Auxiliary Factors Research Articles

An analytical framework based on social-ecological systems for identifying priority areas for ecological restoration in coastal regions

Owing to rapid urbanization, coastal regions worldwide are experiencing immense resource and environmental stress. Ecological restoration is vital for maintaining and sustainably developing coastal regions. This study proposed a method for delineating priority areas for ecological restoration based on the social-ecological systems (SES) theory. First, an analytical model was established based on three dimensions: ecosystem function, social system pressure, and SES evolution, for analyzing the social and natural systems of coastal regions. Second, based on the modes of land–sea interaction relevant to ecological restoration, auxiliary marine factors were incorporated to aid the delineation of priority areas for ecological restoration. A case study was conducted on the Dapeng New District of Shenzhen City to validate our method. The marine areas of the Dapeng New District have significantly poorer ecosystem function than its terrestrial areas because of the natural geography of this area and human activities. A total of 43.4% of marine areas require artificially assisted ecological restoration, and inland areas 1.5 km from the shoreline are significant for ecological conservation and restoration. Additionally, estuaries and artificial shorelines should be the focus of ecological restoration work in the study area. This case study proved the efficacy of our method. The findings will serve as a reference for the planning and implementation of ecological restoration plans in coastal regions.

Phosphorylation of P-stalk proteins defines the ribosomal state for interaction with auxiliary protein factors.

Ribosomal action is facilitated by the orchestrated work of trans-acting factors and ribosomal elements, which are subject to regulatory events, often involving phosphorylation. One such element is the ribosomal P-stalk, which plays a dual function: it activates translational GTPases, which support basic ribosomal functions, and interacts with the Gcn2 kinase, linking the ribosomes to the ISR pathway. We show that P-stalk proteins, which form a pentamer, exist in the cell exclusively in a phosphorylated state at five C-terminal domains (CTDs), ensuring optimal translation (speed and accuracy) and may play a role in the timely regulation of the Gcn2-dependent stress response. Phosphorylation of the CTD induces a structural transition from a collapsed to a coil-like structure, and the CTD gains conformational freedom, allowing specific but transient binding to various protein partners, optimizing the ribosome action. The report reveals a unique feature of the P-stalk proteins, indicating that, unlike most ribosomal proteins, which are regulated by phosphorylation in an on/off manner, the P-stalk proteins exist in a constantly phosphorylated state, which optimizes their interaction with auxiliary factors.

Research on the evaluation method for safety cognitive ability of workers in high-risk construction positions

PurposeSafety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.Design/methodology/approachBased on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.FindingsThe research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.Research limitations/implicationsConsidering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.Practical implicationsThis research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.Originality/valueThis research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

Bayesian inference: more than Bayes’s theorem

Bayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function. But Bayesian inference uses all of probability theory, not just Bayes’s theorem. Many hypotheses of scientific interest are composite hypotheses, with the strength of evidence for the hypothesis dependent on knowledge about auxiliary factors, such as the values of nuisance parameters (e.g., uncertain background rates or calibration factors). Many important capabilities of Bayesian methods arise from use of the law of total probability, which instructs analysts to compute probabilities for composite hypotheses by marginalization over auxiliary factors. This tutorial targets relative newcomers to Bayesian inference, aiming to complement tutorials that focus on Bayes’s theorem and how priors modulate likelihoods. The emphasis here is on marginalization over parameter spaces—both how it is the foundation for important capabilities, and how it may motivate caution when parameter spaces are large. Topics covered include the difference between likelihood and probability, understanding the impact of priors beyond merely shifting the maximum likelihood estimate, and the role of marginalization in accounting for uncertainty in nuisance parameters, systematic error, and model misspecification.

New Strides in Prevention of Malaria during Pregnancy Present Multitudinous Opportunities.

Pregnant women are at a higher risk of developing complications from malaria, a mosquito-borne disease caused by Plasmodium parasites, resulting in considerable maternal and infant morbidity and mortality. Malaria in pregnancy causes unfavorable and life-threatening outcomes for both the mother and fetus not limited to maternal anemia, hypoglycaemia, cerebral malaria, pulmonary edema, and puerperal sepsis. WHO recommends wide-ranging strategies for this detrimental but preventable disease; however, numerous challenges persist in ensuring high uptake of preventive therapies, effective usage of insecticide-treated bed nets, and early initiation and optimal antenatal care coverage for pregnant women. This work distils recent global advances in preventive strategies for malaria in pregnancy. We discuss three mainstay interventions by WHO, viz. intermittent preventive treatment of malaria in pregnancy (IPTp), utilization and outcomes of insecticide-treated bed nets (ITNs), and headways in malaria case management using therapeutic drugs. We cover multitudinous facets of antenatal care, WHO-advised community-based delivery of IPTp (c-IPTp), intermittent screening and treatment for malaria in pregnancy (ISTp), a malaria vaccine for pregnant women, and auxiliary factors that are crucial for improving prevention outcomes. Despite the reduction in malaria globally, malaria in pregnancy remains a prevalent issue in endemic areas, which warrants strengthening of preventative strategies. This work attempts to consolidate pivotal observations of the prevention of malaria during pregnancy by highlighting key advances, priority areas, new opportunities, research gaps, and challenges that need to be addressed to ensure improved outcomes in pregnant women infected with malaria.

Cryo-EM structures of the Spo11 core complex bound to DNA.

DNA double-strand breaks that initiate meiotic recombination are formed by the topoisomerase-relative enzyme Spo11, supported by conserved auxiliary factors. Because high-resolution structural data have not been available, many questions remain about the architecture of Spo11 and its partners and how they engage with DNA. We report cryo-electron microscopy structures at up to 3.3-Å resolution of DNA-bound core complexes of Saccharomyces cerevisiae Spo11 with Rec102, Rec104 and Ski8. In these structures, monomeric core complexes make extensive contacts with the DNA backbone and with the recessed 3'-OH and first 5' overhanging nucleotide, establishing the molecular determinants of DNA end-binding specificity and providing insight into DNA cleavage preferences in vivo. The structures of individual subunits and their interfaces, supported by functional data in yeast, provide insight into the role of metal ions in DNA binding and uncover unexpected structural variation in homologs of the Top6BL component of the core complex.

Insights into Mtg3-mitochondrial ribosome association in Saccharomyces cerevisiae

Ribosome biogenesis is a highly regulated multistep process aided by energy-consuming auxiliary factors. GTPases form the largest class of auxiliary factors used by bacterial, cytosolic, and mitochondrial ribosomes for their maturation. Mtg3, a circularly permuted YqeH family of GTPase, is implicated in the mitoribosome small subunit biogenesis. However, its precise mechanistic role has yet to be characterized. Mtg3 is likely to bind precursor mitoribosome molecules during subunit maturation in vivo. However, this interaction has yet to be observed with mitoribosomes biochemically. In this study, we delineate the specific conditions necessary for preserving the association of Mtg3 with mitoribosomes on a sucrose density gradient. We show that the C-terminal domain of Mtg3 is required for robust binding to the mitoribosome. Furthermore, point mutants likely to abrogate GTP/GDP binding and GTPase activity compromise protein function in vivo. Surprisingly, the association with the mitoribosome was not compromised in mutants likely to be deficient for nucleotide binding/hydrolysis. Thus, our finding supports a model wherein Mtg3 binds to a precursor mitoribosome through its C-terminus to facilitate a conformational change or validate a folding intermediate driven by the GTP/GDP binding and hydrolysis cycle.

Assessing the Accuracy of Eddy‐Covariance Measurement at Different Source Emission Scenarios

AbstractThe eddy‐covariance (EC) method assumes a homogeneous underlying surface. However, recent studies increasingly examining on EC measurements across diverse surfaces, raising concerns about measurement precision and accuracy. This study evaluates the impacts of altering the emission height and rate on the EC measurements through utilizing an artificial source emission system. The results demonstrated a significant impact of changes in the emission height and rate on the EC measurements. Higher emission height may lead to the underestimation of the measured EC fluxes, attributed to the variations in the footprint area and turbulent transport. Traditional data quality control methods may discard effective EC data during sudden changes in the emission rate. Therefore, to secure effective data and accurately observe emissions, it was practical to analyze the auxiliary factors, such as environmental factors, such as vapor pressure deficit (VPD). An unresolved issue would persist with the correction of the EC method for accurately capturing the actual emission signals when there was a sudden increase in the data range or deviation. Furthermore, comparing the footprint model estimations with the actual emissions demonstrated the necessity of footprint analyses, offering a valuable reference for the data calibration when the uncertainties arose owing to inhomogeneous underlying surfaces. Although EC fluxes across the three averaging periods indicated no significant differences, the footprint model suggested that 15‐min interval was the optimal. Further validation experiments are required for the EC measurements in locations with complex source conditions to enhance our understanding of land‐atmosphere flux exchange.

Untraded inter‐dependencies as auxiliary production factors for informal artisans in urban industrial clusters: An empirical study in Kumasi, Ghana

AbstractThe concept and influence of untraded inter‐dependencies are under‐explored in the industrial cluster and informal economy literature. In this paper, we attempt to bridge this gap by extending the conventional Cobb‐Douglas production function to operationalising and testing the moderating effects of two forms of untraded inter‐dependencies in informal production. Based on the diffusion theory, we argue that knowledge‐sharing would favour informal production, as opposed to tool‐sharing. Using quantitative methods, 334 informal artisans were randomly sampled from three clusters in the Kumasi Metropolis of Ghana and analysed data obtained with moderating models and simple slopes plots. The tested models and fuzzy set configurations confirmed that knowledge‐sharing, but not tool‐sharing, has significant interaction effects on informal production. The optimal model derived would be one in which capital interacts with incremental knowledge‐sharing at the existing level of tool‐sharing among the artisans. This paper serves as an extension of new economic geography with an additional factor of untraded inter‐dependencies. As part of post‐COVID restoration and enhancement of informal production processes, we recommend city officials to deliberately plan and space clustered enterprises that enable the observed rates of interactions between production factors and untraded inter‐dependencies.

More Accurately Estimating Aboveground Biomass in Tropical Forests With Complex Forest Structures and Regions of High‐Aboveground Biomass

AbstractAccurately estimating aboveground biomass (AGB) in tropical forests is vital for managing the threats posed by deforestation, degradation, and climate change. However, challenges persist in accurately estimating AGB in high AGB regions. This study aims to accurately estimate the AGB of regions with high AGB by using spatial statistical analyses based on AGB estimates made by machine‐learning fusion of multisource data. We hypothesize that incorporating dominant auxiliary factors in the analysis increases the estimation accuracy. This study focuses on tropical forests located in Longyan, Fujian Province, China, covering an area of 19,028 km2. Multisource data are used, including airborne laser scanning, the Shuttle Radar Topography Mission digital elevation model, the Landsat Operational Land Imager, and the National Forest Inventory. Based on GeogDetector's spatial covariance matrix and the spatial similarity principle, we identify key auxiliary factors (dominant tree species, canopy closure, and herbaceous cover) and investigated how auxiliary variables can improve estimation accuracy. Empirical Bayesian kriging regression prediction introduces the main auxiliary factors to refine AGB estimates. These refinements significantly enhance the accuracy of AGB estimates, particularly for high AGB, resulting in a 0.1 increase in R2, a 7.0% reduction in root mean square error, a 13.5% reduction in mean square error, and a 6.6% reduction in mean absolute error when compared with the AGB estimates obtained by using machine learning to fuse multisource data. Thus, incorporating spatial statistical analysis into the integration of multisource data and machine learning for AGB estimation can enhance the accuracy of high‐AGB estimates in intricate forest structures, resulting in precise AGB maps.

The role of E2F2 in cancer progression and its value as a therapeutic target.

The E2F family of transcription factors plays a crucial role in the regulation of cell cycle progression and cell proliferation. Accumulative evidence indicates that aberrant expression or activation of E2F2 is a common phenomenon in malignances. E2F2 has emerged as a key player in the development and progression of various types of tumors. A wealth of research has substantiated that E2F2 could contribute to the enhancement of tumor cell proliferation, angiogenesis, and invasiveness. Moreover, E2F2 exerts its influence on a myriad of cellular processes by engaging with a spectrum of auxiliary factors and downstream targets, including apoptosis and DNA repair. The dysregulation of E2F2 in the context of carcinogenesis may be attributable to a multitude of mechanisms, which encompass modifications in upstream regulatory elements or epigenetic alterations. This review explores the function of E2F2 in cancer progression and both established and emerging therapeutic strategies aiming at targeting this oncogenic pathway, while also providing a strong basis for further research on the biological function and clinical applications of E2F2.

Plasmid targeting and destruction by the DdmDE bacterial defence system.

Although eukaryotic Argonautes have a pivotal role in post-transcriptional gene regulation through nucleic acid cleavage, some short prokaryotic Argonaute variants (pAgos) rely on auxiliary nuclease factors for efficient foreign DNA degradation1. Here we reveal the activation pathway of the DNA defence module DdmDE system, which rapidly eliminates small, multicopy plasmids from the Vibrio cholerae seventh pandemic strain (7PET)2. Through a combination of cryo-electron microscopy, biochemistry and in vivo plasmid clearance assays, we demonstrate that DdmE is a catalytically inactive, DNA-guided, DNA-targeting pAgo with a distinctive insertion domain. We observe thatthe helicase-nuclease DdmD transitions from an autoinhibited, dimeric complex to amonomeric state upon loading of single-stranded DNA targets. Furthermore, the complete structure of the DdmDE-guide-target handover complex provides a comprehensive view into how DNA recognition triggers processive plasmid destruction. Our work establishes a mechanistic foundation for how pAgos utilize ancillary factors to achieve plasmid clearance, and provides insights into anti-plasmid immunity in bacteria.

Identifying human pre-mRNA cleavage and polyadenylation factors by genome-wide CRISPR screens using a dual fluorescence readthrough reporter.

Messenger RNA precursors (pre-mRNA) generally undergo 3' end processing by cleavage and polyadenylation (CPA), which is specified by a polyadenylation site (PAS) and adjacent RNA sequences and regulated by a large variety of core and auxiliary CPA factors. To date, most of the human CPA factors have been discovered through biochemical and proteomic studies. However, genetic identification of the human CPA factors has been hampered by the lack of a reliable genome-wide screening method. We describe here a dual fluorescence readthrough reporter system with a PAS inserted between two fluorescent reporters. This system enables measurement of the efficiency of 3' end processing in living cells. Using this system in combination with a human genome-wide CRISPR/Cas9 library, we conducted a screen for CPA factors. The screens identified most components of the known core CPA complexes and other known CPA factors. The screens also identified CCNK/CDK12 as a potential core CPA factor, and RPRD1B as a CPA factor that binds RNA and regulates the release of RNA polymerase II at the 3' ends of genes. Thus, this dual fluorescence reporter coupled with CRISPR/Cas9 screens reliably identifies bona fide CPA factors and provides a platform for investigating the requirements for CPA in various contexts.

Simultaneous forecasting of wind speed for multiple stations based on attribute-augmented spatiotemporal graph convolutional network and tree-structured parzen estimator

The global increase in energy demand and environmental concerns have made the development of wind energy increasingly important. Accurate wind speed prediction is crucial for maximizing the benefits of wind energy. In order to further improve the accuracy of multi-site wind speed prediction, this study adopts an evolutionary algorithm-based deep learning model that fully considers the spatiotemporal relationships among multiple station's wind speed data. Firstly, the mutual information (MI) method is used to select variables with stronger correlations to wind speed as auxiliary input factors. Then, an improved version of Attribute-Augmented Spatiotemporal Graph Convolutional Network (IASTGCN) is employed to process data from multiple stations, taking into account both temporal and spatial factors. Additionally, an MI-based wind speed data relationship matrix between multiple stations is calculated to replace the original distance relationship matrix in the model, enabling the model to better capture and utilize the relationships between stations. Next, the Tree-structured Parzen Estimator (TPE) is used to optimize the hyperparameters of the model. This ultimately achieves multi-site multi-step wind speed prediction. Experimental results demonstrate that the proposed model outperforms baseline models and models that only consider either temporal or spatial factors in various scenarios, exhibiting better predictive performance.

Understanding the social-emotional components of our "number sense": insights from a novel non-symbolic numerical comparison task.

A large body of work has identified a core sense of number supported by the Approximate Number System (ANS) that is present in infancy and across species. Although it is commonly assumed that the ANS directly processes perceptual input and is relatively independent from affective factors, some evidence points at a correlation between ANS performance and math anxiety. However, the evidence is mixed. We tested whether giving participants active control in completing a numerical task would change the relationship between math anxiety on performance. Adult participants (N = 103) completed a novel four-alternative-forced-choice non-symbolic numerical comparison task. In a repeated-measures design, participants either passively viewed different dot arrays or actively chose to view each array (i.e., active information-seeking) before deciding on the largest quantity. Participants also provided confidence judgments during the passive version of the task. We replicated the ratio-dependent signature in participants' accuracy in both the passive and active versions of the task using this novel paradigm, as well as in trial-level confidence judgments and information-seeking behavior. Participants' self-reported math anxiety significantly correlated with their accuracy on the passive version of the task. Critically, the correlation disappeared in the active version of the task. Gender also emerged as a predictor of confidence judgments and a moderator of the effect of task on overall accuracy and the effect of active information seeking on accuracy in the active version of the task. Exploratory analysis of estimated Weber Fraction suggests that these results may be driven by auxiliary factors instead of changes in ANS acuity. These findings have implications for understanding the relationship between math anxiety and performance on numerical tasks.

Impact of Auxiliary Features on Retention of Short Dental Crowns: An In-Vitro Analysis of Box and Groove Preparations.

BACKGROUND Several auxiliary features have been proposed to achieve sustainable retention for short-prepared dental crowns; however, achieving retention is challenging. This study aimed to assess the impact of increased total occlusal convergence and auxiliary preparation factors like box and groove on the retention form of short tooth preparations. MATERIAL AND METHODS Eighty resin machine-milled dies with a height of 3 mm and a deep chamfer margin of 1 mm were prepared to mimic the short-prepared molar. Initially, 2 teeth were prepared following the guidelines, and the total occlusal convergence was kept at 10° and 20°, respectively. Auxiliary features such as the proximal box and buccal groove were prepared on separate 20° dies. Eighty dies were prepared with 10 samples each for 10°, 20°, 20° with proximal box and 20° with buccal groove for zirconia (n=40) and metal crowns (n=40). Cementation was done with glass ionomer luting cement, and a pull-off test was conducted. Data were analyzed using one-way analysis of variance and post hoc fisher least significant difference test (P<0.05). RESULTS The highest mean was observed in the proximal box group with the metal crown (14.59), and the lowest in the group with 20° zirconia crowns (9.12). Within groups, the highest retentive values were found for the 20° taper with proximal box preparation; the lowest was for the 20° taper group. CONCLUSIONS Within the study limitations, it could be concluded that incorporating a proximal box or buccal groove in short tooth preparations with an increased total occlusal convergence improved retentive values.

Study of influence of the auxiliary factors onto characteristics of elastic-plastic deformation in the stress concentrator of the beam-wall with broken edges

The thin-walled steel beam-wall with broken edges is being investigated, which is a part of many structures. The wall of this beam consists of two prismatic parts with a linear transition from a smaller to a larger wall height, together forming an angular upper edge with the edges of the prismatic parts. The lower linear edge of the wall is attached to the sheathing.The beam-wall is subjected to static and cyclic loads, under which elastic-plastic deformations strains may occur at in the stress concentrator. This leads to failure of static strength and growth of fatigue cracks. The factors influencing the parameters of elastic-plastic deformation at in the stress concentrator of this beam are practically unstudied. The article under discussion presents the results of studying the influence of the beam-wall thickness and load vector balancing on the values of static and cyclic ranges of elastic-plastic deformations strains at in the stress concentrator. It has had been found that load vector balancing significantly improves the results of elastic-plastic deformations strains under single static loading and allows for the use of a larger load increment to achieve the same results as when no balancing is applied. Applying load vector balancing stabilizes the cyclic deformation loop practically from the first cycle. If balancing is absent, stabilization occurs only from the third cycle. Unlike static ones, the values of cyclic ranges do not depend on the application or non-application of balancing and remain practically stable with fixed geometric parameters and loading. Gradual reduction in the thickness of the beam-wall causes an increase in the range (static and cyclic) of elastic-plastic deformations strains at in the stress concentrator. The obtained results will shorten the time required for planning serial calculations of elastic-plastic deformation of a the beam-wall with edge break broken edges to develop appropriate design techniques.

Replication stress response in fission yeast differentially depends on maintaining proper levels of Srs2 helicase and Rrp1, Rrp2 DNA translocases.

Homologous recombination is a key process that governs the stability of eukaryotic genomes during DNA replication and repair. Multiple auxiliary factors regulate the choice of homologous recombination pathway in response to different types of replication stress. Using Schizosaccharomyces pombe we have previously suggested the role of DNA translocases Rrp1 and Rrp2, together with Srs2 helicase, in the common synthesis-dependent strand annealing sub-pathway of homologous recombination. Here we show that all three proteins are important for completion of replication after hydroxyurea exposure and provide data comparing the effect of overproduction of Srs2 with Rrp1 and Rrp2. We demonstrate that Srs2 localises to rDNA region and is required for proper replication of rDNA arrays. Upregulation of Srs2 protein levels leads to enhanced replication stress, chromosome instability and viability loss, as previously reported for Rrp1 and Rrp2. Interestingly, our data suggests that dysregulation of Srs2, Rrp1 and Rrp2 protein levels differentially affects checkpoint response: overproduction of Srs2 activates simultaneously DNA damage and replication stress response checkpoints, while cells overproducing Rrp1 mainly launch DNA damage checkpoint. On the other hand, upregulation of Rrp2 primarily leads to replication stress response checkpoint activation. Overall, we propose that Srs2, Rrp1 and Rrp2 have important and at least partially independent functions in the maintenance of distinct difficult to replicate regions of the genome.

The Necessity and Feasibility of Usage-Based Insurance for New Energy Vehicles in China

Aims: With the continuous development and growth of China's new energy automobile market, new automobile owners desire exclusive auto insurance. However, most insurance companies use traditional automobile commercial auto insurance to cover them. Under this pricing model, there is little overall difference in premiums, regardless of whether the driver's driving behavior is good or not. This paper wants to implement usage-based insurance (UBI) in China because it can add more auxiliary pricing factors, adjust according to the driver's driving behavior changes, and make auto insurance pricing more scientific and fair.&#x0D; Study Design: This paper employs the literature review and market research methods to analyze the current product supply and consumer demand in the Chinese auto insurance market. Firstly, introduce the current situation of the development of the new energy automobile insurance market in China and its problems. Then, discuss the necessity and feasibility of developing UBI auto insurance for new energy vehicles in China. Finally, based on the reality of China's new energy vehicle UBI auto insurance gives some programs.&#x0D; Conclusion: This paper finds that from the perspective of insurance companies, consumers, and the social level, UBI auto insurance for new energy automobiles is necessary, and it is also the direction of future auto insurance reform and development. Subsequently, combined with China's current relevant policies and technologies, it is concluded that the development of UBI auto insurance for new energy vehicles in China is feasible.

(Digital Presentation) Dynamic Thermal Detection of Water Electrolyzer with Dual-Layer Characteristic Temperature Based on IR

As the prevalence of water electrolysis systems continues to expand, increased attention has been placed on the dynamic thermal detection of the electrolyzer. Presently, the scope of dynamic thermal detection for water electrolysis systems is limited to solely the temperatures at the inlet and outlet. This study propounds a novel dual-layer characteristics temperature (DLCT) model for the purpose of water electrolyzer temperature monitoring. The DLCT model addresses two significant issues of the dynamic thermal detection of the WEE: characteristic temperature extraction difficulty and signal perturbation caused by auxiliary factors. The first layer of multi-gaussian distribution (MGD) regression in the DLCT model quantifies the sectional temperature of the electrolyzer surface and produces numerous potential characteristic temperatures (CT). These temperatures are subsequently assigned to each section and are then conveyed to the second layer of linear regression, which provides an incisive quantized temperature variation pattern for the electrolyzer surface temperature distribution. Importantly, the DLCT model requires no supplementary modifications to the water electrolysis system or the installation of temperature sensors within or on the surface. By employing the DLCT model during dynamic operation, the ability to monitor the temperature of the electrolyzer comprehensively is improved, the temperature distribution of the electrolyzer can be quantized and richer insights regarding the surface temperature distribution can be gained, promoting better thermal uniformity, as well as pin-pointing the potential hot spot. Hence this method can also be used for structure design to produce better uniformity. The dynamic temperature detection results under different operating conditions are analyzed, and it can be concluded that the operating parameters, especially the lye circulation flow, can greatly influence the temperature distribution uniformity of the electrolyzer significantly. In conclusion, the DLCT model effectively handles the two primary challenges in dynamic thermal detection of water electrolysis systems by providing global and sectional characteristic temperature readings, enabling electrolyzer to be monitored holistically. So that future improvement regarding both structural and operational optimization can be conducted in improving the thermal uniformity. Figure 1