Evolutionary Trends Research Articles

The trade of algae for human consumption: The common market competitiveness and impacts of the European Union legislation

The food chain has been confronting diverse limits and challenges. Indeed, the increase in level of environmental pollution, in resource scarcity, in biodiversity loss represents some limits, while guaranteeing the food security of a growing population and develop more sustainable production and consumption systems represents some challenges. In this context, including new foods within the European diet can be a sustainable strategy. With respect to the introduction of foods into the market that do not boast a history of safe consumption within the European Union has prompted regulatory interventions that have aimed to control the level of risk assessment of new products before granting permission for their marketing. This paper aimed in glimpsing the potential effect of this legislation on the trade flow of algae as a novel food, and in assessing the level of self-sufficiency and the comparative advantage of European Union countries. For this purpose, the calculation of specific indices allowed the track of the evolutionary trend of algae for human consumption trade flows, referred to the intra and extra European Union countries. Conclusively, the paper presents an interpretation of the relative trade structure, trade pattern and agri-food competitiveness referred to algae for human consumption while underling the limitation but also the benefit of the legislation intervention in this sector.

Multi-Sensor Platform in Precision Livestock Farming for Air Quality Measurement Based on Open-Source Tools

Monitoring air quality in livestock farming facilities is crucial for ensuring the health and well-being of both animals and workers. As livestock farming can contribute to the emission of various gaseous and particulate pollutants, there is a pressing need for advanced air quality monitoring systems to manage and mitigate these emissions effectively. This study introduces a multi-sensor air quality monitoring system designed specifically for livestock farming environments. Utilizing open-source tools and low-cost sensors, the system can measure multiple air quality parameters simultaneously. The system architecture is based on SOLID principles to ensure robustness, scalability, and ease of maintenance. Understanding a trend of evolution of air quality monitoring from single-parameter measurements to a more holistic approach through the integration of multiple sensors, a multi-sensor platform is proposed in this work. This shift towards multi-sensor systems is driven by the recognition that a comprehensive understanding of air quality requires consideration of diverse pollutants and environmental factors. The aim of this study is to construct a multi-sensor air quality monitoring system with the use of open-source tools and low-cost sensors as a tool for Precision Livestock Farming (PLF). Analysis of the data collected by the multi-sensor device reveals some insights into the environmental conditions in the monitored barn. Time-series and correlation analyses revealed significant interactions between key environmental parameters, such as strong positive correlations between ammonia and hydrogen sulfide, and between total volatile organic compounds and carbon dioxide. These relationships highlight the critical impact of these odorants on air quality, emphasizing the need for effective barn environmental controls to manage these factors.

Hypoflexid function in the “trenchant heel” of carnassial teeth, with comments on talonid evolution

AbstractThe carnassial teeth of Carnivora and Dasyuromorphia are characterized by the enlargement of the carnassial blades and reduction of crushing structures. In some species, the highly carnassialized teeth exhibit a unicuspid talonid with only the hypoconid present (“trenchant heel”). This condition is similar to that seen in the molars of pretribosphenic cladotherians such as Dryolestida, with a single talonid cusp and hypoflexid groove. Tooth wear and reconstruction of the power stroke show that the hypoflexid of the trenchant heel occludes with the paracone of the distal upper antagonist, providing a cutting and guiding function during the power stroke, and maintaining a uniform inclination of the tooth movement up to the point of centric occlusion. In case of the Dasyuromorphia, this occlusal relationship is most pronounced between the distal molars (M4/m4), whereas in the Carnivora it occurs between the upper and lower mesial molars (M1/m1). The occurrence of distal hypoflexid-like grooves is a recurring trend in mammal evolution, before and after the evolution of tribosphenic molars with multicuspid talonid.

Early impact of domestication on aggressiveness, activity, and stress behaviors in zebrafish (Danio rerio) using mirror test and automated videotracking

Fish domestication progresses through five levels: from the initial acclimatization to captivity (Level 1), to the life cycle completion in captivity (Level 4), and even to the implementation of selective breeding programs (Level 5). Domestication leads to phenotypic changes over generations, sometimes from the very first generation. Behavioral traits are among the first to change. However, in fish, potential behavioral changes during early domestication have been little studied. Therefore, we studied potential behavioral changes among early and advanced levels of domestication in a model species, the zebrafish (Danio rerio), using a mirror test experiment, commonly used to assess traits involved in activity, aggressiveness, and stress in this species. We compared these traits between wild zebrafish in captivity (F0; Level 1), the first generation of their captive-born offspring (F1; Level 4), and three laboratory strains (AB, TU, and WIK; Level 5). Each fish was individually filmed and tracked using an automated procedure for 5 min. Nine behavioral traits and one activity-related trait were characterized for each individual based on the movements and positioning of the fish. We applied a principal component analysis (PCA) and tested the significance of potential differences between groups using an analysis of similarities (ANOSIM). We applied an indicator value analysis (IndVal) to determine which traits were most expressed by each group. We detected differences between groups and across domestication levels. More specifically, we highlighted differentiations between different levels of domestication (e.g. between F1, AB, TU, and WIK) as early as the beginning of the domestication process (i.e. F0 vs. F1), but also within the same level of domestication (i.e. AB vs. TU). Based on PCA and IndVal, (i) F0 and F1 tended to show stronger expression of stress-related traits than the other groups, (ii) F0 was more active than others, and (iii) TU was more aggressive than AB. Our results confirmed that domestication can change fish behavior, even in the first generation born in captivity, although these modifications remain limited. In contrast, we did not observe any general trends correlated with domestication levels, given that AB and TU diverged in their aggressiveness levels, and WIK differed only from F1. This result needs to be generalized to other species but also considered for domestication for aquaculture. If future studies confirm that the changes observed at the beginning of the domestication process remain limited and that there is no consistent evolutionary trend across generations in fish, this would highlight the crucial importance of selecting the right species from the outset of domestication. It would also emphasize the need to design selective breeding programs that shape fish stocks with the most desirable characteristics. To our knowledge, this study is one of the few to examine the behavior of wild zebrafish alongside laboratory strains, offering a unique insight into the early stages of domestication.

Spatial Distribution Characteristics of Plant Community and the Identification of Driving Factors in Riparian Zone of the Three-River Headwaters Region, China

The unique geographical and climatic conditions in the Three-River Headwaters Region gave birth to distinctive plant species and vegetation types. To reveal the spatial distribution of plant communities and soil habitats along the riparian zone of the Sanjiangyuan Region and their influencing mechanisms, 14 survey plots were set up （ten from the Yangtze River source, two from the Lancang River source, and two from the Yellow River source）, and the effects of soil nutrient characteristics （especially soil phosphorus morphology）, climate factors, and river topography on plant community characteristics were quantitatively analyzed. The results showed that the plant community composition in the riparian zone of the source of the three rivers was dominated by perennial herbs （72.2%）, followed by annual herbs （20.4%） and shrubs （7.4%）. The dominant plants were Stipa purpurea, Polygonum orbiculatum, Carex parvula, Potentilla anserina, and Gentiana straminea. The average plant coverage, Shannon-Wiener index, and Pielou index were （64.4% ±23.6%）, （1.31 ±0.42）, and （0.84 ±0.08）, respectively. The plant community diversity index was the highest in the Yangtze River source, followed by that in the Lancang River source, and the lowest in the Yellow River source. The soil pH of the riparian zone of the Yangtze River source was significantly higher than that of the Lancang River source, whereas the mean contents of organic matter, total nitrogen, and Fe-Al combined phosphorus were significantly lower than those of the Lancang River source. The calcium and magnesium-combined phosphorus was the main form of phosphorus in riparian soil （63.89%）. Temperature, soil organic phosphorus content, and pH had significant effects on plant composition in the riparian zone of the Three-River Headwaters Region, whereas soil calcium and magnesium-combined phosphorus content had significant effects on plant community diversities. These results may deepen the scientific understanding of the evolution trend and genetic mechanism of plant communities in the riparian zone of the Three-River Headwaters Region.

Isolation and characterization of porcine epidemic diarrhea virus with mutations in the spike gene in China

Porcine epidemic diarrhea (PED) caused by porcine epidemic diarrhea virus (PEDV) has caused enormous economic losses to the global swine industry. Due to frequent mutations in the spike (S) gene of PEDV, commercial vaccines used today are gradually losing their protective efficacy against variants. It's significant to monitor the S gene of PEDV variants and understand its evolutionary trend. In this study, we report four novel PEDV strains isolated from Sichuan, Guangdong and Shanxi Provinces and determined their S gene sequences. Phylogenetic analysis showed that they all belong to GII genotype. Amino acid alignment revealed a unique mutation pattern. We also predicted their three-dimensional structures and continuous B-cell epitopes and compared them to those of the vaccine strain. Our study provides references for understanding the evolution of S gene and antigenic change of S protein, which are of great significance for formulating the prevention and control of PEDV.

Financial well‐being: An integrated framework, operationalization, and future research agenda

AbstractFinancial well‐being occupies a pivotal juncture between money and happiness, serving as fundamental components for favorable individual and organizational outcomes. The exponential growth in literature seeking to delineate its conceptualization, mechanisms, and enablers underscores its significance and implications. However, the varied scholarly contributions have also given rise to persistent discrepancies and a subjective‐objective dichotomy within the field, necessitating a comprehensive review. To address this gap, we conducted a thorough bibliometric analysis employing citation, co‐citation, and co‐occurrence techniques. Our study enriches the theoretical underpinnings by examining its thematic nuances, underlying nomological networks, and evolutionary trends. Specifically, our findings unveil a notable shift toward subjective evaluation shaped by temporal perspectives. Moreover, we discern an increasing influence of psychological variables in shaping individuals' subjective assessments of their financial well‐being, extending beyond traditional cognitive and objective dimensions. Additionally, our analysis underscores the pivotal role of financial socialization, highlighting the impact of social and environmental factors on subjective perceptions. These insights are encapsulated within our proposed operationalization, integrated framework, and future research direction.

Servitization and product service system: A literature review on value creation

In recent years, the concept of servitization has been widely applied in the management of enterprises. However, changing customer demands and competitive pressures of the market have compelled enterprises to seek innovation. Simultaneously, in the context of the Industry 4.0 trend, the rapid development of digital technologies has led to an increasing number of studies on the integration of servitization and digitization. Therefore, this study, based on VOSviewer, Gephi, Scimago Graphica, and Histcite, analyzes the current state and development trends of research on servitization and product service system innovation from the perspective of value creation. Initially, basic statistical characteristics such as the influential author, geographical cooperation, and highly cited papers are presented by collecting relevant data from the Web of Science core collection database. Subsequently, this study explores the research hotspots and evolutionary trends in servitization and product service system innovation through keyword co-occurrence analysis and cluster analysis. Lastly, from a literature analysis perspective, the application of advanced technologies in servitization, digital servitization from an ecosystem perspective, and the innovative use of microservices architecture in product service systems are summarized and forecasted as research directions, providing theoretical guidance for future research in servitization.

Digital economy and the medical and health service supply in China.

The impact of the digital economy on the healthcare sector is becoming increasingly profound. This article focuses on the relationship between the development of China's digital economy and medical and health services supply. Based on panel data from 30 provinces in China from 2012 to 2021, the CRITIC weight method was applied to measure the supply capacity of medical and health services and the level of digital economy development, and the kernel density estimation method and Dagum Gini coefficient method was used to characterize the evolutionary trends and regional differences. Additionally, a two-way fixed-effects model is adopted to investigate the impact of digital economy development on medical and health services supply. The results show that both the supply capacity of healthcare services and the level of digital economy development have been increasing continuously in terms of evolutionary trends. From the perspective of regional differences, compared to the supply level of healthcare services, the regional differences in digital economy development are more significant. The intra-regional differences in medical and health services supply are greater than the inter-regional differences, while the development of the digital economy exhibits the opposite trend. The findings of this paper provide supports for China to enhance the development level of digital economy and improve supply of medical and health service.

Rockburst early-warning method based on time series prediction of multiple acoustic emission parameters

Rockburst early-warning is crucial for ensuring safety in deep underground engineering. Existing methods primarily focus on classifying rockburst grades, making it challenging to provide timely warnings. This paper proposes a novel rockburst early-warning framework based on time series prediction of acoustic emission (AE) parameters. Six AE parameters (rise time, count, duration, amplitude, absolute energy, and peak frequency) were identified as potential indicators for rockburst early-warning based on rockburst tests. A sliding window method was applied to process normalized AE data, calculating statistical parameters of the local duration. An LSTM-based time series prediction model was developed to forecast the future evolution of these AE parameters. This, in turn, enabled the establishment of a comprehensive multi-indicator early-warning system. The Isolation Forest (IF) algorithm, an outlier detection method, was used to determine the warning thresholds for each indicator. The CRITIC weighting method was employed to integrate the six rockburst indicators into a single early-warning coefficient (EC), with EC=100 signifying the warning trigger condition. The results demonstrate that the proposed framework effectively captures the evolution trends of AE parameters, enabling proactive early warnings. This approach addresses the limitations of existing methods, such as reliance on experience for threshold determination, lack of a clear basis for multi-indicator weights, and difficulty in quantifying early-warning trigger conditions. The framework provides a new perspective for rockburst early-warning systems.

Characterization of extreme rainfall changes and response to temperature changes in Guizhou Province, China

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of “high in the south and low in the north, high in the east and low in the west” and “high in the southeast and low in the northwest”, respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change.

Mapping global research landscape and trend of nano-drug delivery system for urological cancers: a bibliometric analysis.

Aim: We conducted a bibliometric analysis to quantitatively study the development pathway, research hotspots and evolutionary trends of nano-drug delivery systems (NDDS) in treating urological tumors.Materials & methods: We used the Web of Science Core Collection to retrieve the literature related to NDDS in the urological tumors up to November 1, 2023. Bibliometric analysis and visualization were conducted using CiteSpace, VOSviewer and R-Bibliometrix. The major aspects of analysis included contributions from different countries/regions, authors' contributions, keywords identification, citation frequencies and overall research trends.Results: We included 3,220 articles. The analysis of annual publication trends revealed significant growth in this field since 2010, which has continued to the present day. The United States and China have far exceeded other countries/regions in the publication volume of papers in this field. The progression of the shell structure of NDDS in the urinary system has gradually transitioned from non-biological materials to biocompatible materials and ultimately to completely biocompatible materials. Mucoadhesive NDDS for intravesical drug delivery is a hotspot and a potential research material for bladder cancer.Conclusion: The field of NDDS in urological tumors has emerged as a research hotspot. Future research should focus on synergistic effects of NDDS with other treatment modalities.

Driving Paths and Evolution Trends of Urban Low-Carbon Transformation: Configuration Analysis Based on Three Batches of Low-Carbon Pilot Cities

In response to global climate challenges, urban low-carbon transformation has become a critical strategy for sustainable development. This study constructs a theoretical model for urban low-carbon transformation using the multi-level perspective framework. We focused on three batches of low-carbon pilot cities in China and employed fuzzy set qualitative comparative analysis to investigate the transformation pathways and impact mechanisms during the periods 2010–2012, 2012–2017, and 2017–2019. The results indicate that none of the six antecedent conditions is necessary for urban low-carbon transformation. Initially, the transformation is primarily driven by a pathway led by low-carbon industries. In the mid-stage, two pathways emerge: one dominated by the combination of low-carbon industries and research and development (R&D) human capital and another led by low-carbon consumption awareness and economic development levels. In the later stage, the influencing factors involve a combination across micro, meso, and macro levels, reflecting an increasingly diversified and intricate configuration. The regional industrial structure consistently plays a dominant role, while awareness of low-carbon consumption has grown over time. This study not only enhances our understanding of the underlying mechanisms but also provides practical policy recommendations for local governments to tailor their strategies for effective low-carbon transformation.

Simulation and prediction of land subsidence in Decheng District under the constraint of InSAR deformation information

Land subsidence, marked by a decline in surface elevation, poses a significant threat to urban infrastructure and safety. Accurate subsidence information and a reliable prediction model are crucial for prevention and control. In this study, we used persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technology to obtain long-term land subsidence data and analyzed subsidence characteristics in Decheng District. By integrating hydrogeological and groundwater data, we developed a three-dimensional groundwater flow and one-dimensional compaction model through numerical simulation. Furthermore, the subsidence data monitored by PS-InSAR were used to further constrain and validate the model. The evolution trend of land subsidence under different groundwater exploitation scenarios was predicted and analyzed. The results showed that from May 2017 to December 2021, the cumulative maximum subsidence in Decheng District reached −173 mm. The subsidence area is mainly concentrated in the northern area, and its subsidence center is near Qiaoyuan Town. According to the Land Subsidence Prevention and Control Plan of Dezhou City, Shandong Province (2018–2025), we set up different groundwater mining scenarios with the goal that the rate of land subsidence in the key prevention and control area is less than 35 mm/yr in 2025.The Fluid-solid coupled model prediction analysis results indicated that a 30% reduction in groundwater exploitation is reasonable.

Evolutionary method of digital twin model for building physics mechanism

ABSTRACT Building digital twin (BDT) realizes real-time monitoring, prediction, and optimization control of the building system through the synchronization between the real world and the virtual platform, and improves the efficiency of building operation and maintenance. However, the changes in physical laws caused by the decline and aging of buildings make it difficult for the BDT models to depict the dynamic evolution mechanism of buildings and improve decision-making, which brings great challenges to the prediction and maintenance of buildings. To this end, an evolutionary method of digital twin model for building physics mechanisms is proposed, which integrates the internet of things (IoT), building information physical model (BIPM), and machine learning algorithms to build a self-evolution framework of digital twins for building physics mechanism, and supports high-precision modeling of BDTs. The advanced prediction (AP) model and autonomous decision-making (ADM) model for building physics mechanisms with self-evolution capability are designed, which support the autonomous correction of model parameters and the dynamic updating of the model driven by real-time data, and the ability to learn optimal control actions through interactive trial and error with the environment. The experimental results based on the settlement prediction and control case of underground engineering show that this evolutionary method can dynamically simulate the future evolution trend of the settlement law of underground engineering, and adjust the physical parameters to the ideal range to guide the evolution of underground engineering in a better direction. Compared with the existing methods, it has better prediction accuracy, interpretability, and generalization performance.

Revisions, new taxa, and venation transformations of the sawfly family Blasticotomidae sensu lato (Hymenoptera: Tenthredinoidea) highlight the evolution of the basal Hymenoptera

Abstract Wing venation pattern is particularly important in the taxonomy and classification of insects, especially for fossil material. There are recognized transformation series that apparently often represent a mainstream in the evolutionary trend of the wing venation of Hymenoptera. One notable instance is the gradual reduction of the subcosta veins from multiple branches to their total absence. Herein, we place four new genera and six new species in the family Blasticotomidae (=Xyelotomidae) of Hymenoptera. They are Xyelocerus abruptus sp. nov., Liberitoma tenella gen et sp. nov., Liberitoma compta sp. nov., Liberitoma incompleta sp. nov., Aduantoma insolita gen. et sp. nov., and Apertoma gen. nov. from the Middle Jurassic of China, and Enspeletoma oligocaenica gen. et sp. nov. from the Upper Oligocene of Germany. The newly discovered species of Liberitoma from China possessed a supernumerary hind branch of vein Sc in its forewing, which has apparently never been recorded before in other hymenopterans, and the unique venation pattern of Aduantoma suggests the possibility of two additional steps of vein Sc transformation before its complete loss. Based on the new findings, Blasticotomidae are proposed to be divided into four subfamilies: Blasticotominae Thomson 1871, Dahurotominae subfam. nov., Pseudoxyelocerinae subfam. nov., and Undatominae subfam. nov.

Spatial evolution and influencing factors of water-town settlements in Southern China: evidence from 942 villages in Zhongshan City

ABSTRACT Zhongshan, a city characterized by its profound historical heritage and distinctive rural civilization, has been consistently influenced by traditional agricultural practices throughout its history. This research conducts an in-depth exploration of Zhongshan’s unique rural spaces, systematically examining the evolutionary trends and determinants of Zhongshan’s water-town settlements across different historical epochs through the application of multidimensional spatial analysis techniques. The results indicate that these settlements exhibited cohesive spatial distribution characteristics across five historical periods. Notably, there was a significant clustering effect during the Ming and Qing dynasties, while Before the Qing dynasty, the spatial distribution of the settlements presented a pattern with multiple core areas coexisting. After the Qing dynasty, the spatial layout of these principal core areas stabilized and gradually diffused to surrounding areas, forming a balanced and continuous distribution pattern. Throughout the study period, the spatial pattern of the water-town settlements exhibited characteristics of five primary core areas and several secondary core areas. Concurrently, the centroid of the water-town settlements consistently shifted southeastward. When examining the intensity of influence on spatial evolution, the study found that socio-economic (q = 0.345) and accessibility factors (q = 0.356) exert a greater impact on the spatial distribution of rural settlements than do natural environmental factors (q = 0.136). However, the interaction between natural environmental factors and socio-economic and accessibility factors provides greater explanatory power than the interactions within natural factors alone. This suggests that in a specific socio-economic context, the impact of the natural environment on water-town settlements is enhanced. Furthermore, multivariate linear regression analysis demonstrates that the rural population, regional economic status, proximity to urban centers, and the distribution of water bodies positively influence the spatial evolution of water-town settlements.

Gaia DR3 reveals the complex dynamical evolution within star clusters

Context. Star clusters, composed of stars born from the same molecular cloud, serve as invaluable natural laboratories for understanding the fundamental processes governing stellar formation and evolution. Aims. This study aims to investigate correlations between the Mean Interdistance ($ \bar{D_{\mathrm{i}}} $), Mean Closest Interdistance ($ \bar{D_{\mathrm{c}}} $) and Median Weighted Central Interdistance ($ \bar{D_{\mathrm{cc}}} $) with the age of star clusters, examining their evolutionary trends and assessing the robustness of these quantities as possible age indicators. Methods. We selected a sample of open clusters in the solar region and with a representative number of members (e.g. well populated and without outliers). The interdistances are derived from the spatial distribution of member stars within a cluster. Their evolution over time allows us to use them as age indicators for star clusters. Results. Our investigation reveals a high-significant correlation between the interdistances and cluster age. Considering the full sample of clusters between 7 and 9 kpc, the relationship is very broad. This is due to uncertainties in parallax, which increase with increasing distance. In particular, we must limit the sample to a maximum distance from the Sun of about 200 pc to avoid artificial effects on cluster shape and on the spatial distribution of their stars along the line of sight. Conclusions. By conservatively restraining the distance to a maximum of ∼200 pc, we have established a relationship between the interdistances and the age of the clusters. In our sample, the relationship is mainly driven by the internal expansion of the clusters and is marginally affected by external perturbative effects. Such relation might enhance our comprehension of cluster dynamics and might be used to derive cluster dynamical ages.

On the origin and evolution of deuterium enrichment in type 1 and 2 chondritic organic solids

Rotationally resonant Deuterium Nuclear Magnetic Resonance spectroscopy (D MAS NMR) was applied to IOM isolated from a CR1 chondrite Grosvenor Mountains (GRO) 95577 and a CM2 chondrite (Murchison). It is shown that in IOM D strongly prefers the aliphatic hydrogen reservoir over the aromatic hydrogen reservoir. For GRO 95577, that has a bulk δD of 3303 ‰ (Alexander et al., 2010), the average δD value of the aromatic reservoir is 1740 ± 128 ‰ and the aliphatic reservoir is 4477 ± 105 ‰, i.e., D/H enrichments of 1.27 and 0.64, respectively, relative to the bulk. For Murchison IOM, that has a bulk δD of 811 ‰ (Alexander et al., 2010), the average δD of the aromatic reservoir is 512 ± 88 ‰ and the aliphatic reservoir is 1033 ± 64 ‰ i.e., D/H enrichments of 1.12 and 0.82, respectively, relative to the bulk. D-H exchange between D-enriched water and a type III kerogen reveals nearly equivalent D up take by both aromatics and aliphatics. Laboratory synthesis of IOM-like material in the presence of D2O reveals a high degree of deuteration with a strong preferential deuteration of the aliphatic hydrogen reservoir indicating that the δD of the water during IOM synthesis is the primary determinant of syn-IOM’s δD. The IOM in GRO 95577 and Murchison (FA and H/C × 100) lie on the molecular evolution line as defined by the IOM of the Tagish Lake clasts and Murchison IOM has experienced more molecular evolution relative to that exhibited by GRO 95577 IOM. A forward prediction derived from the D/H ratios for the aliphatic and aromatic hydrogen reservoirs in Murchison and GRO 95577, relative to their bulk D/H ratios, derived from D MAS NMR, is applied to explain the origin of the Tagish Lake trend of δD vs molecular evolution (H/C × 100). The results of this forward prediction suggest that the Tagish Lake isotopic trend results from a combination of molecular evolution (loss of predominantly aliphatic H and D) and partial D-H exchange with D depleted chondritic water during a short-term hydrothermal alteration event. Such events may be faithfully identified in chondritic organic solids and be a common occurrence, but not necessarily revealed in the mineralogy of type 1 and 2 carbonaceous chondrites.

The Stochastic Evolution Game of Knowledge-Sharing Incentive in Virtual Communities under Intelligent Recommendation Systems

To effectively solve the issue of unsmooth knowledge sharing in virtual communities under intelligent recommendation systems, we analyzed the impact of key factors on the strategy selection and evolution path in different scenarios.Based on the principles of bounded rationality and benefit maximization, we consider the principles of evolutionary game theory and the influence of random interference. A random evolutionary game model is constructed to analyze strategy selection in the process of knowledge sharing incentives between virtual community platforms and users. We obtained the evolutionary equilibrium strategies under different parameter restrictions and analyzed the evolutionary stability of the dynamic game process of knowledge sharing incentives.The research shows that interference from random factors affects both the speed and the trend of strategy evolution in virtual community platforms and users. In order to improve the enthusiasm of users to share, virtual community need to increase the proportion of users with positive feedback, improve the recommendation incentive mechanism, and reduce the user loss coefficient. Based on the above research conclusions, some countermeasures and suggestions for improving the performance of virtual community knowledge sharing under intelligent recommendation systems are proposed, which provides theoretical guidance for knowledge sharing among virtual community members.