Knowledge, Attitudes and Practices Relating to HIV among Motorbike Taxi Drivers in Parakou, Benin, in 2021

Background and Objective: HIV infection is a major global Public Health threat worldwide, particularly in Sub-Saharan Africa of which Benin. The level of knowledge determines the attitudes and behaviors of the populations towards this infection. The study objective was to assess knowledge, attitudes and practices related to HIV infection among motorbike taxi drivers (MTD) in Parakou in 2021. Methods: This was a descriptive cross-sectional study targeting MTD in Parakou in 2021. Participants were selected by cluster sampling. Pretested Digitized questionnaire using KoboCollect@ applicationserved as a data collection tool. Knowledge, attitudes and practices variable were treated on a score scale. A knowledge score was considered to reflect a good knowledge of HIV if at least two-thirds of the knowledge statements had been correctly answered provided the subject recognized the sexual route as one of modes of HIV transmission, identified at least one preventive measure and meant the incurability of the disease. Quantitative and qualitative variables were appropriately described using the EPI Info 7.1.3.3 software. The participant was classified at positive attitude/practice for HIV prevention, when it has a score of at least 80% and suggests a good preventive measure face a risk of exposure to HIV. Results: A total of 374 subjects were recruited into the study. The mean age was 31.51 ± 7.76 years. Most participants (86.06%) had good knowledge of condom use as an HIV prevention method. The sources of information mentioned were mainly the media (77.07%), relatives or friends (63.38%), and field-workers from non-governmental organizations (37.26%). Routine HIV testing was 50.53%. Among participants, 76.10% reported at least two different sexual partners. Condom use was 59.18 % during the casual sexual intercourse. Within the client-provider relationship with female sex workers, 33.17% had had sexual intercourse with them. The sexual route was the most cited (92.99%), and 90.23% stated that HIV infection can be stabilized by medication in a health structure. Conclusion: The level of knowledge of motorbike taxi drivers in Parakou does not match their behavior with regard to HIV prevention. Appropriate strategies are needed to develop prevention skills in this population. To effectively comb at HIV, it will be necessary to strengthen the targeted HIV preventive interventions at key and bridge populations including motorbike taxi drivers in Benin.

Taxi origin and destination demand prediction based on deep learning:a review

Taxi demand prediction is a crucial component of intelligent transportation system research.Compared to region-based demand prediction,origin-destination(OD)demand prediction has a wide range of potential applications,including real-time matching,idle vehicle allocation,ridesharing services,and dynamic pricing,among others.However,because OD demand involves complex spatiotemporal dependence,research in this area has been limited thus far.In this paper,we first review existing research from four perspectives:topology construction,temporal and spatial feature processing,and other relevant factors.We then elaborate on the advantages and limitations of OD prediction methods based on deep learning architecture theory.Next,we discuss ongoing challenges in OD prediction,such as dynamics,spatiotemporal dependence,semantic differentiation,time window selection,and data sparsity problems,and summarize and compare potential solutions to each challenge.These findings offer valuable insights for model selection in OD demand prediction.Finally,we provide public datasets and open-source code,along with suggestions for future research directions.

木聚糖酶TAXI型抑制蛋白的研究进展

木聚糖酶是一种重要的半纤维素酶,广泛用于饲料工业。近年来在小麦中发现一类能抑制木聚糖酶活性的蛋白,这类抑制蛋白可能会对木聚糖酶的应用效果产生影响。目前发现在不同的谷物中共存在2种类型的木聚糖酶抑制蛋白,根据其结构的不同,分为TAXI型(triticum aestivum xylanase inhibitor)和XIP型(xylanase inhibi-tor protein)。本文主要简述了TAXI型抑制蛋白的分子结构、抑制特性和活性影响因素等方面的研究进展,对于深入研究木聚糖酶及其活性影响因子,充分开发利用我国饲料资源和促进畜牧业生产可持续发展具有重要现实意义。

木聚糖酶TAXI型抑制剂及基因工程研究

谷物中存在2种类型的木聚糖酶抑制剂,根据其结构的不同可分为TAXI型和XIP型。本文主要简述了木聚糖酶TAXI型抑制剂对木聚糖酶的抑制特性及其基因工程研究。

语义数据模型及其建模的探讨

本文首先介绍ＴＡＸＩＳ语言的主要特性，然后阐述ＴＡＸＩＳ建模的方法及ＴＡＸＩＳ系统的特点。

木聚糖酶抑制蛋白的研究进展

简要介绍了三类木聚糖酶抑制蛋白的分子结构、抑制特性及其在谷物中的抗病防御作用。

抗抑制活性木聚糖酶研究进展

麦类饲料含非淀粉多糖(NSP)抗营养因子,严重影响麦类饲料的饲喂价值。添加木聚糖酶能减轻饲料中NSP的抗营养作用,但是麦类饲料中的木聚糖酶抑制蛋白会抑制外源添加的微生物来源木聚糖酶的活性,抗抑制性木聚糖酶的使用具有明显优势。文章综述谷物中存在的木聚糖酶抑制蛋白对外源添加木聚糖酶的抑制作用、抗抑制性木聚糖酶的潜在应用价值、研究现状及应用前景,以期麦类饲料能更好地在畜禽日粮中添加应用。

Green Aircraft Taxiing Strategy Based on Multi-scenario Joint Optimization

The issue of green aircraft taxiing under various taxi scenarios is studied to improve the efficiency of aircraft surface operations and reduce environmental pollution around the airport from aircraft emissions.A green aircraft taxi programming model based on multi-scenario joint optimization is built according to airport surface network topology modeling by analyzing the characteristics of aircraft operations under three different taxiing scenarios:all-engine taxi,single-engine taxi,and electronic taxi.A genetic algorithm is also used in the model to minimize fuel consumption and pollutant emissions.The Shanghai Pudong International Airport is selected as a typical example to conduct a verification analysis.Compared with actual operational data,the amount of aircraft fuel consumption and gas emissions after optimization are reduced significantly through applying the model.Under an electronic taxiing scenario,fuel consumption can be lowered by 45.3%,and hydrocarbon(HC)and carbon dioxide(CO)emissions are decreased by 80%.The results show that a green aircraft taxiing strategy that integrates taxiway optimization and electronic taxiing can effectively improve the efficiency of airport operations and reduce aircraft pollution levels in an airport′s peripheral environment.

Analyzing Cross-domain Transportation Big Data of New York City with Semi-supervised and Active Learning

The majority of big data analytics applied to transportation datasets suffer from being too domain-specific,that is,they draw conclusions for a dataset based on analytics on the same dataset.This makes models trained from one domain(e.g.taxi data)applies badly to a different domain(e.g.Uber data).To achieve accurate analyses on a new domain,substantial amounts of data must be available,which limits practical applications.To remedy this,we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task:Selectively choosing a small amount of datapoints from a new domain while achieving comparable performances to using all the datapoints.We choose the New York City(NYC)transportation data of taxi and Uber as our dataset,simulating different domains with 90%as the source data domain for training and the remaining 10%as the target data domain for evaluation.We propose semi-supervised and active learning strategies and apply it to the source domain for selecting datapoints.Experimental results show that our adaptation achieves a comparable performance of using all datapoints while using only a fraction of them,substantially reducing the amount of data required.Our approach has two major advantages:It can make accurate analytics and predictions when big datasets are not available,and even if big datasets are available,our approach chooses the most informative datapoints out of the dataset,making the process much more efficient without having to process huge amounts of data.

Safety analysis of wheel brake system based on STAMP/STPA and Monte Carlo simulation

The wheel brake system safety is a complex problem which refers to its technical state, operating environment, human factors, etc., in aircraft landing taxiing process. Usually, professors consider system safety with traditional probability techniques based on the linear chain of events. However, it could not comprehensively analyze system safety problems, especially in operating environment, interaction of subsystems, and human factors. Thus,we consider system safety as a control problem based on the system-theoretic accident model, the processes(STAMP) model and the system theoretic process analysis(STPA) technique to compensate the deficiency of traditional techniques. Meanwhile,system safety simulation is considered as system control simulation, and Monte Carlo methods are used which consider the range of uncertain parameters and operation deviation to quantitatively study system safety influence factors in control simulation. Firstly,we construct the STAMP model and STPA feedback control loop of the wheel brake system based on the system functional requirement. Then four unsafe control actions are identified, and causes of them are analyzed. Finally, we construct the Monte Carlo simulation model to analyze different scenarios under disturbance. The results provide a basis for choosing corresponding process model variables in constructing the context table and show that appropriate brake strategies could prevent hazards in aircraft landing taxiing.

Real-Time Four-Dimensional Trajectory Generation Based on Gain-Scheduling Control and a High-Fidelity Aircraft Model

Aircraft ground movement plays a key role in improving airport efficiency,as it acts as a link to all other ground operations.Finding novel approaches to coordinate the movements of a fleet of aircraft at an airport in order to improve system resilience to disruptions with increasing autonomy is at the center of many key studies for airport airside operations.Moreover,autonomous taxiing is envisioned as a key component in future digitalized airports.However,state-of-the-art routing and scheduling algorithms for airport ground movements do not consider high-fidelity aircraft models at both the proactive and reactive planning phases.The majority of such algorithms do not actively seek to optimize fuel efficiency and reduce harmful greenhouse gas emissions.This paper proposes a new approach for generating efficient four-dimensional trajectories(4DTs)on the basis of a high-fidelity aircraft model and gainscheduling control strategy.Working in conjunction with a routing and scheduling algorithm that determines the taxi route,waypoints,and time deadlines,the proposed approach generates fuel-efficient 4DTs in real time,while respecting operational constraints.The proposed approach can be used in two contexts:①as a reactive decision support tool to generate new trajectories that can resolve unprecedented events;and②as an autopilot system for both partial and fully autonomous taxiing.The proposed methodology is realistic and simple to implement.Moreover,simulation studies show that the proposed approach is capable of providing an up to 11%reduction in the fuel consumed during the taxiing of a large Boeing 747-100 jumbo jet.

自动驾驶出租车远程遥控驾驶研究

自动驾驶出租车(Robo Taxi)作为未来自动驾驶商业化落地的典型应用场景,在5G网络的赋能下可以实现远程遥控驾驶的功能,为自动驾驶出租车的安全行驶提供冗余保障。首先针对自动驾驶出租车国内外的发展现状进行介绍;然后结合自动驾驶出租车远程遥控驾驶的情况,梳理远程遥控驾驶的需求及政策,分析自动驾驶出租车远程遥控驾驶的技术进展和应用现状;最后针对目前面临的问题和挑战,给出自动驾驶出租车远程遥控驾驶后续的研究思路。

基于嵌入式的工业园区智能导航系统设计

针对工业园区信息导航现状,提出了基于嵌入式的综合信息智能导航系统。采用LPC2478微处理器,在Linux操作系统下,以嵌入式图形开发平台MiniGUI为开发环境,实现了电子地图的缩放、漫游、最优路径查询等功能;通过网关将系统接入Internet,采用流式socket编程,实现了Taxi呼叫系统。该系统具有良好的推广应用价值。

Blockchain and Machine Learning for Intelligent Multiple Factor-Based Ride-Hailing Services

One of the common transportation systems in Korea is calling taxis through online applications,which is more convenient for passengers and drivers in the modern area.However,the driver’s passenger taxi request can be rejected based on the driver’s location and distance.Therefore,there is a need to specify driver’s acceptance and rejection of the received request.The security of this systemis anothermain core to save the transaction information and safety of passengers and drivers.In this study,the origin and destination of the Jeju island SouthKorea were captured from T-map and processed based on machine learning decision tree and XGBoost techniques.The blockchain framework is implemented in the Hyperledger Fabric platform.The experimental results represent the features of socio-economic.The cross-validation was accomplished.Distance is another factor for the taxi trip,which in total trip in midnight is quite shorter.This process presents the successful matching of ride-hailing taxi services with the specialty of distance,the trip request,and safety based on the total city measurement.

Control Research for a Small Fixed-Wing UAV DuringGround Taxiing

Ground taxiing is the key process of take-off and landing for a tricycle-undercarriage unmanned aerial vehicle( UAV). Nonlinear model of a sample UAV is established based on stiffness and damping model of landing gears and tires taken into account. Then lateral nonlinear model is linearized and state space equations are deduced by using nose wheel and ruder as inputs and lateral states as outputs. Adaptive internal model control( AIMC) is proposed and applied to lateral control based on decoupled and linearized dynamic model during ground taxiing process. Different control strategies are analyzed and compared by simulations,and then a combined control strategy of nose wheel steering with holding and rudder control is given. Hardware in loop simulations( HILS) proves the validity of the controller designed.

Selectivity Analysis of Grapholitha molesta(Busck) for Different Pear Varieties

Through analysis of trap catches and fruit decay rate of different pear varieties,it was found that there were significant differences in parasitization of Grapholitha molesta（ Busck） among different pear varieties. The trap catches of Huangguan pear was the highest; the fruit decay rate of Xueqing pear was extremely higher than those of other varieties; the trap catches of early red comice were significantly lower than those of other varieties,and no injured fruits were found.

A Comprehensive Taxi Assessment Index Using Floating Car Data

With the expansion of urban area and development of taxi system,problems arise,such as low operation efficiency,high taxi idling rate,and long passenger waiting-time. Although various studies have been conducted,only limited overview of the factors towards urban taxi system has been provided. Consequently,a comprehensive evaluation of taxi system is essential for the urban planner to analyze the current situation and take effective measures. This paper,by using Floating Car Data( FCD),proposes a Comprehensive Taxi Assessment Index( CTAI) to quantify the quality of existing urban taxi system with the assistance of Geographic Information System( GIS) technology. The proposed index system extracts and classifies key factors,reflecting the taxi system from the perspectives of operation efficiency,customer and taxi-driver satisfaction. The system contributes to improving the organization and operation of urban taxi system. Based on the data obtained from the city of Shenzhen,Guangdong Province,China,for both weekday and weekends( Dec.,2011),the proposed CTAI was illustrated by using the Principal Component Analysis( PCA) with ArcGIS 10. 0 platform. The results indicate that the system provides a good multi-dimensional view to delve into the existing urban taxi operation, thus to point out the most sensitive indices towards the entire system,which consequently provides guidelines for future improvement and management of urban taxi system.

Analysis of Host Selectivity and Taxis of Grapholita molesta in Different Peach Varieties

[Objective]The paper was to preliminarily determine the susceptible varieties of Grapholita molesta(Busck)by analyzing trap catches of peach trees at different ripening stages,new shoot damage rate and fruit damage rate at different development stages.[Method]Three traps were hanged in peach orchard of the same variety,with the interval of 30 m.The traps were fixed on ventilated and shaded branches for regular and fixed-point monitoring.Three trees were randomly selected from each variety to investigate the damage fruit rate and new shoot damage rate at east,south,west and north directions of each tree,and the number of infected fruits and damaged new shoots was recorded.[Result]There were obvious differences in taxis selection of G.molesta to different peach varieties,and the trap catches in the same variety varied among different periods.The damage caused by G.molesta in the same variety over the same period was different among different organs.The catch peak of late ripening peach 03-46-78 appeared on August 11.In summer shoot period,the trap catches of late ripening peach 03-46-78 were extremely higher than those of other varieties,and the damage rate of late ripening peach Jinyuan was extremely higher than that of other varieties.In autumn shoot period,the average trap catches of late ripening peach 03-46-78 were significantly higher than those of other varieties,and the damage rate of late ripening peach Jinyuan was significantly higher than that of other varieties.The investigation and analysis of different ripening stages of peach fruits showed that the damage rate of late ripening variety Ruiguang 39 was significantly higher than that of other varieties in the ripening stage.The trap catches of late ripening peach 03-46-78 were significantly higher than those of other varieties in the young fruit stage.The trap catches of late ripening peach 03-46-78 had significant difference with those of other varieties during fruit expansion stage.The trap catches of late ripening peach 03-46-78 had significant difference with that of other varieties during fruit ripening stage.[Conclusion]With the development of new shoots and the ripening of fruits,G.molesta appears different dynamic regularities in different organs of various varieties.The time point that G.molesta transfers with the development of fruit tree organs should be grasped to deeply analyze the physical and chemical properties of fruit trees during the growth period,so as to find out reasonable and effective prevention and control techniques for fruit farmers.

Developing a Comprehensive Taxi Strategy for Dubai: Based on System Analysis &Structured Assessment

Taxi plays an important role in providing passenger mobility. Taxi services are among the most frequently used passenger transport services in many cities in the world. Taxis are an integral part of a city’s image. In a recent IRU/EU report taxis are considered as part of the collective public transport chain. In this context taxis role is a complementary mobility option to public transport rather than a competitive one. In the growing city of Dubai taxis are utilized by many local and foreign residences as well as by tourists and visitors. The annual number of taxi trips reached 104 million trips in 2016, while the fleet is growing currently at 9613 and is expected to reach around 12,765 by 2020. Riding a taxi in Dubai is known to be pleasant, comfortable, convenient and relatively affordable experience. The Roads and Transport Authority (RTA) is the Dubai government authority responsible for the planning and governance of the taxi sector in Dubai. The RTA through its agency namely the Public Transport Agency (PTA) exercises such roles. This research is meant to provide a system analysis and structured assessment of the taxi sector in Dubai with the objective of identifying strengths and gaps as well as reviewing the literature and conducting stakeholder consultation hence culminating on developing a comprehensive taxi strategy in Dubai. Such strategy would be targeted to achieve customer satisfaction leading eventually to customer happiness. All in all this is expected to provide an added value and benefit to the business planning for PTA as well as for the overall strategic and futuristic planning by RTA.