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Adolescent vision protection has always been a focus of social concern. With the rapid development of modern technology and changes in social lifestyles, adolescents are generally facing risks to their visual health. This paper explores the social service model of youth vision protection through a review of existing literature and questionnaire analysis. Firstly this study aims to analyze and explore the current situation of prevention and control of youth and adolescent vision and the impact of social service models on it through theoretical studies of literature, with the aim of establishing a more complete vision protection system and improving the sustainability and effectiveness of social services for adolescent vision protection. In addition, this paper introduces the current social service model of youth vision protection, including services at school, family and community levels, and discusses the home-school-community linkage model and its construction method, and finally puts forward suggestions for the future social service model of youth vision protection. After the investigation and research, we found that youth vision protection is a complex social issue that requires the joint efforts of the whole society. Through social service models at different levels, comprehensive vision protection services can be provided to adolescents to promote their healthy growth. This study has some reference value for improving the quality of social services for vision protection and enhancing the intervention effects on adolescent vision protection.

Deep learning is the key development trend of news recommendation technology, which has been thoroughly studied by most researchers. In today's social, news recommendation has become a very essential way for people to acquire news. The fundamental idea and procedure of news modeling are covered in this paper's main body, and one of our research interests is how to leverage convolutional neural networks to create news recommendation technology. We also looked at the news recommendation evaluation index, which looks at things like satisfaction, accuracy, diversity, and innovation. Additionally, this paper analyses numerous traditional algorithms and contrast the benefits and drawbacks of each. We also outlined a number of the challenges that the current study has faced. To contribute to this research, we looked into the expected future evolution of news recommendation technology.

Mean-reversion theory predicts that historical returns and asset price volatility will eventually return to the long-run mean or average level of the entire dataset. The mean-reversion strategy applies the fundamental idea of selling high and attracting low to stock market investment. Researchers studying the international exchange market have shown that foreign exchange rates display momentum and mean reversion behavior. This study aims to assess the effectiveness of the mean-reversion approach on exchange rates and improve it. Using historical data, the author assessed the mean-reversion method's impact on the exchange rate. According to the study, the method offers a risk-to-reward ratio that is conservative. The clear disadvantage is that for most of the exchange rate, mean-reversion methods yield lesser profits. Furthermore, the return is significantly influenced by the mean-reversion lookback period. Quantitatively, exchange rates with significant volatility and variation often outperform when using the mean-reversion approach. Overall, these results shed light on guiding further exploration of mean-revision strategy.

The land cover of the Sanjiang Plain has changed dramatically since the 1950s. Although previous studies have analysed its spatiotemporal dynamics at long time intervals, a near real-time and accurate representation of the interannual evolution of cropping patterns in this region is of far-reaching importance for rationally allocating agricultural resources and ensuring food security. Based on the 30 m and 10 m land cover datasets in 2015 and 2017–2019, the current study used Landsat-8 satellite data in 2014, 2016 and 2020 to identify paddy rice and dryland crops using a decision tree classification approach and constructed the annual cropland datasets of the Sanjiang Plain from 2014 to 2020. The results show that the overall classification accuracies of crop datasets exceeded 95%, and the Kappa coefficients were higher than 0.92. The average annual accuracies of users and producers were 93% and 94% for rice fields and 97% and 95% for dryland crops, respectively. During the 7 years, the total area of paddy fields and dryland crops decreased by 5% and 8%. However, with minor positive and negative variation between years. 24.2% of paddy rice and 42% of dryland crops has been cultivated under 4 years. The centres of gravity for both crops mainly aggregated in the central counties with the migration direction and magnitude varying interannually. The current study emphasizes the importance of establishing annual high-resolution crop datasets to track the detailed spatio-temporal trajectories of cropping patterns that are essential to support sustainable cropland management and agricultural development.

Large-scale distributed training mainly consists of sub-model parallel training and parameter synchronization. With the expansion of training workers, the efficiency of parameter synchronization will be affected. To tackle this problem, we first propose 2D-TGA, a grouping AllReduce method based on the two-dimensional torus topology. This method synchronizes the model parameters by grouping and makes full use of bandwidth. Secondly, we propose a distributed algorithm, 2D-TGA-ADMM, which combines the 2D-TGA with the alternating direction method of multipliers (ADMM). It focuses on sub-model training and reduces the wait time among workers in the synchronization process. Finally, experimental results on the Tianhe-2 supercomputing platform show that compared with the $${\mathtt {MPI\_Allreduce}}$$ MPI _ Allreduce , the 2D-TGA could shorten the synchronization wait time by $$33\%$$ 33 % .

Objective. This study is aimed at exploring the molecular mechanism of Shufeiya recipe in the treatment of pulmonary hypertension (PH) using network pharmacology and molecular docking analysis. Methods. Active components and their target proteins in the recipe were screened using the TCMSP database. PH-related core proteins were screened using GeneCards, STRING database, and Cytoscape-v3.8.2. Common proteins were obtained by intersection of the target proteins of these recipe active components and pH-related core proteins. Rx64 4.0.2 software was used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the common proteins to obtain pathway-enriched proteins, and then core enriched proteins were further screened. We analyzed the relationship between the active components and pathway-enriched proteins using Cytoscape-v3.8.2. AutoDock Vina was used to dock their core proteins into the components. Results. Shufeiya recipe contained 67 active components. 61 common proteins of the target proteins of the active components and PH-related core proteins were obtained. The treatment involved both functional and pathway regulations. The core pathway-enriched proteins were prostaglandin G/H synthase 2 (PTGS2), epidermal growth factor receptor (EGFR), and RAC-alpha serine/threonine-protein kinase (AKT1), and their binding energies to the corresponding components were all less than -5 kJ•mol-1. Conclusion. It was found that the main mechanism might be the active components acting on the core pathway-enriched proteins to regulate related signaling pathways, thereby playing roles in anticoagulation, vasodilation, anti-PASMC proliferation, promotion of PAECs apoptosis, inhibition of oxidative stress, and anti-inflammatory effects.

The aerodynamic performances of aircraft change due to the ground effect for flights near the ground. The air cushion generated near the ground will change the development of the aircraft wake vortex. Researchers have compared several different ground boundary conditions with two-dimensional airfoils, while three-dimensional cases have not been studied specifically. In this study, the effects of stationary and moving wall boundary conditions on the aircraft aerodynamic characteristics and wake development were numerically investigated in three dimensions. The results showed that the stationary wall overestimated the viscous effect of the ground, resulting in a reduction of the wingtip vortex (WTV) vorticity magnitude. The difference appeared at $ x\, = \,7b $ (wingspan of the aircraft) where the secondary vortex was induced by the wingtip and horizontal tail vortex (HTV).

The fast growth of Moso bamboo (Phyllostachys edulis) shoots is caused by the rapid elongation of each internode. However, the key underlying cellular processes and epigenetic mechanisms remain largely unexplored. We used microscopy and multi-omics approaches to investigate two regions (bottom and middle) of the 18th internode from shoots of two different heights (2 and 4 m). We observed that internode cells become longer, and that lignin biosynthesis and glycosyltransferase family 43 (GT43) genes are substantially upregulated with shoot height. Nanopore direct RNA sequencing (DRS) revealed a higher N6-methyladenine (m6A) modification rate in 2-m shoots than in 4-m shoots. In addition, different specific m6A modification sites were enriched at different growth stages. Global DNA methylation profiling indicated that DNA methylation levels are higher in 4-m shoots than in 2-m shoots. We also detected shorter poly(A) tail lengths (PALs) in 4-m shoots compared with 2-m shoots. Genes showing differential PAL were mainly enriched in the functional terms of protein translation and vesicle fusion. An association analysis between PALs and DNA methylation strongly suggested that gene body CG methylation levels are positively associated with PAL. This study provides valuable information to better understand post-transcriptional regulations responsible for fast-growing shoots in Moso bamboo.

Diabetic kidney disease (DKD) is the most common complication of type 2 diabetes mellitus (T2DM), and its pathogenesis is not yet fully understood and lacks noninvasive and effective diagnostic biomarkers. In this study, we performed urine metabolomics to identify biomarkers for DKD and to clarify the potential mechanisms associated with disease progression.We applied a liquid chromatography-mass spectrometry-based metabolomics method combined with bioinformatics analysis to investigate the urine metabolism characteristics of 79 participants, including healthy subjects (n = 20), T2DM patients (n = 20), 39 DKD patients that included 19 DKD with microalbuminuria (DKD + micro) and 20 DKD with macroalbuminuria (DKD + macro).Seventeen metabolites were identified between T2DM and DKD that were involved in amino acid, purine, nucleotide and primarily bile acid metabolism. Ultimately, a combined model consisting of 2 metabolites (tyramine and phenylalanylproline) was established, which had optimal diagnostic performance (area under the curve (AUC) = 0.94). We also identified 19 metabolites that were co-expressed within the DKD groups and 41 metabolites specifically expressed in the DKD + macro group. Ingenuity pathway analysis revealed three interaction networks of these 60 metabolites, involving the sirtuin signaling pathway and ferroptosis signaling pathway, as well as the downregulation of organic anion transporter 1, which may be important mechanisms that mediate the progression of DKD.This work reveals the metabolic alterations in T2DM and DKD, constructs a combined model to distinguish them and delivers a novel strategy for studying the underlying mechanism and treatment of DKD.

Journal of traffic and transportation engineering 9(5), 880-891 (2022). doi:10.1016/j.jtte.2021.02.007, Published by Elsevier Science Direct, Beijing [u.a.]

Integrated photonics has profoundly affected a wide range of technologies underpinning modern society1–4. The ability to fabricate a complete optical system on a chip offers unrivalled scalability, weight, cost and power efficiency5,6. Over the last decade, the progression from pure III–V materials platforms to silicon photonics has significantly broadened the scope of integrated photonics, by combining integrated lasers with the high-volume, advanced fabrication capabilities of the commercial electronics industry7,8. Yet, despite remarkable manufacturing advantages, reliance on silicon-based waveguides currently limits the spectral window available to photonic integrated circuits (PICs). Here, we present a new generation of integrated photonics by directly uniting III–V materials with silicon nitride waveguides on Si wafers. Using this technology, we present a fully integrated PIC at photon energies greater than the bandgap of silicon, demonstrating essential photonic building blocks, including lasers, amplifiers, photodetectors, modulators and passives, all operating at submicrometre wavelengths. Using this platform, we achieve unprecedented coherence and tunability in an integrated laser at short wavelength. Furthermore, by making use of this higher photon energy, we demonstrate superb high-temperature performance and kHz-level fundamental linewidths at elevated temperatures. Given the many potential applications at short wavelengths, the success of this integration strategy unlocks a broad range of new integrated photonics applications.

Wingtip vortex is the initial phase of aircraft wake flow that jeopardizes flight safety. Previous studies have focused on the effect of incidence angle on tip vortex flow; thus, investigations on tip vortex in the roll-up stage under crosswind conditions are limited. In the present study, two NACA0012 wings with different tip shapes (round and square) were numerically analyzed to explore the effects of wingtip configurations on tip vortex. In addition, the effects of crosswinds on wingtip vortex evolution were also investigated. It was found that sharp edges of the square wingtip generated a multi-vortex system, resulting in a larger turbulent wake vortex core radius. The lift and vortex strength of the square wingtip were 23% higher and only 12% stronger than those of the round wingtip, respectively. Furthermore, crosswinds changed both the pressure distribution and the vortex structure. Crosswinds made the flow field unstable; hence, upwind lower edge vortices of the square wingtip burst earlier and merged faster. Consequently, the tightness of the upwind vortex of the square wingtip increased, and the corresponding vortex strength was enhanced. The downwind vortex of the square wingtip was weakened by 2.7% under a crosswind velocity of 4 m/s, whereas the downwind tip vortex of the round wingtip was strengthened under the same conditions.

Soybean protein adhesive is loved by the society because of its low price, simple preparation, non-toxicity to the environment and easy decomposition. However, the soybean protein adhesive itself is easy to crack when exposed to water, the viscosity is insufficient, and there are many changes in individual users. This research will describe several methods of modifying soy protein to enhance various properties of soy protein adhesives. The first method is heat treatment, which folds the molecules of the soy protein adhesive to strengthen it. The second is a cross-linking treatment that allows soy protein to form a network with other agents to enhance its structure through chemical bonds. The third is graft copolymerization, where other agents are grafted onto the soy protein adhesive to give it some good properties. The fourth is blending, where the soy protein adhesive is mixed with other adhesives so that the new homogeneous mixture has the properties of both adhesives. And with the development of these researches, application of the modified soybean protein adhesives is further introduced.

Background and purposeC-C motif chemokine ligand 17 (CCL17) presents an important role in immune regulation, which is critical in the pathophysiology of brain injury after subarachnoid haemorrhage (SAH). There is rare evidence to illustrate the function of CCL17 towards SAH. In this study, we try to reveal the therapeutic effects of CCL17 and its underlying mechanism in rat SAH model.MethodsSAH rat models were assigned to receive recombinant CCL17 (rCCL17) or phosphate buffer saline (PBS). AZD2098 and JR-AB2-011 were applied to investigate the C-C motif chemokine receptor 4 (CCR4)/mammalian target of rapamycin complex 2 (mTORC2) axis in CCL17-mediated neuroprotection. To elucidate the underlying mechanism, the in vitro kinase assay was performed in primary microglia. Microglial-specific Rictor knockdown was administered via intracerebroventricular injection of adenovirus-associated virus. Brain water content, short-term neurobehavioural evaluation, western blot analysis, quantitative RT-PCR and histological staining were performed.ResultsThe expression of CCL17 was increased and secreted from neurons after oxyhaemoglobin stimulation. Exogenous rCCL17 significantly alleviated neuronal apoptosis, and alleviated short-term neurofunction after SAH in rats. In addition, rCCL17 increased M2-like polarisation of microglia in rats post-SAH and in primary microglia culture. The neuroprotection of rCCL17 was abolished via inhibition of either CCR4 or mTORC2.ConclusionCCL17 activated the CCR4/mTORC2 axis in microglia, which can alleviate SAH-induced neurological deficits by promoting M2-like polarisation of microglia.

Nuclear magnetic resonance (NMR) relaxometry provides insight into the pore radius distribution (PRD) of rocks. Several permeability (k) of prediction models are based on the knowledge of the PRD. The Schlumberger-Doll Research (SDR) equation relates the weighted geometric mean of the transverse relaxation time ([Formula: see text]) and porosity to k. In the common form of SDR equation, porosity is raised to the fourth power. This exponent is not in agreement with theoretical models of permeability prediction. Modified versions of the SDR equation have been tested with varying exponents for porosity and other characteristic relaxation times or pore radii determined from NMR relaxometry. We have evaluated the quality of various k-prediction models using a sample set of Eocene sandstones with known values of measured permeability. A porosity exponent of five provides the best quality permeability prediction using the weighted geometric mean of [Formula: see text]. The replacement of the weighted geometric mean of [Formula: see text] by the weighted arithmetic or harmonic mean in combination with a porosity exponent of six indicates a slightly lower predictive quality. The use of average pore radii instead of average [Formula: see text] enables a better permeability prediction. The porosity exponents become smaller in these equations. This finding is confirmed by multivariate regression that provides noninteger exponents for porosity, relaxation time, or characteristic pore radii.

Spontaneous subarachnoid hemorrhage (SAH) accounts for 5-10% of all strokes and is a subtype of hemorrhagic stroke that places a heavy burden on health care. Despite great progress in surgical clipping and endovascular treatment for ruptured aneurysms, cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI) threaten the long-term outcomes of patients with SAH. Moreover, there are limited drugs available to reduce the risk of DCI and adverse outcomes in SAH patients. New insight suggests that early brain injury (EBI), which occurs within 72 h after the onset of SAH, may lay the foundation for further DCI development and poor outcomes. The mechanisms of EBI mainly include excitotoxicity, oxidative stress, neuroinflammation, blood-brain barrier (BBB) destruction, and cellular death. Mitochondria are a double-membrane organelle, and they play an important role in energy production, cell growth, differentiation, apoptosis, and survival. Mitochondrial dysfunction, which can lead to mitochondrial membrane potential (ΔΨm) collapse, overproduction of reactive oxygen species (ROS), release of apoptogenic proteins, disorders of mitochondrial dynamics, and activation of mitochondria-related inflammation, is considered a novel mechanism of EBI related to DCI as well as post-SAH outcomes. In addition, mitophagy is activated after SAH. In this review, we discuss the latest perspectives on the role of mitochondria in EBI and DCI after SAH. We emphasize the potential of mitochondria as therapeutic targets and summarize the promising therapeutic strategies targeting mitochondria for SAH.

In recent years, ground-based radar has been widely used as an emerging deformation monitoring technology. Compared with traditional satellite-based radar, ground-based radar has many unique advantages, such as high temporal resolution and independence from atmospheric and ionospheric influences. Scholars usually assume that the radar's position is fixed every day when making continuous observations of the target area for multiple days. However, when experimental conditions do not allow us to temporarily fix the radar on the ground, a baseline error arises between two days of measurements, which causes the attitude of the radar to change. Based on the upper and lower dual antenna design adopted by the GAMMA portable Radar, this paper proposes a DEM model generated using the upper and lower antennas to back-calculate the baseline difference between the two measurements and eliminate the baseline difference by the model to ensure the accuracy of the experimental results. The results of the measured data processing demonstrate the effectiveness of the method mentioned in this paper in eliminating baseline errors

OBJECTIVES Accurate intraoperative identification of small lung tumours is crucial for precise resection of these lesions during video-assisted thoracoscopic surgery (VATS). This study aimed to evaluate the feasibility and safety of indocyanine green (ICG) inhalation for intraoperative visualization of lung tumours. METHODS From January 2022 to May 2022, 43 patients with lung nodules were included into this study. All patients received intraoperative ICG inhalation for visualization of lung tumours under near-infrared (NIR) imaging. The primary outcomes of this trial were the detection rate and background-tumour-ratio (BTR) of lung nodules, and the secondary objectives were time to search for nodules and operative time to nodules excision. RESULTS A total of 50 pulmonary nodules in 43 patients were identified and completely resected. And 44 lung nodules were detected during intraoperative fluorescent exploration with a median inhaled ICG dose of 18.8 mg. In vivo, the median BTR was 7.10. The median detection time of nodules was 100 seconds and the median operative time to nodules excision was 18 min. Quantification analysis showed that the fluorescence intensity of postoperative sputum declined to about 10% of the first fluorescent sputum within 20 hours. No adverse events attributed to ICG inhalation were recorded during the follow-up period. CONCLUSIONS Intraoperative inhalation of ICG was a feasible and safe method for detection of lung tumours at low dose of ICG. This technique could be a remedial measure for identification of unpalpable lung nodules without preoperative localization. Trial registration Chinese Clinical Trial Registry, Identifier: ChiCTR2100053708

Background BRASSINAZOLE-RESISTANT (BZR) is a class of specific transcription factor (TFs) involved in brassinosteroid (BR) signal transduction. The regulatory mechanism of target genes mediated by BZR has become one of the key research areas in plant BR signaling networks. However, the functions of the BZR gene family in cucumber have not been well characterized. Results In this study, six CsBZR gene family members were identified by analyzing the conserved domain of BES1 N in the cucumber genome. The size of CsBZR proteins ranges from 311 to 698 amino acids and are mostly located in the nucleus. Phylogenetic analysis divided CsBZR genes into three subgroups. The gene structure and conserved domain showed that the BZR genes domain in the same group was conserved. Cis-acting element analysis showed that cucumber BZR genes were mainly involved in hormone response, stress response and growth regulation. The qRT-PCR results also confirmed CsBZR response to hormones and abiotic stress. Conclusion Collectively, the CsBZR gene is involved in regulating cucumber growth and development, particularly in hormone response and response to abiotic stress. These findings provide valuable information for understanding the structure and expression patterns of BZR genes.

RNF2 is a RING domain-containing E3 ubiquitin ligase that mediate histone H2A mono-ubiquitination to repress gene transcription, but its expression patterns and molecular function in hepatocellular carcinoma (HCC) remain unclear. Herein, we extracted data from TGCA database and validated RNF2 expression in our own cohort, which revealed that RNF2 was highly expressed in HCC and was associated with malignant characteristics and poor prognosis of HCC. Moreover, RNF2 was demonstrated to promote HCC metastasis via enhancing epithelial-mesenchymal transition (EMT) both in vitro and in vivo. Mechanistically, RNF2 repressed E-Cadherin transcription by increasing the deposition of H2K119ub at the E-Cadherin promoter region. In addition, RNF2-regulated crosstalk between H2AK119ub, H3K27me3 and H3K4me3 synergistically reduced E-Cadherin transcription, which promoted EMT and HCC metastasis. These results indicate that RNF2 played an oncogenic role in HCC progression via inducing EMT, and RNF2 could be a potential therapeutic target for HCC.

With the development of medical care, the safety of thyroidectomy is improving year by year. Due to economic benefits and other advantages of the overnight and outpatient thyroidectomy, more and more patients and medical institutions have favored overnight and outpatient thyroidectomy, and its proportion in thyroidectomy has increased year by year. However, overnight and outpatient thyroidectomy still faces many challenges and remains to be improved. In this review, we focused on the recent progress and the relevant clinical features of overnight and outpatient thyroidectomy, including its safety, economic benefits, etc., which may bring valuable clues and information for further improvements of patient benefits and promotions of overnight or outpatient thyroidectomy in the future.

Background: Immune cell death (ICD) is a type of tumor cell death that has recently been shown to activate and regulate tumor immunity. However, the role of ICD-related long non-coding RNAs (lncRNAs) in gastric cancer remains to be clarified.Methods: We obtained 375 tumor samples from the Cancer Genome Atlas (TCGA) database and randomly assigned them to training and verification groups. LASSO and Cox regression analysis were utilized to identify ICD-related lncRNAs and establish a risk model. The changes in the immune microenvironment of the two groups were compared by examining the tumor-infiltrating immune cells.Results: We established a tumor signature based on nine ICD-related lncRNAs. In light of the receiver operating characteristic and Kaplan–Meier curves, the prognostic values of this risk model were verified. Multivariate regression analysis showed that the risk score was an independent risk factor for the prognosis of patients in both the training cohort (HR 2.52; 95% CI: 1.65–3.87) and validation cohort (HR 2.70; 95% CI: 1.54–4.8). A nomogram was developed to predict the 1-, 3-, and 5-year survival of patients with gastric cancer, and the signature was linked to high levels of immunological checkpoint expression (B7-H3, VSIR).Conclusions: An ICD-related lncRNA signature could predict the immune response and prognosis of patients with gastric cancer. This prognostic signature could be employed to independently monitor the efficacy of immunotherapy for gastric cancer patients.

The use of vehicle operating mode (OpMode) distribution is widely accepted for estimating energy consumption and emissions in the Motor Vehicle Emission Simulator (MOVES) model. However, the heterogeneity of driving behavior may lead to errors when using the default OpMode distribution. To improve the accuracy of energy consumption estimations, it is necessary to recognize the heterogeneity in OpMode distribution among different driving behaviors. With this aim, this paper designs a speed-specific indicator of energy efficiency reflecting driving behavior based on the speed-specific vehicle-specific power (VSP) distribution. The paper uses field data from 26,082 drivers recorded second by second during workdays. It also discusses the intra-heterogeneity and inter-heterogeneity of driving behavior based on unsupervised algorithm clustering. The findings of this paper are as follows. (1) The speed-specific VSP distribution clearly reflects the differences in energy efficiency of individuals’ driving behavior. (2) The energy efficiency indicator reflects the multidimensional inter-heterogeneity and intra-heterogeneity of driving behavior. (3) Drivers’ varied driving behavior causes heterogeneity in energy efficiency at different speeds, possibly causing an error of 6.34% in the emissions estimations. (4) Drivers of electric vehicles (EVs) and hybrid electric vehicles (HEVs) show more aggressive driving behaviors than drivers of conventional vehicles (CVs), which may cause an energy estimation error of over 6% for EVs and HEVs. Thus, the OpMode distribution of EVs, HEVs, and CVs should be modeled separately for on-road energy estimations.

A detailed and accurate fuel model fuel consumption model that reflects real-world fuel consumption is required as input for devising and executing a model policy for prospective regulatory tools. The fuel consumption model based on the vehicle-specific power (VSP) has rapidly become the primary development direction since the release of the Motor Vehicle Emissions Simulator (MOVES) model. However, fuel consumption cannot be accurately characterized under high-speed scenarios. This work develops two fuel consumption models for the light-duty (gasoline) vehicles that can better characterize fuel consumption for light-duty vehicles under high-speed scenarios. For model 1, the VSP of −5kW/ton is a crucial turning point. When VSP∈ [−30, −5] kW/ton, the fuel rate is only determined by speed. When VSP∈(−5, 30], the fuel rate will gradually increase with VSP, and the growth characteristics will vary with speed. Model 2 develops the new interpretations for VSP and forms the one-to-one correspondence between the fuel rate and the new VSP. The two models can separately improve the accuracy by 12.2% and 13.8% compared with the conventional model. The fuel factor differences become significant when speed is higher than 65 km/h, which are separately 30.66% and 28.13% higher than the conventional VSP model when the speed is 100 km/h. Further, the fuel factors of the two models for freeways are, respectively, 6.33% and 7.56% higher than the conventional VSP model, and the distinction for arterial, collector, and local street roads is not notable.