transformation of China’s manufacturing industry.
Subjects: Psychology >> Cognitive Psychology submitted time 2024-07-31
Abstract： Visual attention, which is a mechanism of information selection and cognitive resource allocation, is not only the basis of information processing and cognitive functions, but also an important condition for accomplishing various social behaviors. Numerous studies have confirmed that visual attention affects individual decision-making preferences. On the basis of a comprehensive review of previous studies, this article sorts out the effects of visual attention on perceptual decision-making, preferential decision-making and other social decision-making. Moreover, it first summarizes and discusses four hypotheses: the mere exposure effect, the gaze cascade hypothesis, the sequential sampling model, and the adaptive attention representation model. Based on this, this article has explained the role of visual attention in these three kinds of decision-making. Finally, four prospects are proposed: future studies should (a) consider setting options with different degrees of preference differences, (b) examine moderating factors in decision-making situations or visual environments, (c) consider the roles of other forms of attention in decision-making, and (d) explore the mechanisms of the sequential sampling model further in order to deepen the understanding of the effects of visual attention on decision-making and its mechanisms.
Subjects: Biology >> Botany submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： Savanna, semi-deserts, and hot deserts characterize the Saharo-Arabian region, which includes Morocco, Mauretania, Algeria, Tunisia, Libya, Egypt, Palestine, Kuwait, Saudi Arabia, Qatar, Bahrain, the United Arab Emirates, Oman, Yemen, southern Jordan, Syria, Iraq, Iran, Afghanistan, Pakistan, and northern India. Its neighboring regions, the Sudano-Zambezian region belonging to the Paleotropical Kingdom and the Mediterranean and Irano-Turanian regions included in the Holarctic Kingdom, share a large portion of their flora with the Saharo-Arabian region. Despite the widespread acknowledgment of the region's global importance for plant diversity, an up to date list of the Saharo-Arabian endemics is still unavailable. The available data are frequently insufficient or out of date at both the whole global and the national scales. Therefore, the present study aims at screening and verifying the Saharo-Arabian endemic plants and determining the phytogeographical distribution of these taxa in the Egyptian flora. Hence, a preliminary list of 429 Saharo-Arabian endemic plants in Egypt was compiled from the available literature. Indeed, by excluding the species that were recorded in any countries or regions outside the Saharo-Arabian region based on different literature, database reviews, and websites, the present study has reduced this number to 126 taxa belonging to 87 genera and 37 families. Regarding the national geographic distribution, South Sinai is the richest region with 83 endemic species compared with other eight phytogeographic regions in Egypt, followed by the Isthmic Desert (the middle of Sinai Peninsula, 53 taxa). Sahara regional subzone (SS1) distributes all the 126 endemic species, Arabian regional subzone (SS2) owns 79 taxa, and Nubo-Sindian subzone (SS3) distributes only 14 endemics. Seven groups were recognized at the fourth level of classification as a result of the application of the two-way indicator species analysis (TWINSPAN) to the Saharo-Arabian endemic species in Egypt, i.e., I Asphodelus refractus group, II Agathophora alopecuroides var. papillosa group, III Anvillea garcinii group, IV Reseda muricata group, V Agathophora alopecuroides var. alopecuroides group, VI Scrophularia deserti group, and VII Astragalus schimperi group. It's crucial to clearly define the Saharo-Arabian endemics and illustrate an updated verified database of these taxa for a given territory for providing future management plans that support the conservation and sustainable use of these valuable species under current thought-provoking devastating impacts of rapid anthropogenic and climate change in this region.
Subjects: Biology >> Botany submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： The presence of invasive plant species poses a substantial ecological impact, thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary. This study uses maximum entropy (MaxEnt) modeling to forecast the likelihood of Leucaena leucocephala (Lam.) de Wit invasion in Saudi Arabia under present and future climate change scenarios. Utilizing the MaxEnt modeling, we integrated climatic and soil data to predict habitat suitability for the invasive species. We conducted a detailed analysis of the distribution patterns of the species, using climate variables and ecological factors. We focused on the important influence of temperature seasonality, temperature annual range, and precipitation seasonality. The distribution modeling used robust measures of area under the curve (AUC) and receiver-operator characteristic (ROC) curves, to map the invasion extent, which has a high level of accuracy in identifying appropriate habitats. The complex interaction that influenced the invasion of L. leucocephala was highlighted by the environmental parameters using Jackknife test. Presently, the actual geographic area where L. leucocephala was found in Saudi Arabia was considerably smaller than the theoretical maximum range, suggesting that it had the capacity to expand further. The MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC curve. Precipitation and temperature were the primary factors influencing the potential distribution of L. leucocephala. Currently, an estimated area of 216,342 km2 in Saudi Arabia was at a high probability of invasion by L. leucocephala. We investigated the potential for increased invasion hazards in the future due to climate change scenarios (Shared Socioeconomic Pathways (SSPs) 245 and 585). The analysis of key climatic variables, including temperature seasonality and annual range, along with soil properties such as clay composition and nitrogen content, unveiled their substantial influence on the distribution dynamic of L. leucocephala. Our findings indicated a significant expansion of high risk zones. High-risk zones for L. leucocephala invasion in the current climate conditions had notable expansions projected under future climate scenarios, particularly evident in southern Makkah, Al Bahah, Madina, and Asir areas. The results, backed by thorough spatial studies, emphasize the need to reduce the possible ecological impacts of climate change on the spread of L. leucocephala. Moreover, the study provides valuable strategic insights for the management of invasion, highlighting the intricate relationship between climate change, habitat appropriateness, and the risks associated with invasive species. Proactive techniques are suggested to avoid and manage the spread of L. leucocephala, considering its high potential for future spread. This study enhances the overall comprehension of the dynamics of invasive species by combining modeling techniques with ecological knowledge. It also provides valuable information for decision-making to implement efficient conservation and management strategies in response to changing environmental conditions.
Subjects: Biology >> Botany submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： Rising atmospheric CO2 (carbon dioxide) concentrations and salinization are manifestations of climate change that affect plant growth and productivity. Species with an intermediate C3-C4 type of photosynthesis live in a wide range of precipitation, temperature, and soil quality, but are more often found in warm and dry habitats. One of the intermediate C3-C4 photosynthetic type is C2 photosynthesis with a carbon concentration mechanism (CCM) that reassimilates CO2 released via photorespiration. However, the ecological significance under which C2 photosynthesis has advantages over C3 and C4 plants remains largely unexplored. Salt tolerance and functioning of CCM were studied in plants from two populations (P1 and P2) of Sedobassia sedoides (Pall.) Freitag & G. Kadereit Asch. species with C2 photosynthesis exposed to 4 d and 10 d salinity (200 mM NaCl) at ambient (785.7 mg/m3, aCO2) and elevated (1571.4 mg/m3, eCO2) CO2. On the fourth day of salinity, an increase in Na+ content, activity catalase, and superoxide dismutase was observed in both populations. P2 plants showed an increase in proline content and a decrease in photosynthetic enzyme content: rubisco, phosphoenolpyruvate carboxylase (PEPC), and glycine decarboxylase (GDC), which indicated a weakening of C2 and C4 characteristics under salinity. Treatment under 10 d salinity led to an increased Na+ content and activity of cyclic electron flow around photosystem I (PSI CEF), a decreased content of K+ and GDC in both populations. P1 plants showed greater salt tolerance, which was assessed by the degree of reduction in photosynthetic enzyme content, PSI CEF activity, and changes in relative growth rate (RGR). Differences between populations were evident under the combination of eCO2 and salinity. Under long-term salinity and eCO2, more salt-tolerant P1 plants had a higher dry biomass (DW), which was positively correlated with PSI CEF activity. In less salt-tolerant P2 plants, DW correlated with transpiration and dark respiration. Thus, S. sedoides showed a high degree of photosynthetic plasticity under the influence of salinity and eCO2 through strengthening (P1 plants) and weakening C4 characteristics (P2 plants).
Subjects: Biology >> Ecology submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China, exhibiting typical mountain-oasis-desert distribution characteristics. In recent decades, climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems. However, the trade-offs and synergies between ecosystem services (ESs) have not been thoroughly examined. This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs. Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Revised Wind Erosion Equation (RWEQ) using land use/land cover (LULC), climate, vegetation, soil, and hydrological data, we quantified the spatiotemporal changes in the five principal ESs (carbon storage, water yield, food production, wind and sand prevention, and habitat quality) of the watershed from 1995 to 2020. Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs. The findings reveal that water yield, carbon storage, and habitat quality exhibited relatively high levels in the upstream, while food production and wind and sand prevention dominated the midstream and downstream, respectively. Furthermore, carbon storage, food production, wind and sand prevention, and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020. Specifically, carbon storage, wind and sand prevention, and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream. Food production in the midstream showed a continuously increasing trend during the study period. Trade-off relationships were identified between water yield and wind and sand prevention, water yield and carbon storage, food production and water yield, and habitat quality and wind and sand prevention. Prominent temporal and spatial synergistic relationships were observed between different ESs, notably between carbon storage and habitat quality, carbon storage and food production, food production and wind and sand prevention, and food production and habitat quality. Water resources emerged as a decisive factor for the sustainable development of the basin, thus highlighting the intricate trade-offs and synergies between water yield and the other four services, particularly the relationship with food production, which warrants further attention. This research is of great significance for the protection and sustainable development of river basins in arid areas.
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Soil Science submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： Soil salinization may affect biodiversity and species composition, leading to changes in the plant community structure. However, few studies have explored the spatial pattern of soil salinization and its effects on shrub community structure at the ecosystem scale. Therefore, we conducted a transect sampling of desert shrublands in Northwest China during the growing season (June–September) in 2021. Soil salinization (both the degree and type), shrub community structure (e.g., shrub density and height), and biodiversity parameters (e.g., Simpson diversity, Margalf abundance, Shannon-Wiener diversity, and Pielou evenness indices) were used to assess the effects of soil salinization on shrub community structure. The results showed that the primary degree of soil salinization in the study area was light salinization, with the area proportion of 69.8%. Whereas the main type of soil salinization was characterized as sulfate saline soil, also accounting for 69.8% of the total area. Notably, there was a significant reduction in the degree of soil salinization and a shift in the type of soil salinization from chloride saline soil to sulfate saline soil, with an increase in longitude. Regional mean annual precipitation (MAP), mean annual evapotranspiration (MAE), elevation, and slope significantly contributed to soil salinization and its geochemical differentiation. As soil salinization intensified, shrub community structure displayed increased diversity and evenness, as indicated by the increases in the Simpson diversity, Shannon-Wiener diversity, and Pielou evenness indices. Moreover, the succulent stems and leaves of Chenopodiaceae and Tamaricaceae exhibited clear advantages under these conditions. Furthermore, regional climate and topography, such as MAP, MAE, and elevation, had greater effects on the distribution of shrub plants than soil salinization. These results provide a reference for the origin and pattern of soil salinization in drylands and their effects on the community structure of halophyte shrub species.
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Soil Science submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： Perennial grass-legume mixtures have been extensively used to restore degraded grasslands, increasing grassland productivity and forage quality. Tillage is crucial for seedbed preparation and sustainable weed management for the establishment of grass-legume mixtures. However, a common concern is that intensive tillage may alter soil characteristics, leading to losses in soil organic carbon (SOC). We investigated the plant community composition, SOC, soil microbial biomass carbon (MBC), soil enzyme activities, and soil properties in long-term perennial grass-legume mixtures under two different tillage intensities (once and twice) as well as in a fenced grassland (FG). The establishment of grass-legume mixtures increased plant species diversity and plant community coverage, compared with FG. Compared with once tilled grassland (OTG), twice tilled grassland (TTG) enhanced the coverage of high-quality leguminous forage species by 380.3%. Grass-legume mixtures with historical tillage decreased SOC and dissolved organic carbon (DOC) concentrations, whereas soil MBC concentrations in OTG and TTG increased by 16.0% and 16.4%, respectively, compared with FG. TTG significantly decreased the activity of N-acetyl-β-D-glucosaminidase (NAG) by 72.3%, whereas soil enzyme β-glucosidase (βG) in OTG and TTG increased by 55.9% and 27.3%, respectively, compared with FG. Correlation analysis indicated a close association of the increase in MBC and βG activities with the rapid decline in SOC. This result suggested that MBC was a key driving factor in soil carbon storage dynamics, potentially accelerating soil carbon cycling and facilitating biogeochemical cycling. The establishment of grass-legume mixtures effectively improves forage quality and boosts plant diversity, thereby facilitating the restoration of degraded grasslands. Although tillage assists in establishing legume-grass mixtures by controlling weeds, it accelerates microbial activity and organic carbon decomposition. Our findings provide a foundation for understanding the process and effectiveness of restoration management in degraded grasslands.
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Soil Science submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： The eastern foothills of the Helan Mountains in China are a typical mountainous region of soil and gravel, where gravel could affect the water movement process in the soil. This study focused on the effects of different gravel contents on the water absorption characteristics and hydraulic parameters of stony soil. The stony soil samples were collected from the eastern foothills of the Helan Mountains in April 2023 and used as the experimental materials to conduct a one-dimensional horizontal soil column absorption experiment. Six experimental groups with gravel contents of 0%, 10%, 20%, 30%, 40%, and 50% were established to determine the saturated hydraulic conductivity (Ks), saturated water content (θs), initial water content (θi), and retention water content (θr), and explore the changes in the wetting front depth and cumulative absorption volume during the absorption experiment. The Philip model was used to fit the soil absorption process and determine the soil water absorption rate. Then the length of the characteristic wetting front depth, shape coefficient, empirical parameter, inverse intake suction and soil water suction were derived from the van Genuchten model. Finally, the hydraulic parameters mentioned above were used to fit the soil water characteristic curves, unsaturated hydraulic conductivity (Kθ) and specific water capacity (C(h)). The results showed that the wetting front depth and cumulative absorption volume of each treatment gradually decreased with increasing gravel content. Compared with control check treatment with gravel content of 0%, soil water absorption rates in the treatments with gravel contents of 10%, 20%, 30%, 40%, and 50% decreased by 11.47%, 17.97%, 25.24%, 29.83%, and 42.45%, respectively. As the gravel content increased, inverse intake suction gradually increased, and shape coefficient, Ks, θs, and θr gradually decreased. For the same soil water content, soil water suction and Kθ gradually decreased with increasing gravel content. At the same soil water suction, C(h) decreased with increasing gravel content, and the water use efficiency worsened. Overall, the water holding capacity, hydraulic conductivity, and water use efficiency of stony soil in the eastern foothills of the Helan Mountains decreased with increasing gravel content. This study could provide data support for improving soil water use efficiency in the eastern foothills of the Helan Mountains and other similar rocky mountainous areas.
Subjects: Geosciences >> Hydrology submitted time 2024-07-31 Cooperative journals: 《干旱区科学》
Abstract： Understanding the distribution and dynamics of glaciers is of great significance to the management and allocation of regional water resources and socio-economic development in arid regions of Northwest China. In this study, based on 36 Landsat images, we extracted the glacier boundaries in the Manas River Basin, Northwest China from 2000 to 2020 using eCognition combined with band operation, GIS (geographic information system) spatial overlay techniques, and manual visual interpretation. We further analyzed the distribution and variation characteristics of glacier area, and simulated glacial runoff using a distributed degree-day model to explore the regulation of runoff recharge. The results showed that glacier area in the Manas River Basin as a whole showed a downward trend over the past 21 a, with a decrease of 10.86% and an average change rate of –0.54%/a. With the increase in glacier scale, the number of smaller glaciers decreased exponentially, and the number and area of larger glaciers were relatively stable. Glacier area showed a normal distribution trend of increasing first and then decreasing with elevation. About 97.92% of glaciers were distributed at 3700–4800 m, and 48.11% of glaciers were observed on the northern and northeastern slopes. The retreat rate of glaciers was the fastest (68.82%) at elevations below 3800 m. There was a clear rise in elevation at the end of glaciers. Glaciers at different slope directions showed a rapid melting trend from the western slope to the southern slope then to the northern slope. Glacial runoff in the basin showed a fluctuating upward trend in the past 21 a, with an increase rate of 0.03×108 m3/a. The average annual glacial runoff was 4.80×108 m3, of which 33.31% was distributed in the ablation season (June–September). The average annual contribution rate of glacial meltwater to river runoff was 35.40%, and glacial runoff accounted for 45.37% of the total runoff during the ablation season. In addition, precipitation and glacial runoff had complementary regulation patterns for river runoff. The findings can provide a scientific basis for water resource management in the Manas River Basin and other similar arid inland river basins.
Subjects: Psychology >> Social Psychology submitted time 2024-07-31
Huarong LIU
Xinyu ZHU
Nanying LI
Xinrui HUANG
Qingqing DU
Ruoting LIU
Liyunhan PENG
Feng YU
Kaiping PENG
Sylvia Xiaohua CHEN
Xiaomeng HU
Abstract： With the rapid development and widespread application of artificial intelligence (AI) technology, the profound cultural influence on AI values has attracted widespread attention. Research to date, however, has not systemically looked at both the human universals and cultural differences in people’s normative expectations of AI values. To further explore the potential impacts of culture on AI values through the lens of cultural psychology and highlight the importance of taking into account the role of cultural diversity played in AI developments and applications, our current integrative review briefly synthesizes what might be the cross-cultural consensus and what might be the cultural differences in shaping people’s attitudes, behaviors, and normative expectations regarding AI values. In addition, we discuss the vital role of cultural beliefs and cultural norms in the ethical supervision and application of AI in human society. To better understand the complex interaction between AI and culture, future work should focus on developing and iterating algorithms for diverse cultural scenarios, thereby both promoting the globalization of AI application and meet diverse cultural demands to ultimately improve the well-being of individuals and society across the globe.
Peer Review Status:Awaiting Review
Subjects: Medicine, Pharmacy >> Preventive Medicine and Hygienics submitted time 2024-07-31 Cooperative journals: 《中国全科医学》
Abstract： Background With the improvement of economic level and changes in lifestyle of residents，the obesity among children and adolescents has become increasingly severe，threatening the healthy growth of children and adolescents.BMI was used as an evaluation index of obesity in most previous studies，which may underestimate the prevalence of central obesity. Therefore，it is urgent to evaluate the waist circumference（WC）and trend of the prevalence of central obesity among children and adolescents in Putuo District，in order to provide scientific basis for targeted proposed intervention. Objective To analyze WC and the trend in the prevalence of central obesity among children and adolescents aged 7-18 years in Putuo District，Shanghai，from 2018 to 2023. Methods Data on medical examinations of primary and secondary school students in Putuo District in 2018 and 2020-2023 were used to analyze the WC，the prevalence of central obesity and the trends. The 90th percentile（P90）age-specific children and adolescents of different genders was used as the cut-off point of high WC，and WC exceeding the P90 value was defined as central obesity. SPSS 22.0 and SAS 13.1 were used for statistical analysis and Excel 2021 was used for graphic plotting. Results A total of 280 648 primary and secondary school students participated in the medical examination in Putuo District，Shanghai，from 2018 to 2023，of which 146 334（52.1%）were male students and 134 314（47.9%）were female students，with an average age of 10.9±2.6 years. WC of male and female students from 2018 to 2023 showed fluctuating downward trends with a statistically significant difference（Hmale=209.785，Hfemale=373.076；P<0.001）. WC of male students decreased from 65.2（58.0，74.0）cm in 2018 to 64.8（56.9，74.0）cm in 2023 and female students decreased from 60.5（55.0，67.0）cm to 59.8（53.8，66.2）cm. Comparison of the prevalence of central obesity among male and female students in each year showed statistically significant differences（χ2 male=264.123，χ2 female=448.289；P<0.001）. The results of Cochran-Armitage trend test showed decreasing trends in prevalences of central obesity among male and female groups from 2018 to 2023（Ztrend male=-10.974，Ztrend female=-15.218；Ptrend<0.001）. The prevalence of central obesity among male students decreased from 28.8% to 24.6%，while that among female students decreased from 21.9% to 15.5%. WC and the prevalence of central obesity increased in 2022 for both sexes. Prevalence of central obesity showed increasing trends with age for both sexes（Ztrend male=35.167，Ztrend female=6.533；Ptrend<0.001）. Conclusion This study suggests that WC and the prevalence of central obesity among children and adolescents aged 7-18 in Putuo District are fluctuating and decreasing. WC and the prevalence of central obesity of male students are high than those of female students of the same age. The prevalence of central obesity is increasing with age. Results of this study provide theoretical support for the targeted intervention of central obesity in children and adolescents.
Subjects: Medicine, Pharmacy >> Preventive Medicine and Hygienics submitted time 2024-07-31 Cooperative journals: 《中国全科医学》
Abstract： Background With the aging population，the incidence of pressure injuries（PI）is gradually increasing. This not only severely impacts the quality of life for patients but also increases healthcare expenditures. However，the early detection and accurate staging of PI heavily depend on specialized training. Objective To construct and validate an artificial intelligence model for the automatic detection and staging of pressure injuries（PI）aimed at enhancing the real-time nature，accuracy，and objectivity of PI diagnostics. Methods A total of 693 pressure injury images from the electronic management system of pressure ulcers at Changshu City First People's Hospital were selected from January 2021 to February 2024，categorized into six stages according to guidelines：Stage Ⅰ（154 images），Stage Ⅱ（188 images），Stage Ⅲ（160 images），Stage Ⅳ（82 images），unstageable（52 images），and deep tissue injury（57 images）. A deep learning object detection model for PI was established using five different versions of the YOLOv8 neural network and transfer learning. The model evaluation metrics included accuracy，sensitivity，specificity，false positive rate，and detection speed. Finally，the model was deployed to a mobile application via the Ultralytics Hub platform，facilitating the application of the AI model in clinical practice.Results During the evaluation of a test set containing 142 PI images，the YOLOv8l version demonstrated high accuracy（0.827） and fast inference speed（68.49fps），achieving the best balance between precision and speed among the YOLO versions. Specifically，it achieved an overall accuracy of 93.18% across all categories，a sensitivity of 76.52%，a specificity of 96.29%，and a false positive rate of 3.72%. Among the six stages of PI，the model achieved the highest accuracy for Stage Ⅰ at 95.97%.The accuracies for Stage Ⅱ，Stage Ⅲ，Stage Ⅳ，deep tissue injury，and unstageable were 91.28%，91.28%，91.95%，95.30%，and 93.29%，respectively. In terms of processing speed，YOLOv8l took a total of 2.07 seconds to process 142 images，averaging 68.49 PI images per second. Conclusion The AI model based on the YOLOv8l network can quickly and accurately detect and stage PI. Deploying this model to a mobile app allows for portable use in clinical practice，demonstrating significant potential for clinical application.
Subjects: Biology >> Botany >> Applied botany submitted time 2024-07-31 Cooperative journals: 《广西植物》
Abstract： Newly emerged twigs are the most active part of plant branching systems and are most sensitive to changes in habitat such as light and temperature. Analyzing the differences in stem and leaf characteristics of the twigs and evaluating their growth status is crucial for understanding the growth and survival strategies of plants and their adaptability mechanisms. As an evergreen broad-leaved shrub, the crown of Kandelia obovata produces a certain number of the twigs in different seasons within a year. To gain a deeper understanding of the growth status and seasonal dynamics of the twigs of Kandelia obovata, this study investigated the growth traits of the stems and leaves of the twigs. Statistical methods such as variance analysis, multiple comparisons, and principal component analysis (PCA) were used to comprehensively evaluate the growth performance of the twigs in different seasons and to explore the growth and survival strategies of mangrove plants, represented by Kandelia obovata. The results were as follows: (1) The 14 trait indicators characterizing the growth status of the twigs showed significant variation, with a coefficient of variation ranging from 13.856% to 56.469%, and a strong correlation between the indicators. (2) The growth traits of the twigs varied significantly in different seasons, with the overall performance being highest in July followed by May, March, and October. Additionally, the importance of the growth traits was ranked as follows: leaf traits > biomass > stem configuration. (3) The total weight proportion of the 7 trait indicators such as leaf density, the ratio of leaf and stem biomass, leaf number, leaf biomass, large leaf area, stem length, and leaf area ratio was 87.146%, which were the key indicators characterizing the growth status of the twigs of Kandelia obovata. In conclusion, the growth status of the twigs reflects the adaptation strategy of the tree to resource levels, influenced by external factors such as light and temperature, as well as internal growth strategies. These research results provide insight into the response of the twigs to environmental changes in different seasons and offer a reference basis for the protection and sustainable development of Kandelia obovata population.
Subjects: Biology >> Botany >> Applied botany submitted time 2024-07-31 Cooperative journals: 《广西植物》
Abstract： Wheat is one of three major staple crops in the world, QTL mapping and candidate gene analysis of important agronomic traits are beneficial for breeding new cultivars. In this study, the excellent wheat varieties Shumai 969 and Shumai 830 were used to construct a recombinant inbred line (F7) population consisting of 89 lines, and the reduced representation genome sequencing technology was carried out to genotype this population and its parents. In field, the phenotype of plant height, internode length, awn length, spike length, flag leaf length, flag leaf width, tiller number, effective tiller number, thousand grain weight, grain length, grain width, and grain surface area were measured. The complete interval mapping method was employed to locate the QTL sites controlling these agronomic traits. The results were as follows: (1) A total of 27 QTLs were identified. These QTLs distributed on 13 distinct chromosomes, and could elucidate 3.74% to 26.7% of the phenotype variation of the agronomic traits. Among them, the QTL in the 608.58-609.12 Mb interval on chromosome 7B controlled both plant height and panicle length, which was identified by two years. The QTL in the 519.94-528.83 Mb interval on chromosome 5A controlled both tiller number and effective tiller number, and the QTL in the 437.38-439.30 Mb interval on chromosome 5D controlled both thousand grain weight and grain surface area. 7 QTLs located in the same positions as previously reported. (2) The gene function analysis showed 2 candidate genes associated with plant height traits, 4 candidate genes linked to tiller traits, and 3 candidate genes attributed to thousand grain weight within the mapped interval. The two candidate genes of plant height encoded a leucine repeat receptor-like protein kinase and a gibberellin 2-oxidase. The candidate genes of tiller encompassed a auxin response protein, a RING/U-box superfamily protein, and two F-box proteins. The candidate genes for the thousand grain weight encoded a leucine repeat receptor-like protein kinase, a protein kinase, and a chlorophyll a-b-binding protein. The identified QTLs and predicted major genes in this research established a foundation for the meticulous mapping and cloning of the major genes controlling the correspondent agronomic traits, and benefited breeding new wheat cultivars.
Subjects: Biology >> Botany >> Applied botany submitted time 2024-07-31 Cooperative journals: 《广西植物》
Abstract： NAC transcription factors play important roles in plant growth, development, and various stress responses. However, the molecular mechanism of the RdNAC72 gene in Rhododendron delavayi involved in the heat stress response was still unclear. To investigate the the roles of the RdNAC72 gene in heat stress response, we first designed primers for cloning the full length coding sequence of the RdNAC72 gene using PCR technology. Subsequently, the gene’s structure, function, and physicochemical properties were analyzed and predicted using bioinformatics method. The spatial and temporal expression characteristics of the RdNAC72 gene under heat stress and ABA were analyzed using real-time fluorescence quantitative PCR(RT-qPCR). The results were as follows: (1) The RdNAC72 gene had a full length of 1 005 bp, encoding 334 amino acids with a relative molecular weight of 37.415 kDa. Subcellular localization analysis showed that the RdNAC72 protein was located in the nucleus. (2) Multiple sequence alignment and phylogenetic analysis indicated that the RdNAC72 was most closely related to the RwNAC72 in R. williamsianum. Additionally, cis-acting element analysis revealed that the gene contains elements associated with hormone response, light response, anaerobic response, low temperature response, and heat stress response. (3) Heat stress could induce the expression of RdNAC72, exhibiting temporal and spatial expression specificity. After three days of heat stress treatment, the relative expression level of the RdNAC72 gene in leaves was significantly upregulated by 31.16-fold, while no significant changes were observed in stems and roots. After six days of heat stress treatment, the relative expression levels of RdNAC72 were significantly upregulated, with the highest observed in leaves (61.56-fold), followed by stems (50.14-fold), and roots (17.42-fold). Additionally, it was found that ABA was found to induce the expression of RdNAC72. (4) RT-qPCR analysis demonstrated a coordinated expression pattern between RdHSP17.2 and RdNAC72 with RdHSP17.2 containing multiple NAC recognition motifs (CATGTG) and core binding sequences (CACG) in its promoter region, suggesting it may be a downstream target gene of RdNAC72. Therefore, the RdNAC72, a transcription factor, localized in the nucleus, responds significantly to high temperatures and ABA, potentially activating the RdHSP17.2 expression to confer heat resistance. These findings not only understanding our comprehension of the biological functions of NAC transcription factors in response to stress, but also potentially guide future genetic and breeding strategies to enhance stress resilience in plants.
Subjects: Biology >> Botany >> Applied botany submitted time 2024-07-31 Cooperative journals: 《广西植物》
Abstract： Pogostemon cablin (Blanco) Benth. possesses significant medical and industrial values, as it can be used for medicinal purposes as well as for essential oil extraction. However, the yield and quality of P. cablin can vary depending on the ecological environment and artificial cultivation measures employed in different production regions and origins. In order to study the structural characteristics and compare the differences of the chloroplast genome of P. cablin of different origins, this study used the DNBSeq sequencing platform to sequence the whole genome of P. cablin, used getOrganelle to assemble the complete chloroplast genome, annotated the chloroplast genome through the OGDRAW website, and analyzed the basic structural characteristics, IR/SC boundary comparison, genome comparison and collinearity analysis, simple repeat sequences and interspersed repeat sequences, polymorphism analysis and relative usage analysis of synonymous codons. The results were as follows: (1)The full length of the chloroplast genomes of 20 different origins of patchouli was 152 461~152 510 bp, and 132 genes were annotated, including 87 CDS, 37 tRNA genes and 8 rRNA genes. (2)The mVISTA comparison found that atpF, atpF-atpH, rps16-trnQ_UUG, rpoB-trnC_GCA, accD, psaI-ycf4, petA-psbJ, rpl16, and rps15-ycf1 were hypervariable regions. (3) The sites with nucleic acid diversity greater than 0.002 were located in the trnM-CAU-atpB interval, ycf4, rpl32, and rpl32-trnL-UAC interval. (4)Analysis of the relative usage of synonymous codons detected a total of 64 codons encoding 20 amino acids, and there were 33 highly preferred codons, among which codons ending in A/U accounted for the majority. (5)74-76 SSRs, 15-18 palindrome repeat sequences, and 12-17 forward repeat sequences were detected. (6)After genetic distance analysis and phylogenetic analysis, only GSY_MLXY has a distant genetic relationship with other cultivated types. In this study, the genome structure and different sites identified of chloroplasts from 20 different sources of P. cablin were obtained, which provided basic data for the development of molecular markers and the selection of superior germplasm.
Subjects: Biology >> Botany >> Applied botany submitted time 2024-07-31 Cooperative journals: 《广西植物》
Abstract： In order to gain an understanding of the characteristics of soil inorganic phosphorus and bioavailable phosphorus fractions affected by land use types and hydrothermal conditions in karst ecosystems, the characteristics of soil inorganic phosphorus and bioavailable phosphorus fractions in karst ecosystems were analyzed and compared across croplands, artificial forests, and natural forests in low hydrothermal regions (Nanchuan District in Chongqing, Dushan and Suiyang Counties in Guizhou) and high hydrothermal regions (Huanjiang, Mashan County/Wuming, and Longzhou Counties in Guangxi). One-way analysis of variance, two-factor analysis of variance, and correlation analysis were used to explore the different characteristics and the relationship between soil inorganic phosphorus fractions and bioavailable phosphorus fractions under the influence of land use types and hydrothermal conditions. Redundancy analysis was used to explore the key inorganic phosphorus fractions influencing soil bioavailable phosphorus fractions. The results were as follows: (1) Soil inorganic phosphorus fractions were significantly affected by land use types. The contents of dicalcium phosphate (Ca2-P), octacalcium phosphate (Ca8-P), phosphorus adsorbed on the Al oxides surfaces (Al-P), phosphorus adsorbed on the Fe oxides surfaces (Fe-P), occluded phosphorus (O-P) and decalcium phosphate (Ca10-P) in the soils of croplands were found to be higher than those in the soils of artificial forests and natural forests. Furthermore, the contents of Ca8-P, Fe-P and O-P exhibited the order of croplands > artificial forests > natural forests, whereas the contents of Ca2-P and phosphorus extracted by hydrochloric acid (HCl-P) demonstrated the order of croplands > natural forests > artificial forests. (2) In high hydrothermal regions, Ca10-P and O-P contents of natural forests soils were significantly higher than in low hydrothermal regions, and phosphorus extracted by enzymes (Enzyme-P) contents of artificial and natural forests soils were the opposite. (3) Soil inorganic phosphorus fractions Ca2-P, Ca8-P, Al-P, Fe-P and Ca10-P contents were significantly and positively correlated with bioavailable phosphorus fractions CaCl2-P and HCl-P contents. Redundancy analysis showed that Ca2-P was the key factor affecting the bioavailable phosphorus fractions. The results indicate that land use types and hydrothermal conditions are key fraction influencing the characteristics of soil inorganic phosphorus fractions and bioavailable phosphorus fractions. Increasing the contents of inorganic phosphorus fractions has a positive effect on bioavailable phosphorus fractions. Therefore, consideration should be given to the potential effects of future climate change on the fractions and availability of phosphorus in soil, thereby promoting the restoration of karst ecosystems.
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