bluuebunny/crossref_metadata_2025_split huggingface dataset:
AssemblyTron: flexible automation of DNA assembly with Opentrons OT-2 lab robots
Authors: Bryant John A , Kellinger Mason , Longmire Cameron , Miller Ryan , Wright R Clay 
Published: December 2022

Abstract
As one of the newest fields of engineering, synthetic biology relies upon a trial-and-error Design–Build–Test–Learn (DBTL) approach to simultaneously learn how a function is encoded in biology and attempt to engineer it. Many software and hardware platforms have been developed to automate, optimize and algorithmically perform each step of the DBTL cycle. However, there are many fewer options for automating the build step. Build typically involves deoxyribonucleic acid (DNA) assembly, which remains manual, low throughput and unreliable in most cases and limits our ability to advance the science and engineering of biology. Here, we present AssemblyTron, an open-source Python package to integrate j5 DNA assembly design software outputs with build implementation in Opentrons liquid handling robotics with minimal human intervention. We demonstrate the versatility of AssemblyTron through several scarless, multipart DNA assemblies, beginning from fragment amplification. We show that AssemblyTron can perform polymerase chain reactions across a range of fragment lengths and annealing temperatures by using an optimal annealing temperature gradient calculation algorithm. We then demonstrate that AssemblyTron can perform Golden Gate and homology-dependent in vivo assemblies (IVAs) with comparable fidelity to manual assemblies by simultaneously building four four-fragment assemblies of chromoprotein reporter expression plasmids. Finally, we used AssemblyTron to perform site-directed mutagenesis reactions via homology-dependent IVA also achieving comparable fidelity to manual assemblies as assessed by sequencing. AssemblyTron can reduce the time, training, costs and wastes associated with synthetic biology, which, along with open-source and affordable automation, will further foster the accessibility of synthetic biology and accelerate biological research and engineering.
Factors important for bull purchasing decisions and management in extensive rangeland production systems of New Mexico: a producer survey
Authors: Gifford Craig A , Taylor Keegan M , Spiegal Sheri , Duff Glenn C , Aney Skye , Elias Emile , Steiner Jean L , Estell Rick , McFarlane Zach D , Schohr Tracy K , DeAtley Kasey L , Banwarth Megan R 
Published: December 2022

Abstract
There were 463,000 head of beef cows in New Mexico as of January 1, 2021 (NASS, 2020), down roughly 4% from 2020 (NASS, 2019). Frequent drought often results in herd reduction and loss of valuable genetic progress. Bull selection is critical due to their influence on herd development. A survey was conducted to identify traits important to bull selection in New Mexico. Surveys were collected digitally (n = 83) and via the mail (n = 74). Responses were largely by cow/calf producers averaging 57 ± 1 years old with 24 ± 1 years’ experience. Survey respondents represented 4,384,296 acres of private owned, private leased, and leased public rangeland and irrigated pasture meadow in New Mexico and surrounding states. Average cow/calf operation size was 294 ± 39 head and average bull herd size was 21 ± 3 head. Average price paid for a bull in the past 2 years was $3,981 ± 213. Physical characteristics, individual bull performance information, and genetic information are all important traits to New Mexico bull buyers; however, most producers (56%) indicated that structural soundness was the most important factor influencing their selection decisions. Amongst expected progeny differences (EPDs), New Mexico producers consider the calving ease direct (CED) and birth weight (BW) EPDS to be most important (40% and 35%, respectively). Producers also indicated that multitrait selection indexes used by the American Angus Association were important to their selection decisions, with the beef value ($B) and weaned calf value ($W) indexes being cited most often (35% and 31%, respectively). Elements important to bull purchase include the bull’s sale preview (87%), body condition score (86%), feed efficiency/average daily gain information (85%), and actual scrotal circumference (82%). Following purchase of a new bull, most (60%) keep the bull separate from the cow herd until the following breeding season, while the remaining 40% of producers turn newly purchased bulls out within 30 days of purchase. Sixty eight percent of producers evaluate semen quality annually or prior to the start of the breeding season. Interestingly, 39% of producers indicated they used reproductive technologies like artificial insemination and synchronization of estrus while most (80%) test for trichomoniasis. The primary factor influencing culling decisions is age, followed by soundness and fertility.
Parameterization of the propeller thrust for modelling ship braking in ice channel behind icebreaker
Authors: Goncharov Vadim K , Klementieva Natalia Yu 
Published: December 2022

Abstract
Cargo ship sailing within the ice channel that an assisting icebreaker tracks in the compact ice cover is the usual navigation practice for difficult ice conditions in freezing seas and Arctic water areas. When the icebreaker or an ahead vessel stops before the insuperable ice obstacle or because of engine trouble, the danger of an emergency appears, namely of collision with the icebreaker or the ahead ship, if the interval between them is not sufficient for effective braking and stopping. The paper presents the equation that describes the ship braking process within an ice channel and includes the thrust of the propeller that works under the reverse regime. The specific of this regime is the following: the ship continues the motion ‘forwards' and the propeller rotates ‘backwards’. An analytical method for description of the ship propeller work on the reverse regime is absent because of the detached flow on its blades. The paper describes the developed empirical method of this regime parameterization on the basis of serial models of propeller testing. The outcomes of this investigation are applied to a ship braking process simulation and the evaluation of the safe interval between the ship and the icebreaker.
Railway switch fault diagnosis based on Multi-heads Channel Self Attention, Residual Connection and Deep CNN
Authors: Chen Xirui , Liu Hui , Duan Zhu 
Published: December 2022

AbstractA novel switch diagnosis method based on self-attention and residual deep convolutional neural networks (CNNs) is proposed. Because of the imbalanced dataset, the K-means synthetic minority oversampling technique (SMOTE) is applied to balancing the dataset at first. Then, the deep CNN is utilized to extract local features from long power curves, and the residual connection is performed to handle the performance degeneration. In the end, the multi-heads channel self attention focuses on those important local features. The ablation and comparison experiments are applied to verifying the effectiveness of the proposed methods. With the residual connection and multi-heads channel self attention, the proposed method has achieved an impressive accuracy of 99.83%. The t-SNE based visualizations for features of the middle layers enhance the trustworthiness.
Road traffic anomaly monitoring and warning based on DeepWalk algorithm
Authors: Wang Zihe , Ye Junqing , Tang Jinjun 
Published: December 2022

Abstract
In the complex urban road traffic network, a sudden accident leads to rapid congestion in the nearby traffic region, which even makes the local traffic network capacity quickly reduce. Therefore, an efficient monitoring system for abnormal conditions of the urban road network plays a crucial role in the tolerance of the urban road network. The traditional traffic monitoring system not only costs a lot in construction and maintenance, but also may not cover the road network comprehensively, which could not meet the basic needs of traffic management. Only a more comprehensive and intelligent monitoring method is able to identify traffic anomalies more effectively and quickly, so that it can provide more effective support for traffic management decisions. The extensive use of positioning equipment made us able to obtain accurate trajectory data. This paper presents a traffic anomaly monitoring and prediction method based on vehicle trajectory data. This model uses deep learning to detect abnormal trajectory on the traffic road network. The method effectively analyses the abnormal source and potential anomaly to judge the abnormal region, which provides an important reference for the traffic department to take effective traffic control measures. Finally, the paper uses Internet vehicle trajectory data from Chengdu (China) to test and obtains an accurate result.
Research on the logic monitoring method for the cloud computing based safety computer
Authors: Yang Yaran , Ma Lianchuan , Tang Tao , Ding Huan , Liu Zhen 
Published: December 2022

Abstract
With the development of railway construction in China, the computing demand of the train control system is increasing day by day. The application of cloud computing technology on the rail transit signal system has become a research hotspot in recent years. How to improve the safety and availability of the safety computer platform in the cloud computing environment is the key problem when applying cloud computing to the train operation control system. Since the cloud platform is in an open network environment, facing many security vulnerabilities and malicious network attacks, it is necessary to monitor the operation of computer programmes through edge safety nodes. Firstly, this paper encrypts the logical monitoring method, and then proposes a secure computer defence model based on the dynamic heterogeneous redundancy structure. Then the continuous time Markov chain (CTMC) is used to quantitatively solve the stable probability of the system, and the influence of different logical monitoring methods on the anti-attack performance of the system is analysed. Finally, the experiment proves that the dynamic heterogeneous redundancy structure composed of encryption logic monitoring can guarantee the safe and stable operation of the safety computer more effectively.
Performance of a vehicle-mounted anemometer under crosswind: Simulation and experiment
Authors: Sun Bo , Chen Guang , Chen Jun , Li Xiaobai , Tang Mingzan , Zhong Mu 
Published: December 2022

Abstract
Environmental wind measurements are essential for ensuring the operational safety of rail vehicles. In our previous work, an anemometer that can be mounted on the top of a train to achieve real-time measurements of wind speed and direction was proposed based on the pressure distributions around the cylindrical anemometer. However, the flow field on the top of the train is significantly influenced by the train; thus, the measured data might differ from the actual environmental wind parameters, particularly when trains are subjected to windbreak walls. In this study, simulations considering flow fields around trains installed with the proposed anemometer were conducted, and an improved delayed detached eddy simulation approach was adopted. Through simulations, the flow field at the top of the train was analysed, and the aerodynamic characteristics of the anemometer were investigated. Accordingly, relationships between the measured wind characteristics and environmental wind characteristics are presented under various situations herein. Field experiments were performed for the proposed anemometer installed on a certain type of high-speed train along the Nanjiang Railway in China. The results obtained from both the numerical and experimental studies show that the proposed method has high accuracy for measuring environmental wind speed and direction when mounted on the top of a train.
Correlation study between the square-cone energy-absorbing structure and the frontal collision behaviour of leading vehicles
Authors: Xu Ping , Gao Ying , Huang Chong , Yang Chengxing , Yao Shuguang , Che Quanwei 
Published: December 2022

Abstract
In order to study the influence of square-cone energy-absorbing structures on the mechanical behaviour of the collision performance of the leading vehicle, a parameterization method for rapidly changing the performance of energy-absorbing structures was proposed. Firstly, a finite element simulation model of the collision of the leading vehicle with a square-cone energy-absorbing structure was constructed. Then, the platform force, the slope of the platform force and the initial peak force of the force-displacement curve derived from the energy-absorbing structure were studied for the collision performance of the leading vehicle. Finally, the correlation model of the square-cone energy-absorbing structure and the mechanical behaviour of the collision performance of the leading vehicle was established by the response surface method. The results showed that the increase of the platform force of the energy-absorbing structure can effectively buffer the longitudinal impact of the train and reduce the nodding attitude of the train. The increase of the platform force slope can not only effectively buffer the longitudinal impact and vertical nodding of the train, but also reduce the lateral swing of the train. An increase in the initial peak force to a certain extent may lead to a change in the deformation mode, thereby reducing the energy-absorption efficiency. The correlation model can guide the design of the square-cone energy-absorbing structure and predict the deformation attitude of the leading vehicle.
Flexible Optimal Model and Algorithm for Track Utilization in High-speed Railway Stations
Authors: Gao Quan , Zhang Yinggui , Chen Zhiya , Chen Yuan 
Published: December 2022

Abstract
Track utilization is the most important technical operation in high-speed railway stations. It is an effective way to take flexible management based on dispatchers’ decision preferences into consideration for making track utilization plans to relieve the influence caused by unmeasurable unstructured factors. Thus, based on the flexible management concept and taking the flexible optimal for track utilization in high-speed railway stations as the object, time and space occupation safety trajectories of arrival routes, departure routes and tracks are all analysed. Then, taking the following constraints into consideration—minimum safety time intervals for various routes and tracks occupation, space-time arc occupation and decision-makers’ preferences—a flexible optimal model for track utilization in high-speed railway stations is established to maximize its balance and robustness and to minimize its volatility at the same time. Further, a flexible optimal solution based on a simulated annealing algorithm is designed to make a safety track utilization plan in high-speed railway stations integrating the dispatchers’ decision preference. The results from the experiments show that the proposed methodology can effectively make satisfied safety track utilization plans based on decision-makers’ preferences, which can improve its balance and robustness level significantly. Meanwhile, its volatility can be reduced as much as possible caused by flexible management based on artificial intervention to ensure the relative stability of the plan.
CO2 emissions reduction performance of China's HSR based on substitution effect and demand effect
Authors: Wang Liying , Yin Ping , Liu Shangqing 
Published: December 2022

Abstract
As an important transportation infrastructure and transportation backbone in China, high-speed rail (HSR) plays a critical role in promoting the development of green and low-carbon transportation. Calculating the CO2 emissions reduction performance of HSR will be conducive to promote the CO2 emissions reduction work of the railway. Based on the Dalkic HSR CO2 emissions reduction performance model, by adjusting the HSR CO2 emission factor (CEFHSR), the annual times of departures (T) and other parameters, this study develops a Chinese HSR CO2 emissions reduction performance model. Taking the Beijing-Shanghai HSR as the research object, this study conducts a questionnaire survey to explore the substitution effect and demand effect of HSR on different transportation modes; collects data such as passenger volume, average electricity use and annual times of departures of the Beijing-Shanghai HSR in 2019; and calculates the CO2 emissions reduction performance of the Beijing-Shanghai HSR. This study has two main results: (1) It builds a Chinese HSR CO2 emissions reduction performance model based on substitution effect and demand effect. (2) In 2019, the CO2 emissions of the Beijing-Shanghai HSR are 2 898 233.62 t, the CO2 emissions reduction performance of the Beijing-Shanghai HSR is 17 999 482.8 t, the annual CO2 emissions of the Beijing-Shanghai line in ‘No HSR’ case are 7.2 times as in the 'HSR' case and the PKT of the HSR is 10.2 g/pkm. Based on the research results, this study proposes three CO2 emissions reduction policy suggestions. This study would be helpful for further HSR CO2 emissions reduction research and departments related to railway transportation management to make CO2 emissions reduction policies.
Lane-changing decision rule with the difference of traffic flow's variation in multi-lane highway for connected and autonomous vehicles
Authors: Li Chuanyao , Huang Dexin , Wang Tao , Qin Jin 
Published: December 2022

Abstract
Drivers are not far-sighted when they execute lane-changing manipulation. To address this issue, this study proposes a rule to improve vehicles' lane-changing decisions with accurate information of surrounding vehicles (e.g. time headway). More specifically, connected and autonomous vehicles (CAVs) change lanes in advance if they find severer flow reducing in the lanes, while CAVs should maintain the car-following state if the variations of traffic flow in all lanes have a similar trend. To illustrate the idea, this study first calibrates two classic car-following models and a lane-changing model, and then conducts numerical simulations to illustrate the short-sighted decision of drivers. The study incorporates the idea into a lane-changing decision rule by changing the lane-changing model's parameter, and conducts numerical tests to evaluate the effectiveness of the lane-changing decision rule in a multi-lane highway with a bottleneck. The results of this study indicate that the new lane-changing decision rule can substantially improve the throughput of the traffic flow, especially when the inflow exceeds the remaining capacity of the road. The lane-changing rule and results can bring insights into the control of CAVs, as well as the driver assistance system in connected vehicles.
Research on headway control of a guided transport system based on intersection condition evaluation
Authors: Yu Xiao , Cao Yuan , Sun Yongkui 
Published: December 2022

Abstract
In order to ensure the safety and efficiency of the section tracking operation of a guided transport system, a safety headway control method of section tracking based on intersection conditions is proposed in this paper. Considering the difference of signal phase, the evaluation model of road conditions was established based on a fuzzy comprehensive evaluation method, FAGT. Based on the artificial potential field method, the time-varying hybrid artificial potential field (TH-APF) method was proposed, and the tracking headway control algorithm was designed to realize the dynamic control of the tracking headway of the guide transport vehicle. The simulation results verified the effectiveness and applicability of the evaluation model of intersection road conditions; the tracking headway can be maintained at about 120 s. The tracking headway control algorithm of guided transport vehicles can respond to the road conditions and avoid the local optimum of the artificial potential field method, thus improving the operating efficiency.
Left-turn-across-path-from-opposite-direction accidents in China: CIDAS accident study
Authors: Chen Yong , Buerger Christian , Lin Miao , Li Xudong , Labenski Volker , Jin Haixia , Wang Hai , Liu Yang , Ino Tsuyoshi , Feifel Harald , Tan Tian , Chang Fangrong 
Published: December 2022

Abstract
Left-turn-across-path-from-opposite-direction (LTAP/OD) conflicts are one of the most common crash types at intersections. The research aims to reveal the general and dynamic information about the conflict for the most relevant street layouts for each conflict configuration of the LTAP/OD accidents involving passenger cars, motorcycles and Ebikes. The analysis was based on 276 LTAP/OD accidents collected by the China in-depth accident study (CIDAS 2011–2019). The LTAP/OD accidents include 44 car-to-car conflicts, 157 car-to-motorcycle conflicts and 75 car-to-Ebike conflicts. Most accidents belonging to the three types were observed at the W0 street layout without a green belt separating the oncoming lane and no offset lane between the turning car and the oncoming traffic, the main distance between both vehicles in the beginning of the critical situation being about four metres, occurring in the clear day with no rain and at junctions lighted either because of daylight or based on street lighting. In terms of the turning car initial speed, the range is 15–30 km/h for most car-to-car and car-to-motorcycle accidents, but 30–40 km/h for most car-to-Ebike accidents. As for the collision speed, this range is between 10 km/h and 20 km/h for car-to-car and car-to-Ebike accidents and between 10 km/h and 25 km/h for car-to-motorcycle crashes. Based on the distributions of objective motorcycles’ and Ebikes' positions in collisions with passenger cars, the maximum longitudinal distance is 60 m for both types of accidents and the maximum lateral distance ranges from −20 m to 20 m and from −15 m to 15 m, respectively.
Research on the evolutionary game of the supervision of civil aviation dangerous goods transportation training
Authors: Shen Haibin , Zhao Shengnan 
Published: December 2022

Abstract
This study is carried out to promote the precise supervision of dangerous goods transportation training, improve the efficiency of civil aviation supervision and further ensure the safety of air transportation. First, from the perspective of behaviour interaction and interest demands, evolutionary game theory is used to construct a tripartite evolutionary game model of dangerous goods transportation training institutions, the Civil Aviation Administration of China (CAAC) and the public. Then, the evolutionary game equilibrium of the system is further analysed under the joint action of the three parties. Finally, the influences of important parameters of the model on the behavioural strategy selection of the three parties are investigated via MATLAB numerical simulation. The conclusions reveal that the system has three evolutionarily stable strategies under different parameters, namely (non-compliant training, supervision, non-participation in supervision), (non-compliant training, supervision, participation in supervision) and (compliant training, supervision, non-participation in supervision). Moreover, the CAAC supervision cost, the fine amount, the supervision cost of public participation, the supervision success rate and the reporting reward amount are the main parameters that affect the behavioural strategy selection of the tripartite game players. The conclusions and suggestions of this study provide a decision-making basis and guidance for the supervision and management of civil aviation dangerous goods transportation training.