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Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is a rapidly progressing infectious disease with a high fatality rate caused by a novel bunyavirus (SFTSV). The role of lipids in viral infections is well-documented; however, the specific alterations in lipid metabolism during SFTSV infection remain elusive. This study aims to elucidate the lipid metabolic dysregulations in the early stages of SFTS patients. Methods This study prospectively collected peripheral blood sera from 11 critical SFTS patients, 37 mild SFTS patients, and 23 healthy controls during the early stages of infection for lipidomics analysis. A systematic bioinformatics analysis was conducted from three aspects integrating lipid differential expressions, lipid differential correlations, and lipid-clinical indices correlations to reveal the serum lipid metabolic dysregulation in SFTSV-infected individuals. Results Our findings reveal significant lipid metabolic dysregulation in SFTS patients. Specifically, compared to healthy controls, SFTS patients exhibited three distinct modes of lipid differential expression: increased levels of lipids including phosphatidylserine (PS), hexosylceramide (HexCer), and triglycerides (TG); decreased levels of lipids including lysophosphatidylcholine (LPC), acylcarnitine (AcCa), and cholesterol esters (ChE); and lipids showing “dual changes” including phosphatidylcholine (PC) and phosphatidylethanolamine (PE). Finally, based on lipid metabolic pathways and literature analysis, we systematically elucidated the potential mechanisms underlying lipid metabolic dysregulation in the early stage of SFTSV infection. Conclusions Our study presents the first global serum lipidome profile and reveals the lipid metabolic dysregulation patterns in the early stage of SFTSV infection. These findings provide a new basis for the diagnosis, treatment, and further investigation of the disease.

In China and other developing countries, some bicycle riders exhibit retrograde behaviour, which affects the riding safety of normal cyclists. The effect of retrograde behaviour on visual search and cycling behaviours of normal cyclists is investigated and quantified in this study. First, cyclists are instructed to wear an SMI iView ETG head-mounted mobile eye tracker and a mobile phone equipped with a Global Positioning System real-time location monitoring function to cycle on a road to obtain the times of fixation, saccade and blink, as well as the pupil diameter, gaze position and velocity in normal and retrograde conditions. Subsequently, the effect of retrograde behaviour on the attention of normal cyclists is analysed using three indexes: proportion of fixation time, coefficient of variation of pupil diameter and area of interest. Then, the effect of cycling behaviour is analysed using three indexes: the cycling trajectory, the velocity at three stages and the coefficient of variation of velocity. Finally, polynomial regression analysis is performed to analyse the visual and cycling behaviour impact indexes under the retrograde condition. The results show that retrograde behaviour significantly affects the vision and cycling behaviour of normal cyclists and that the two indexes are positively correlated.

Background Short tandem repeat (STR) markers are widely used in forensic DNA analysis due to their ability to provide automated and standardised typing. However, incorrect STR typing can have a significant impact on forensic outcomes.Aim In this study, we detected drop-out alleles at the SE33 locus in a putative father-son pair using the Microreader™ 28 A ID System. This result could lead to a false conclusion of non-paternity.Subjects and methods To investigate the cause of the drop-out alleles, we developed a nest and touch-down PCR program for Sanger sequencing of the SE33 locus. Subsequently, we investigated the mutation frequency in 300 unrelated individuals and reviewed the results of 429 paternity tests.Results The results showed that the frequency of the G > T mutation at this locus was less than 0.01, which is a novel and rare mutation. Our analysis revealed a novel G > T mutation in the primer-binding region of both samples, which was a rare single-nucleotide mutation site in the Chinese population. This variation was found to be responsible for the drop-out alleles observed in the samples.Conclusion Our findings have important implications for optimising primer design and constructing DNA databases for forensic analysis.

Fusion of hyperspectral image (HSI) and multispectral image (MSI) is a prevalent scheme to generate a HSI with enhanced spatial resolution. Current methods often fail to sufficiently leverage the effective spectral and spatial priors existing in the observed HSI and MSI to further enhance the fusion performance. To address this limitation, this paper proposes a novel HSI-MSI fusion approach, which integrates Sparse and Low Rank with a CNN denoiser (SLRCNN) while considering spectral dictionary optimization. Firstly, an initialized spectral dictionary is derived from the HSI. Next, the spatial coefficients optimization model is established by incorporating the sparse prior, local low-rank prior, and plugged image prior simultaneously, where the l1 norm is imposed to promote the sparse prior, and the super-pixel segmentation strategy is conducted on the MSI to impose the local low-rank prior while a well-trained CNN denoiser is plugged in to enforce the image prior. Then, the spectral dictionary optimization model is constructed to refine the initial spectral dictionary, capturing more detailed spectral characteristics to further improve the fusion results. Finally, the optimization process involves applying the split-augmented Lagrangian shrinkage method and the alternating direction method of multipliers. Experimental results on simulated and real datasets, namely the Pavia University dataset, the Indian Pines dataset, and the EO-1 dataset, indicate that SLRCNN outperforms existing state-of-the-art approaches at 4x, 5x, and 6x resolutions in both qualitative and quantitative evaluation results. Specifically, the peak signal-to-noise ratio (PSNR) of SLRCNN is improved by more than 0.9 dB, 0.9 dB, and 0.2 dB while the spectral angle mapper (SAM) is decreased by more than 0.1, 0.2, and 0.2 in degree compared to other state-of-the-art methods across three datasets, respectively, which underscores the effectiveness of SLRCNN in leveraging both spatial detail reconstruction and spectral preservation.

Through exploring the stress corrosion cracking (SCC) behaviors of the as-cast Mg-8%Li and Mg-8%Li-6%Zn-1.2%Y alloys in a 0.1 M NaCl solution, it revealed that the SCC susceptibility index (ISCC) of the Mg-8%Li alloy was 47%, whilst the ISCC of the Mg-8%Li-6%Zn-1.2%Y alloy was 68%. Surface, cross-sectional and fractography observations indicated that for the Mg-8%Li alloy, the α-Mg/β-Li interfaces acted as the preferential crack initiation sites and propagation paths during the SCC process. With regard to the Mg-8%Li-6%Zn-1.2%Y alloy, the crack initiation sites included the I-phase and the interfaces of I-phase/β-Li and α-Mg/β-Li, and the preferential propagation paths were the I-phase/β-Li and α-Mg/β-Li interfaces. Moreover, the SCC of the two alloys was concerned with hydrogen embrittlement (HE) mechanism.

Background/Objectives: Indomethacin (IDM) is commonly used to treat chronic inflammatory diseases such as rheumatoid arthritis and osteoarthritis. However, long-term oral IDM treatment can harm the gastrointestinal tract. This study presents a design for encapsulating IDM within mixed micelles (MMs)-loaded dissolving microneedles (DMNs) to improve and sustain transdermal drug delivery. Methods: Indomethacin-loaded mixed micelles (IDM-MMs) were prepared from Soluplus® and Poloxamer F127 by means of a thin-film hydration method. The MMs-loaded DMNs were fabricated using a two-step molding method and evaluated for storage stability, insertion ability, in vitro release, in vitro transdermal penetration, and in vivo PK/PD studies. Results: The obtained MMs were stable at 4 °C and 30 °C for 60 days. The in vitro IDM transdermal penetration was remarkably improved by the MMs-loaded DMNs compared to a commercial patch. A pharmacokinetic study demonstrated that the MMs-loaded DMNs had a relative bioavailability of 4.1 in comparison with the commercial patch. Furthermore, the MMs-loaded DMNs showed a significantly shorter lag time than the commercial patch, as well as a more stable plasma concentration than the DMNs without MMs. The therapeutic efficacy of the IDM DMNs was examined in Complete Freund’s Adjuvant-induced arthritis mice. The IDM DMN treatment effectively reduced arthritis severity, resulting in decreased paw swelling, arthritis index, spleen hyperplasia, and serum IL-1β and TNF-α levels. Conclusions: Our findings demonstrated that the novel MMs-loaded DMNs were an effective strategy for sustained IDM release, providing an alternate route of anti-inflammatory drug delivery.

ObjectiveThis retrospective observational study primarily aimed to analyse the clinical characteristics of patients with neuronal surface antibody-mediated autoimmune encephalitis (AE) in China and report their prognosis after immunotherapy.MethodsClinical characteristics, laboratory or imaging examinations, and treatment outcomes of 103 patients diagnosed with AE between 1 September 2014 and 31 December 2020 were collected. Univariate and multivariate logistic regression analyses were performed to determine the predictors of poor prognosis.ResultsOverall, 103 patients were enrolled in the study. The main clinical symptoms included seizures (74.8%), psychiatric and behavior disorders (66.0%), cognitive deficits (51.5%), disturbances of consciousness (45.6%), and movement disorders/involuntary movements (26.2%). The distribution of clinical syndromes also differed for different AE subtypes. The efficacy rates of first-line immunotherapy for anti-NMDAR, anti-LGI1, anti-GABABR, and anti-CASPR2 encephalitis were 70.2%, 92.3%, 70%, and 83.3%, respectively, and rituximab was administered to 21 patients as second-line immunotherapy, including 14 patients with anti-NMDAR encephalitis, 4 with anti-LGI1 encephalitis, 2 with anti-GABABR encephalitis, and 1 with anti-CASPR2 encephalitis. Five patients with poor effect of the second-line treatment received bortezomib. According to the results of the last follow-up, 78 patients had a good prognosis (mRS 0–2), and 21 patients had a poor prognosis (mRS 3–6). The proportion of patients with a poor prognosis was significantly higher in anti-GABABR encephalitis compared to the other AE subtypes (p

Considering the great time and labor consumption involved in conventional hazard assessment methods in compiling landslide inventory, the construction of a transferable landslide susceptibility prediction model is crucial. This study employs UAV images as data sources to interpret the typical alpine valley area of Beichuan County. Eight environmental factors including a digital elevation model (DEM) are extracted to establish a pixel-wise dataset, along with interpreted landslide data. Two landslide susceptibility models were built, each with a deep neural network (DNN) and a support vector machine (SVM) as the learner, and the DNN model was determined to have the best pre-training performance (accuracy = 88.6%, precision = 91.3%, recall = 94.8%, specificity = 87.8%, F1-score = 93.0%, and area under curve = 0.943), with higher parameters in comparison to the SVM model (accuracy = 77.1%, precision = 80.9%, recall = 87.8%, specificity = 73.9%, F1-score = 84.2%, and area under curve = 0.878). The susceptibility model of Beichuan County is then transferred to Mao County (which has no available dataset) to realize cross-regional landslide susceptibility prediction. The results suggest that the model predictions accomplish susceptibility zoning principles and that the DNN model can more precisely distinguish between high and very-high susceptibility areas in relation to the SVM model.

Acute hepatopancreatic necrosis disease (AHPND) caused by Vibrio parahaemolyticus causing AHPND (VPAHPND) is the most serious disease affecting shrimp farming. The PirAvp and PirBvp toxins of VPAHPND are known virulence factors. However, the corresponding target protein in shrimp that mediates their action has not been identified. By screening yeast two-hybrid cDNA libraries from intestine, stomach, and hepatopancreas of Litopenaeus vannamei, the protein with the largest increase in gene expression in shrimp hepatopancreas in response to VPAHPND challenge was identified and designated LvFABP. Analysis revealed high sequence homology of the LvFABP gene and a lipocalin/cytosolic fatty acid binding gene. Yeast two-hybrid pairwise analysis, GST-pull down assay, and far-western blot assay were performed to determine the interaction between LvFABP and PirBvp. LvFABP was able to directly bind to PirBvp. The expression of LvFABP in the hepatopancreas was significantly higher at P23 and P27 developmental stages of L. vannamei. RNA interference (RNAi) of LvFABP reduced the mortality, histopathological signs of AHPND in the hepatopancreas, and the number of virulent VPAHPND bacteria in the intestine, stomach, and hepatopancreas after VPAHPND challenge. We concluded that the LvFABP was involved in AHPND pathogenesis and acted as a VPAHPND toxin interacting protein. This is the first identification of VPAHPND toxin interacting protein from the shrimp digestive system by yeast two-hybrid library screening and were confirmed by in vitro protein interaction verification and in vivo challenge experiments. This study provides novel insight into the contributions of LvFABP towards AHPND pathogenesis in shrimp. The findings could inform AHPND preventative measures in shrimp farming.

ObjectiveThis study aimed to determine the clinical characteristics and evaluate the efficacy of immunotherapy and the long-term prognosis of severe autoimmune encephalitis (AE) in China.MethodsClinical features, laboratory or radiological findings, and treatment outcomes of 60 severe patients with AE from January 1, 2014, to December 31, 2020, were collected. Continuous variables were compared using the t-test and the nonparametric Mann–Whitney U test, as appropriate. Univariate and multivariable logistic regression analyses were performed to assess the correlations between factors, treatment responses, and prognosis of severe AE.ResultsThe median age of symptom onset was 35 years. Tumors were identified in 23.3% of patients, and 36/60 (60%) patients responded to first-line immunotherapy. Second-line immunotherapy was implemented in 26/60 (43.3%) patients. A significant clinical benefit was observed in 19/26 (73.1%) patients treated with lower dosage rituximab; seven patients were still refractory and received bortezomib as an add-on therapy. During the last follow-up, 48/60 (80%) patients achieved good outcomes (mRS, 0–2), and 10 died. Seventeen patients experienced relapses. A high CD19+ B-cell count (OR, 1.197; 95% CI [1.043–1.496]; p = 0.041) and a lower neutrophil-to-lymphocyte ratio (NLR; OR, 0.686; 95% CI [0.472–0.884]; p = 0.015) predict the response to first-line treatment and good prognosis, respectively.ConclusionsPatients with severe AE were in critical condition at baseline but could be salvaged after effective rescue immunotherapy. A lower dosage of rituximab could be an optimal option for severe AE. CD19+ B-cell count and NLR may provide prognostic information for predicting treatment response and outcome of severe AE.

ObjectiveThis study was performed to assess the potential factors for poor short-term first-line treatment response, the appropriate further treatment options, and the prognosis in patients with autoimmune encephalitis (AE).MethodsThis retrospective study consisted of 135 patients with AE. According to their short-term first-line treatment response, patients were divided into the response group and the non-response group. The demographics, clinical characteristics, main accessory examinations, immunotherapy, and outcomes of patients were compared between the two groups. Univariate and multivariate logistic regression models were used to analyze whether non-responders have poor long-term outcomes. Further treatment and prognosis of non-responders were also analyzed.ResultsOf the 128 patients who were treated with first-line immunotherapy, 59 (46.1%) were non-responders. Patients in the non-response group had more symptoms and exhibited a higher proportion of mental behavior disorder, central hypoventilation, and autonomic nervous dysfunction. The modified Rankin scale (mRS) scores and neutrophil-to-lymphocyte ratio (NLR) levels were significantly higher and albumin, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (apoA) levels were significantly lower in the non-response group (p < 0.05, all). Multivariate logistic regression analysis showed that the number of clinical symptoms, mental behavior disorder, central hypoventilation, maximum mRS score, and albumin level was independently associated with non-response to short-term first-line treatment. Non-responders had poor long-term outcomes compared with the responders at all times of followed-up (p < 0.05, all). In multivariable analysis, initial first-line treatment response was independently associated with the long-term prognosis, both at 12-month [odds ratio (OR), 4.74, 95% CI, 1.44–15.59, and p=0.010] and 24-month follow-ups (OR, 8.81, 95% CI, 1.65–47.16; and p = 0.011). Among the non-responders, a higher improvement of mRS scores was observed in those who received second-line treatment than those who had no further treatment or repetition of first-line immunotherapy in the follow-up. However, the rate of a good outcome and median mRS scores were not significantly different among the three groups.ConclusionDisease severity, clinical features, anti-N-methyl-D-aspartate receptor subtypes, antibody titers, NLR, albumin, HDL-C, and apoA levels were all associated with non-response to short-term first-line treatment. The short-term first-line treatment response is a valuable predictor of long-term outcomes in patients with AE. Second-line immunotherapy may be a more aggressive treatment option for patients who failed short-term first-line immunotherapy.

Roundabouts are a common traffic infrastructure, which are supposed to facilitate safe and smooth traffic flow. Electric bikes as a common traffic tool in a lot of cities in China play an important role in relieving traffic congestion due to the rapid increase of motor vehicles on roads. However, compared with cyclists, e-bikers are more vulnerable because of their higher speed when colliding with motor vehicles. In this research, the spatial-temporal distribution characteristics of conflicts between motor vehicles and electric bikes (e-bikes) at signalized roundabouts are explored. First, the time distance method was used to identify conflicts, and the time to collision (TTC) was selected as the discrimination index we proposed for two representative conflict types. On conflict heat maps and conflict distribution during one signal cycle, we found a series of spatial-temporal conflict distribution regularities. Spatially, the proposed two representative types of conflicts were mainly distributed at exit areas and near the outermost circulatory lanes. Conflict Type 1 was mainly distributed around the outermost motor vehicle lanes, and Type 2 was mainly distributed inside the outermost vehicle lanes and behind the second stop line. In time span, both types of conflicts showed rapid increase before reaching a peak at 30 percentile green time and then decreasing gradually after that peak. Type 1 presented a sharp increasing range during 0–10 percentile green time, while the sharp increasing range for Type 2 presented during the 10–20 percentile. The conclusions developed by this article could provide a theoretical basis for improving traffic safety at roundabouts.

A control strategy using variable speed limit (VSL) is a proven solution to reduce freeway collision risks and improve safety. However, the heterogeneity of human drivers restricts the effectiveness of traditional VSL controls, which may be made up by recent advanced technologies of connected and automated vehicles (CAVs). This study aims to propose a CAV-based VSL control system to address the limitations caused by human drivers on VSL control’s effectiveness. First, the heterogeneity of human drivers is analyzed, and its impact on the safety performance of VSL is examined. Specifically, a microscopic simulation platform is established, and two vehicle dynamic models developed for CAVs and human-driven vehicles (HDVs) are incorporated into the simulation platform. Based on a widely utilized surrogate safety measurement, time-to-collision, its derivative metrics are applied to evaluate collision risks, and the total travel time is used to assess operational efficiency. Extensive simulations are conducted to examine the performance of the proposed CAV-VSL system. The results indicate the following: (1) the heterogeneity of human drivers negatively affects the performance of the VSL; (2) the performance of the proposed control system in a mixed flow can be improved by advanced wireless communication technology; (3) CAVs are able to implement the VSL control strategy effectively resulting in the proactive reduction of the heterogeneity.

Rickettsia felis (R. felis) infection is a cause of unspecified encephalitis. However, the incidence has been underestimated due to the intracellular features of the pathogen and insufficient understanding of its clinical picture. This study reported a case of R. felis infection in a 26-year-old female who only manifested with certain neurological symptoms. With a lack of specific systemic inflammatory symptoms, the diagnosis was initially misdiagnosed as a brain glioma. However, a brain tissue biopsy showed prominent perivascular inflammatory infiltrations, which indicated inflammatory disease. Spinal fluid metagenomic next-generation sequencing (mNGS) was taken after ruling out other common infectious and autoimmune diseases. The results suggested R. felis infection, which was also supported by Weil-Felix reaction in the serum. After the diagnosis was corrected as R. felis encephalitis, the patient was successfully treated with doxycycline and had a good prognosis at the 1-year follow-up.

Using natural succession to restore degraded grassland is mainly achieved by self-adjusting the structure and relationship of the internal components of grassland ecosystems. Microorganisms play an important role in the restoration of grassland ecosystems; however, there is no systematic research summary on how microbial communities respond to natural restoration succession in degraded grasslands. In this study, related research results in recent years were summarized and analyzed using meta-analysis. Results showed that soil microbes displayed no significant changes at the early stage (≤5 years) of natural restoration succession, but significantly increased at the following stage (6–10 years) of restoration succession, before decreasing with the continuation of succession. Changes in microbial activity mainly occurred in the 0–20 cm soil depth layer. Numbers of bacteria, fungi, and actinomycetes significantly increased at the six to 10 year stage of restoration succession. When restoration succession ceased after 10 years, most microorganisms began to decrease. During natural restoration succession, the diversity of fungi and bacteroidetes increased, while chloroflexi diversity decreased. These results indicated that the optimal period for the natural restoration succession of degraded grassland was approximately 10 years to ensure that the microbes of the grassland system returned to relatively high levels.

Root traits have an important impact on plant growth, which reflects the adaptation of plants to nutrients. This paper describes the focus and progress of root traits research and provides references for future research. Based on the Web of Science online database, articles related to root traits from 2000–2021 were evaluated using bibliometric methods. The results showed that the study of root traits has been growing steadily in the last two decades. Wang Yan is the author with the highest number of published papers, the most citations and the highest H-index. The top three published countries are the USA, China and India. The top three institutions are the University of Western Australia, China Agricultural University and Nanjing Agricultural University. Plant and Soil, Frontiers in Plant Science and PLoS One have the highest number of published articles. In terms of co-occurrence of keyword analysis, growth, soil and plant diversity are highly correlated with root traits. It was found that cooperation between authors, institutions and countries are not close enough and that z global network of cooperation has not yet been formed. Therefore, worldwide cooperation should be strengthened to promote resource sharing and the openness of relevant mechanisms.

MicroRNAs (miRNAs) are endogenous small non-coding RNAs that constitute a broad layer of gene regulation at both transcriptional and post-transcriptional levels from prokaryotes to eukaryotes. In embryonic development, they regulate the complex gene expression associated with the complexity of embryogenesis. There is little information about miRNAs in the red claw crayfish (Cherax quadricarinatus), an important commercial species and a potential biological model. In the present study, miRNAs and their target genes were identified during three embryonic developmental stages of C. quadricarinatus. Nineteen known miRNAs and 331 novel ones belonging to 50 miRNA families were obtained. A total of 113 differentially expressed miRNAs were identified, and 2,575 target genes were predicted, of which 1,257 were annotated. Additionally, 63 target genes of 9 miRNAs in C. quadricarinatus were found to be related to embryonic development. For example, miR-10 and its target genes may regulate the nervous system development and body segmentation and miR-2788 may regulate cell proliferation to impact embryonic development. Moreover, miR-28 (target gene tutl), miR-50 (target gene fbx5), and miR-1260b (target gene sif) may co-regulate eye development of embryonic C. quadricarinatus. These miRNAs together with their target genes constitute a network for regulating the development of tissues and organs in the embryo of C. quadricarinatus. Our results lay a foundation for further study on the fundamental molecular and developmental mechanism of crustacean embryogenesis.

Bicycle traffic flow suffers from the impact of tracks at an intersection in which a modern streetcar route is laid. The primary objective of this study involves discussing the impacts of modern streetcar tracks on bicycling through an intersection and developing a quantitative approach to calculate bicycle delay. Field investigations are conducted at eight sites in Nanjing and Shenyang, China. The sites are related to five intersections. Two of the five intersections are designed with a central modern streetcar style of track. Other two intersections operate on a roadside style of track and the last intersection is without tracks. The impact of the differences in bicycle speed are tested at each site based on the observed data. The results show that modern streetcar tracks exert a significant influence on bicycle speed and bicycling behavior and lead to delay, discomfort and unsafe conditions. Furthermore, a model is proposed to predict bicycle delay caused by modern streetcar tracks. The proposed model achieved a relatively accurate prediction. The findings of this study help in adequately understanding the impacts of modern streetcar tracks on bicycling. The results also suggest that longer crossing times should be used in signal design for bicycling at an intersection in which a modern streetcar route is laid.

The Pacific white shrimp (Litopenaeus vannamei), as one of the most valuable crustaceans, is widely distributed in China. Dietary astaxanthin has multiple functions in L. vannamei, such as promoting growth and antioxidant production. In the current study, shrimps were fed a diet which was supplemented with 0, 50, or 100 ppm astaxanthin for 4 weeks, and the specific growth rate (SGR) and weight gain were significantly greater in treatment groups compared to control group. We performed the transcriptome analysis of hepatopancreas of L. vannamei and detected 14,336, 14,780, and 14,400 genes, respectively. 598 and 285 genes were significant differentially expressed compared with the control group, under supplementation with 50 and 100 ppm astaxanthin, respectively, of which 434 and 104 were up-regulated and 164 and 181 were down-regulated. Through the KEGG pathway analysis, we found that the significant differentially expressed genes were mainly enriched in metabolic-related pathways, such as metabolic pathway, pyruvate metabolism, and glycolysis/gluconeogenesis pathway. Twelve genes were chosen to validate the results of RNA-Seq by qRT-PCR. This study provides valuable information about the effect of astaxanthin on L. vannamei. The genes and pathways, which are identified in the current study, can help to reveal the molecular mechanism responsible for the effect of astaxanthin on metabolism. Keywords: Astaxanthin, Litopenaeus vannamei, Transcriptome, Growth performance, Metabolism

With the continuous process of urbanization, regional integration has become an inevitable trend of future social development. Accurate prediction of passenger volume is an essential prerequisite for understanding the extent of regional integration, which is one of the most fundamental elements for the enhancement of intercity transportation systems. This study proposes a two-phase approach in an effort to predict highway passenger volume. The datasets subsume highway passenger volume and impact factors of urban attributes. In Phase I, correlation analysis is conducted to remove highly correlated impact factors, and a random forest algorithm is employed to extract significant impact factors based on the degree of impact on highway passenger volume. In Phase II, a deep feedforward neural network is developed to predict highway passenger volume, which proved to be more accurate than both the support vector machine and multiple regression methods. The findings can provide useful information for guiding highway planning and optimizing the allocation of transportation resources.

Walking, as a healthy and environmentally friendly mode of travel, has been revived in many cities around the world. The mid-block crosswalk (MBC) is a common type of pedestrian facility, and the pedestrian hybrid beacon (PHB) is one of most commonly used signalized MBCs, having a wide range of applications. This study applied an upstream detection (UD) strategy to PHB to reduce the pedestrian waiting time at the crossing. Data were collected through video recordings at two crosswalks at two different periods of the day in the city of Nanjing. First, basic simulation models were developed in VISSIM according to the current layout and the signal control methods of the two crosswalks. Second, signal control logic was adjusted to develop simulation models of PHB. Third, upstream detectors were added to develop simulation models of PHB with a UD strategy. Models for PHB were simulated with 10 different random seeds, and a paired t-test was conducted to evaluate the performance of the UD strategy statistically. The results show that the UD strategy for PHB reduces pedestrian waiting time and increases vehicle delay. However, the reduction in pedestrian waiting time is greater than the increase in vehicle delay. The UD strategy has also been found to be more effective for crosswalks, with relatively short crossing lengths and low pedestrian volume. Finally, a discussion about factors concerned with the application of UD strategies in practice is carried out.

This paper is on the purpose of developing a segmented signal progression model for modern streetcar system. The new method is presented with the following features: (1) the control concept is based on the assumption of only one streetcar line operating along an arterial under a constant headway and no bandwidth demand for streetcar system signal progression; (2) the control unit is defined as a coordinated intersection group associated with several streetcar stations, and the control joints must be streetcar stations; (3) the objective function is built to ensure the two-way streetcar arrival times distributing within the available time of streetcar phase; (4) the available time of streetcar phase is determined by timing schemes, intersection structures, track locations, streetcar speeds, and vehicular accelerations; (5) the streetcar running speed is constant separately whether it is in upstream or downstream route; (6) the streetcar dwell time is preset according to historical data distribution or charging demand. The proposed method is experimentally examined in Hexi New City Streetcar Project in Nanjing, China. In the experimental results, the streetcar system operation and the progression impacts are shown to affect transit and vehicular traffic. The proposed model presents promising outcomes through the design of streetcar system segmented signal progression, in terms of ensuring high streetcar system efficiency and minimizing negative impacts on transit and vehicular traffic.

Intersections with a permitted left-turn phase have serious safety hazards as left-turning vehicles compete for the right of way with vehicles approaching from the opposite direction. This is a recurring problem in some developing countries. This study develops quantitative methods for assessing the driving safety of left-turning vehicles at intersections, based on data collected at four sites in Xi’an, China. The turning behaviors of left-turning vehicles were classified into three patterns, no-interference, yield, or rush, based on the interactions with the vehicles approaching from the opposite direction. This study established a vehicle-driving safety evaluation model through statistical analysis of kinematic characteristics and obtained the safety level distribution of the three turning behavior patterns. In addition, the intersection was divided into three areas, combined with the driving paths of the left-turning vehicles, and a safety evaluation model based on the entropy weight technique for order preference by similarity to an ideal solution (TOPSIS) method was proposed to calculate the safety level of left-turning vehicles in each area. The results showed that the rush pattern was judged to be the most dangerous turning behavior according to the driving safety level. Further, for vehicles turning left from west to north, the area between the north curb line and the north entry stop line is the most dangerous driving area. This study will help to understand the operational safety characteristics of left-turning vehicles from the spatial perspective and provide ideas for drivers to choose driving strategies and for vehicle manufacturers to design driver assistance systems. [ABSTRACT FROM AUTHOR]