Colorectal cancer’s burden attributable to a diet high in processed meat in the Belt and Road Initiative countries

BACKGROUND Colorectal cancer(CRC)plays a significant role in morbidity,mortality,and economic cost in the Belt and Road Initiative(“B and R”)countries.In addition,these countries have a substantial consumption of processed meat.However,the burden and trend of CRC in relation to the consumption of a diet high in processed meat(DHPM-CRC)in these“B and R”countries remain unknown.AIM To analyze the burden and trend of DHPM-CRC in the“B and R”countries from 1990 to 2019.METHODS We used the 2019 Global Burden of Disease Study to collate information regarding the burden of DHPM-CRC.Numbers and age-standardized rates(ASRs)of deaths along with the disability-adjusted life years(DALYs)were determined among the“B and R”countries in 1990 and 2019.Using joinpoint regression analysis,the average annual percent change(AAPC)was used to analyze the temporal trends of age-standardized DALYs rate(ASDALR)from 1990 to 2019 and in the final decade(2010–2019).RESULTS We found geographical differences in the burden of DHPM-CRC among“B and R”countries,with the three highest-ranking countries being the Russian Federation,China,and Ukraine in 1990,and China,the Russian Federation,and Poland in 2019.The burden of DHPM-CRC generally increased in most member countries from 1990 to 2019(all P<0.05).The absolute number of deaths and DALYs in DHPM-CRC were 3151.15[95%uncertainty interval(UI)665.74-5696.64]and 83249.31(95%UI 15628.64-151956.31)in China in 2019.However,the number of deaths(2627.57-2528.51)and DALYs(65867.39-55378.65)for DHPM-CRC in the Russian Federation has declined.The fastest increase in ASDALR for DHPM-CRC was observed in Vietnam,Southeast Asia,with an AAPC value of 3.90%[95%confidence interval(CI):3.63%-4.16%],whereas the fastest decline was observed in Kyrgyzstan,Central Asia,with an AAPC value of-2.05%(95%CI:-2.37%to-1.73%).A substantial upward trend in ASR of mortality,years lived with disability,years of life lost,and DALYs from DHPM-CRC changes in 1990-2019 and the final decade(2010-2019)for most Maritime Silk Route members in East Asia,South Asia,Southeast Asia,North Africa,and the Middle East,as well as Central Europe,while those of the most Land Silk Route members in Central Asia and Eastern Europe have decreased markedly(all P<0.05).The ASDALR for DHPM-CRC increased more in males than in females(all P<0.05).For those aged 50-74 years,the ASDALR for DHPM-CRC in 40 members exhibited an increasing trend,except for 20 members,including 7 members in Central Asia,Maldives,and 12 high or high-middle social development index(SDI)members in other regions(all P<0.05).CONCLUSION The burden of DHPM-CRC varies substantially across“B and R”countries and threatens public health.Relevant evidence-based policies and interventions tailored to the different trends of countries in SDIs or Silk Routes should be adopted to reduce the future burden of CRC in“B and R”countries via extensive collaboration.

A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed

In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed(DHPFSP-VPS),considering both the minimum makespan and total energy consumption(TEC)as objectives.A discrete multi-objective squirrel search algorithm(DMSSA)is proposed to solve the DHPFSPVPS.DMSSA makes four improvements based on the squirrel search algorithm.Firstly,in terms of the population initialization strategy,four hybrid initialization methods targeting different objectives are proposed to enhance the quality of initial solutions.Secondly,enhancements are made to the population hierarchy system and position updating methods of the squirrel search algorithm,making it more suitable for discrete scheduling problems.Additionally,regarding the search strategy,six local searches are designed based on problem characteristics to enhance search capability.Moreover,a dynamic predator strategy based on Q-learning is devised to effectively balance DMSSA’s capability for global exploration and local exploitation.Finally,two speed control energy-efficient strategies are designed to reduce TEC.Extensive comparative experiments are conducted in this paper to validate the effectiveness of the proposed strategies.The results of comparing DMSSA with other algorithms demonstrate its superior performance and its potential for efficient solving of the DHPFSP-VPS problem.

Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

基于Swin Transformer的沥青路面病害分类检测研究

针对传统卷积神经网络模型在沥青路面病害检测中识别长距离裂缝结构能力不足以及面临的精度局限问题,引入Swin Transformer模型进行沥青路面病害分类研究;首先对于路面检测车采集到的沥青路面扫描图像对比度低的问题,使用直方图均衡技术处理图像,增加图像可视化效果;其次,选取3种经典卷积神经网络模型作为对比模型,并在训练过程中采用更换损失函数,调整预训练模型等手段解决过拟合问题;并选用准确率、查全率、F1-score作为评价指标;在最终实验结果中Swin Transformer识别准确率达到了80.6%,F1-score达到了0.776,不仅在整体分类准确率上超越了传统CNN模型,并且对具有长距离特征结构的病害方面具有更高的识别准确率,同时具有良好的可靠性。

A Memorable Journey of Self- searching in Jack Kerouac's On the Road

hrough the across-America-journey, in Jack Kerouac's renowned novel, On the Road, Sal Paradise and his friends accomplished a self-searching and truth-searching process.

Evaluation of the Safety of Mine Road Based on Fuzzy Analytic Hierarchy Process

Generally, mine roads are located in the mountain areas, as its complex topography, mostly along the river near the cliffs, steep bend anxious, the mine road design has to adopt lower technical standards relatively and usually is lack of traffic safety facilities. Especially, there are mainly medium-sized vehicles on mine road, under the heavy traffic vehicles affect repeatedly, high frequency of traffic accidents more easily happen in mine road area and cause serious effects on life or property. Combining with the particularity of mine road safety environment, this paper studies the basic theory of safety evaluation, analyses the factors of traffic safety design and special mine terrain conditions, and then establishes mine road safety index system and evaluation model based on the principles such as systematicness, independent indexes, qualitative and quantitative analysis, feasibility, scientificity and reliability. At last, the paper successfully evaluates the safety of road in Huang Mailing phosphate rock area with fuzzy AHP method based on engineering project.

SIMULATION ANALYSIS OF INFLUENCE OF ROAD SURFACE ROUGHNESS ON TYRE DYNAMIC PERFORMANCE IN AUTOMOTIVE BRAKING

Using a nonlinear time varying tyre model, this paper simulatively analyzes the influence of road surface roughness amplitude and road spatial frequency on automobile ground adhesion ability. The result shows that with the increase of road surface roughness, the tyre adhesion ability declines, and the automotive braking distance increases. Moreover, the reliability of the nonlinear time varying tyre model in reflecting the influence of the road surface roughness is validated. It is testified that this model is an effective dynamic one in the simulation of automotive braking performance on uneven road.

Materials,preparation,performances and mechanism of polyurethane modified asphalt and its mixture:A systematic review

With the rapid development of asphalt pavement technology,it has attracted considerable attention to improving the durability of asphalt pavement.An effective action is to use modified asphalt with high performance and durability.Polyurethane(PU)has been used in asphalt pavement engineering to enhance the durability and service life of asphalt pavement because of its excellent high-temperature performance,toughness,wear resistance,aging resistance and oil resistance.However,PU modified asphalt technology is still in the exploratory stage.The preparation,modification mechanism and working performances of PU modified asphalt need to be further clarified.Therefore,this paper summarized the research progress of PU modified asphalt and its mixture.The composition of PU modified asphalt was introduced.The addition methods of PU materials and preparation process parameters of the PU modified asphalt were determined.The modification mechanism of PU on asphalt was discussed.The effects of polyurethane on asphalt were analyzed and the road performances of its mixture were evaluated.Finally,the development tendency towards PU modified asphalt and its mixture were forecasted.

Automatic Clustering of User Behaviour Profiles for Web Recommendation System

Web usage mining,content mining,and structure mining comprise the web mining process.Web-Page Recommendation(WPR)development by incor-porating Data Mining Techniques(DMT)did not include end-users with improved performance in the obtainedfiltering results.The cluster user profile-based clustering process is delayed when it has a low precision rate.Markov Chain Monte Carlo-Dynamic Clustering(MC2-DC)is based on the User Behavior Profile(UBP)model group’s similar user behavior on a dynamic update of UBP.The Reversible-Jump Concept(RJC)reviews the history with updated UBP and moves to appropriate clusters.Hamilton’s Filtering Framework(HFF)is designed tofilter user data based on personalised information on automatically updated UBP through the Search Engine(SE).The Hamilton Filtered Regime Switching User Query Probability(HFRSUQP)works forward the updated UBP for easy and accuratefiltering of users’interests and improves WPR.A Probabilistic User Result Feature Ranking based on Gaussian Distribution(PURFR-GD)has been developed to user rank results in a web mining process.PURFR-GD decreases the delay time in the end-to-end workflow for SE personalization in various meth-ods by using the Gaussian Distribution Function(GDF).The theoretical analysis and experiment results of the proposed MC2-DC method automatically increase the updated UBP accuracy by 18.78%.HFRSUQP enabled extensive Maximize Log-Likelihood(ML-L)increases to 15.28%of User Personalized Information Search Retrieval Rate(UPISRT).For feature ranking,the PURFR-GD model defines higher Classification Accuracy(CA)and Precision Ratio(PR)while uti-lising minimum Execution Time(ET).Furthermore,UPISRT's ranking perfor-mance has improved by 20%.

Development of Search System Used for Material Processing by Mobile Internet

A wireless search system was integrated on Windows 2000 server.Based on the communication principle between wireless data and Internet,the object expression of search file,the automatic query of document information,the segment browsing of result information,and the receiving and sending of user information were realized by using Active Server Page 3.0,VB Script,WML Script insert languages and object orient database technology.The requirement querying information of material processing through Internet by GPRS,WAP mobile handset and so on was accomplished.

Design and Implementation of a New Chinese Word Segmentation Dictionary for the Personalized Mobile Search

Chinese word segmentation is the basis of natural language processing. The dictionary mechanism significantly influences the efficiency of word segmentation and the understanding of the user’s intention which is implied in the user’s query. As the traditional dictionary mechanisms can't meet the present situation of personalized mobile search, this paper presents a new dictionary mechanism which contains the word classification information. This paper, furthermore, puts forward an approach for improving the traditional word bank structure, and proposes an improved FMM segmentation algorithm. The results show that the new dictionary mechanism has made a significant increase on the query efficiency and met the user’s individual requirements better.

Development of a Web-Based Decision Support System for Cell Formation Problems Considering Alternative Process Routings and Machine Sequences

In this study, we use the respective advantages of the tabu search (TS) and the Web-based technologies to develop a Web-based decision support system (DSS) for cell formation (CF) problems considering alternative process routings and machine sequences simultaneously. With the assistance of our developed Web-based system, the CF practitioners in the production departments can interact with the systems without knowing the details of algorithms and can get the best machine cells and part families with minimize the total intercellular movement wherever and whenever they may need it. To further verify the feasibility and effectiveness of the system developed, an example taken from the literature is ado- pted for illustrational purpose. Moreover, a set of test problems with various sizes drawn from the literature is used to test the performance of the proposed system. Corresponding results are compared to several well-known algorithms previously published. The results indicate that the proposed system improves the best results found in the literature for 67% of the test problems. These show that the proposed system should thus be useful to both practitioners and researchers.

Storing and Searching Metadata for Digital Broadcasting on Set-Top Box Environments

Digital broadcasting is a novel paradigm for the next generation broadcasting. Its goal is to provide not only better quality of pictures but also a variety of services that is impossible in traditional airwaves broadcasting. One of the important factors for this new broadcasting environment is the interoperability among broadcasting applications since the environment is distributed. Therefore the broadcasting metadata becomes increasingly important and one of the metadata standards for a digital broadcasting is TV-Anytime metadata. TV-Anytime metadata is defined using XML schema, so its instances are XML data. In order to fulfill interoperability, a standard query language is also required and XQuery is a natural choice. There are some researches for dealing with broadcasting metadata. In our previous study, we have proposed the method for efficiently managing the broadcasting metadata in a service provider. However, the environment of a Set-Top Box for digital broadcasting is limited such as low-cost and low-setting. Therefore there are some considerations to apply general approaches for managing the metadata into the Set-Top Box. This paper proposes a method for efficiently managing the broadcasting metadata based on the Set-Top Box and a prototype of metadata management system for evaluating our method. Our system consists of a storage engine to store the metadata and an XQuery engine to search the stored metadata and uses special index for storing and searching. Our two engines are designed independently with hardware platform therefore these engines can be used in any low-cost applications to manage broadcasting metadata.

Optimization and Process Design Tools for Estimation of Weekly Exposure to Air Pollution Integrating Travel Patterns during Pregnancy

A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution throughout everyday life. In the literature, the most commonly used estimate is based on home address only or taking into account, in addition, the work address. However, several studies have shown the importance of daily mobility in the estimate of exposure to air pollutants. In this context, we developed an R procedure that estimates individual exposures combining home addresses, several important places, and itineraries of the principal mobility during a week. It supplies researchers a useful tool to calculate individual daily exposition to air pollutants weighting by the time spent at each of the most frequented locations (work, shopping, residential address, etc.) and while commuting. This task requires the efficient calculation of travel time matrices or the examination of multimodal transport routes. This procedure is freely available from the Equit’Area project website: (https://www.equitarea.org). This procedure is structured in three parts: the first part is to create a network, the second allows to estimate main itineraries of the daily mobility and the last one tries to reconstitute the level of air pollution exposure. One main advantage of the tool is that the procedure can be used with different spatial scales and for any air pollutant.

Prospects of Partial Substitution of Cement with Rice Husk Ash for Road Concrete Works

Rice Husk Ash(RHA)has been found as a potential partial replacement for cement in concrete.This study attempts to make an evidence based evaluation of the sustainability and benefits of RHA utilisation as partial replacement of cement in road concrete works within Anambra State of Nigeria.The ashes of the rice husks collected from different locations were characterised.Direct interviews were conducted among the rice mill personnel and experts in the construction companies.The values of SiO2+Fe2O3+Al2O3 for the four analysed RHA samples ranged from 78.9%to 80.3%as revealed by the X-ray fluorescence analysis.This confirms that they are pozzolanic.The highest observed 28th day compressive strength of concrete was 41.8 N/mm2 for the concrete containing 10%RHA.Beyond the 10%replacement level,the compressive strength dropped below the control values.The result of the Analytical Hierarchy Process(AHP)analysis displayed the highest option preference of 40.3%for utilising RHA in road construction.These show that utilising RHA for road concrete works would be a sustainable option.10%replacement of cement with RHA was recommended for optimum performance based on the compressive strengths of the tested RHA based concretes.

基于SSA和双稳随机共振的车削颤振微弱特征提取

围绕车削颤振激发过程,针对车削颤振过渡阶段特征微弱且存在噪声和转频干扰的问题,提出一种基于麻雀优化算法(sparrow search algorithm, SSA)和双稳随机共振(bistable stochastic resonance, BSR)系统的车削颤振微弱特征提取方法。该方法利用SSA优良的寻优特性,以信噪比作为优化指标确定最佳BSR系统参数,用优化后的参数对车削颤振信号进行滤波处理,提取颤振特征频率。仿真试验表明SSA-BSR方法可以实现对强噪声背景下微弱特征信号的提取与增强,同时兼顾寻优速度快和获得全局最优解概率高的优点。开展车削颤振检测试验,颤振激发过程的加速度信号图谱分析结果验证了车削颤振特征频率幅值与颤振激发程度之间的相关性;不同模型在车削颤振过渡阶段特征提取的对比结果验证了SSA-BSR模型的有效性和优越性,并且能够满足车削颤振检测对实时性的要求,实现在进入剧烈颤振阶段前发出预警,为量化车削颤振和车削颤振在线监测提供一种新思路。

基于VMD-SSA-LSTM考虑刀具磨损的数控铣床切削功率预测模型研究

传统的切削过程功率获取需要基于复杂的切削功率模型且很少考虑刀具磨损的影响,针对此设计了一种基于变分模态分解(VMD)、麻雀搜索算法(SSA)、长短时记忆(LSTM)神经网络的考虑刀具磨损的数控铣床切削功率预测模型,该模型无需解构数控铣床运行过程的能耗机理,基于一次性的历史实验数据即可实现数控铣床切削过程功率的高精度预测。首先,采用人工智能机器视觉技术对刀具磨损图片进行分析处理,获取刀具磨损图像的数字化特征,从而得到刀具最大磨损量;然后,建立基于VMD-SSA-LSTM考虑刀具磨损的数控铣床切削功率预测模型,利用VMD对数控铣床运行数据进行分解,采用SSA算法对LSTM神经网络超参数进行寻优,并将分解出的铣床运行数据分量输入到LSTM神经网络中,接着将每个分量的预测值相加,得到切削功率预测值;最后以面铣加工为例,将所提出的预测模型与BP神经网络、LSTM神经网络和传统模型进行对比分析,验证了所提模型的有效性和优越性。

Progressive LiDAR Adaptation for Road Detection

Despite rapid developments in visual image-based road detection, robustly identifying road areas in visual images remains challenging due to issues like illumination changes and blurry images. To this end, LiDAR sensor data can be incorporated to improve the visual image-based road detection,because LiDAR data is less susceptible to visual noises. However,the main difficulty in introducing LiDAR information into visual image-based road detection is that LiDAR data and its extracted features do not share the same space with the visual data and visual features. Such gaps in spaces may limit the benefits of LiDAR information for road detection. To overcome this issue, we introduce a novel Progressive LiDAR adaptation-aided road detection(PLARD) approach to adapt LiDAR information into visual image-based road detection and improve detection performance. In PLARD, progressive LiDAR adaptation consists of two subsequent modules: 1) data space adaptation, which transforms the LiDAR data to the visual data space to align with the perspective view by applying altitude difference-based transformation; and 2) feature space adaptation, which adapts LiDAR features to visual features through a cascaded fusion structure. Comprehensive empirical studies on the well-known KITTI road detection benchmark demonstrate that PLARD takes advantage of both the visual and LiDAR information, achieving much more robust road detection even in challenging urban scenes. In particular, PLARD outperforms other state-of-theart road detection models and is currently top of the publicly accessible benchmark leader-board.

基于HFACS的道路运输事故致因分析与分类系统研究

为了深入研究道路运输事故的致因因素,挖掘出关键致因规则,在人因分析和分类系统(HFACS)的基础上,构建道路运输事故致因分析与分类系统(RTAACS),并根据该系统框架对收集到的事故进行分析。首先将RTAACS框架分为监管部门、道路运输企业、驾驶人3个层级,将事故致因因素纳入该系统框架进行频率统计,通过R语言改进卡方检验、让步比分析得出致因因素之间的关联规则,最后根据ANP网络层次分析法计算各项致因因素的权重,并确定关键致因规则。结果表明:工作流程与不充分的企业监督、工具技术与习惯性违规、资源管理与工具技术、资源管理与习惯性违规、未纠正的已知错误与习惯性违规为道路运输事故的关键致因规则。研究构建的系统框架以及提出的分析方法为道路运输业的安全预防提供一定的借鉴意义。

Automatic Extraction of Urban Road Centerlines from High-Resolution Satellite Imagery Using Automatic Thresholding and Morphological Operation Method

The commercial high-resolution imaging satellite with 1 m spatial resolution IKONOS is an important data source of information for urban planning and geographical information system (GIS) applications. In this paper, a morphological method is proposed. The proposed method combines the automatic thresholding and morphological operation techniques to extract the road centerline of the urban environment. This method intends to solve urban road centerline problems, vehicle, vegetation, building etc. Based on this morphological method, an object extractor is designed to extract road networks from highly remote sensing images. Some filters are applied in this experiment such as line reconstruction and region filling techniques to connect the disconnected road segments and remove the small redundant. Finally, the thinning algorithm is used to extract the road centerline. Experiments have been conducted on a high-resolution IKONOS and QuickBird images showing the efficiency of the proposed method.