Drone systems for delivering defibrillators for sudden cardiac arrests

Unmanned aerial vehicles(UAVs),or drones,that were initially developed for military use during World War I[1],have evolved into highly sophisticated aircraft that can be navigated remotely using global positioning systems.With constant improvements,drones have become more efficient,and cost-effective,with longer battery life and greater loading capacity.Today,UAVs have proven to be an effective and affordable solution for enhancing healthcare accessibility for patients who face geographical or infrastructural barriers.Using drone networks can greatly reduce the time transporting life-saving equipment,such as delivering automated external defibrillators(AEDs),to cardiac arrest victims,and can provide quick assistance to reduce travel time for the patients.

A Study on Optimizing the Double-Spine Type Flow Path Design for the Overhead Transportation System Using Tabu Search Algorithm

Optimizing Flow Path Design(FPD)is a popular research area in transportation system design,but its application to Overhead Transportation Systems(OTSs)has been limited.This study focuses on optimizing a double-spine flow path design for OTSs with 10 stations by minimizing the total travel distance for both loaded and empty flows.We employ transportation methods,specifically the North-West Corner and Stepping-Stone methods,to determine empty vehicle travel flows.Additionally,the Tabu Search(TS)algorithm is applied to branch the 10 stations into two main layout branches.The results obtained from our proposed method demonstrate a reduction in the objective function value compared to the initial feasible solution.Furthermore,we explore howchanges in the parameters of the TS algorithm affect the optimal result.We validate the feasibility of our approach by comparing it with relevant literature and conducting additional tests on layouts with 20 and 30 stations.

Transportation mobility during COVID-19:a systematic review and bibliometric analysis

The COVID-19 pandemic has significantly affected global transportation mobility,presenting unprecedented challenges to transportation management.Public transit and ride-hailing services saw a drastic reduction in ridership,leading to an increased inclination towards private vehicles.The pandemic also altered travel patterns and individual mobility due to various COVID-19 protocols.This study conducted a comprehensive review of 96 academic papers spanning from January 1,2020,to December 31,2022,focusing on transportation and mobility using the Scopus database.Three major themes were identified:‘Impact on Ride-Hailing Services',‘Impact on Mode Preference',and‘Impact on Trip Purpose',with subdivisions based on keywords and key findings extracted using VOSviewer.The pandemic significantly impacted ride-hailing services,altering demand,usage,and safety measures.Mode preference shifted towards private vehicles due to safety concerns.The present study underscores the long-term implications of the pandemic,emphasizing recovery strategies for ride-hailing services and mode preferences post-pandemic.It highlights the need for sustainable transportation policies,advocating for enhanced public transportation systems,promoting active travel modes,and addressing socioeconomic disparities in mobility patterns.The findings emphasize the need for resilient transportation strategies in the face of future disruptions.

Bolzano Traffic: An Example of Open ITS Deployment for Advanced Traveller Information Services

This paper aims to present the experience gathered in the Italian alpine city of Bolzano within the project“Bolzano Traffic”whose goal is the introduction of an experimental open ITS platform for local service providers,fostering the diffusion of advanced traveller information services and the future deployment of cooperative mobility systems in the region.Several end-users applications targeted to the needs of different user groups have been developed in collaboration with local companies and research centers;a partnership with the EU Co-Cities project has been activated as well.The implemented services rely on real-time travel and traffic information collected by urban traffic monitoring systems or published by local stakeholders(e.g.public transportation operators).An active involvement of end-users,who have recently started testing these demo applications for free,is actually on-going.

A mixed stochastic user equilibrium model considering influence of advanced traveller information systems in degradable transport network

Advanced traveler information systems （ATIS） can not only improve drivers＇ accessibility to the more accurate route travel time information, but also can improve drivers＇ adaptability to the stochastic network capacity degradations. In this paper, a mixed stochastic user equilibrium model was proposed to describe the interactive route choice behaviors between ATIS equipped and unequipped drivers on a degradable transport network. In the proposed model the information accessibility of equipped drivers was reflected by lower degree of uncertainty in their stochastic equilibrium flow distributions, and their behavioral adaptability was captured by multiple equilibrium behaviors over the stochastic network state set. The mixed equilibrium model was formulated as a fixed point problem defined in the mixed route flows, and its solution was achieved by executing an iterative algorithm. Numerical experiments were provided to verify the properties of the mixed network equilibrium model and the efficiency of the iterative algorithm.

ENTIRE SOLUTIONS OF LOTKA-VOLTERRA COMPETITION SYSTEMS WITH NONLOCAL DISPERSAL

This paper is mainly concerned with entire solutions of the following two-species Lotka-Volterra competition system with nonlocal(convolution)dispersals:{u_(t)=k*u-u+u(1-u-av),x∈R,t∈R,vt=d(k*v-v)+rv(1-v-bu),c∈R,t∈R.(0.1)Here a≠1,b≠1,d,and r are positive constants.By studying the eigenvalue problem of(0.1)linearized at(ϕc(ξ),0),we construct a pair of super-and sub-solutions for(0.1),and then establish the existence of entire solutions originating from(ϕc(ξ),0)as t→−∞,whereϕc denotes the traveling wave solution of the nonlocal Fisher-KPP equation ut=k*u−u+u(1−u).Moreover,we give a detailed description on the long-time behavior of such entire solutions as t→∞.Compared to the known works on the Lotka-Volterra competition system with classical diffusions,this paper overcomes many difficulties due to the appearance of nonlocal dispersal operators.

The Institut Pasteur of Côte D’Ivoire (Ivory Coast) in the Emergency Management of Air Travellers during the COVID-19 Pandemic: A Unique Experience in Supporting the Response Strategy in Côte D’Ivoire from 2021 to 2022

Since its outbreak in December 2019 in Wuhan Province (China), the Coronavirus (COVID-19) disease quickly spread around the world in such a way that most response plans were outdated. There was an urgent need to change and adapt response strategies as the virus globally spread. Entire firms and economies were brought to a standstill in order to reduce the virus’ capacity to spread and to limit some of the short-term impacts in order to save time and find out solutions to come back to a more or less normal way of life. Thus, most of the countries that closed their air, sea and land borders had to reopen them progressively, with travel restrictions submitted to rigid controls. In Côte d’Ivoire, as in all other countries, air travellers leaving the territory were required to provide a certificate for a negative COVID-19 test, valid for 24 to 72 hours depending on the country of destination. However, the national system implemented could not provide a result before 48 hours. The objective of this work was to develop an alternative strategy to the system for air travellers who were in a hurry and those who had a computer bug in obtaining their result. A total of 38,444 air travellers benefited from this strategy implemented by the Institut Pasteur de Côte d’Ivoire during these two years.

JINMAO TEX:Highlight products ring traveller,ring cup and reed

JINMAO TEX has three customer delighted products-ring traveller, ring and reed. They are all critical accessories to the quality and efficiency of spinning and weaving.

Fault Analysis and Structure Optimization of Traveling Transmission System of Shuttle Car

This paper firstly introduces the common faults of traveling transmission system of shuttle car.Secondly,by analyzing the characteristics of shuttle car structure,the layout of traveling transmission system and the common faults on shuttle car,this paper concludes that"internal holding torque"is the main cause of faults.Finally,this paper proposes a corresponding optimization design scheme to reduce the impact of"internal torque",and calculates the relevant results through the finite element simulation analysis method.Through these analyses and calculations,it is shown that the method can effectively reduce the probability of failure of traveling transmission system of shuttle car.

国际传播视域下“中国旅行”火爆的原因与启示

随着我国推出144小时过境免签政策,入境游的外国游客人次激增,“China Travel(中国旅行)”视频成为许多海外博主的“流量密码”。当前,全球信息传播秩序中官方国际舆论场的结构性导致中国国际形象被污名化,见证了中国真实情况的外国游客纷纷在短视频中驳斥西方错误叙事。同时,全球信息传播秩序中民间国际舆论场的贴近性是“中国旅行”视频爆火的重要原因。提升我国国际传播效能,既要加快构建多渠道、立体式对外传播格局,又要调适、完善中国话语和中国叙事体系。

文旅产业国际传播策略优化研究——基于YouTube#China travel视频用户评论语料分析

目的:了解外国游客对现有中国旅游业的评价与态度,是优化“媒体+文旅”形势下国际传播效果及文旅产业建设的重要佐证。方法:通过使用Gooseeker工具对YouTube #China travel和#144-hour标签下热门视频用户评价进行爬取和分析。结果:从受众视角揭示了我国现有文旅产业国际传播的现状及效果,为优化中国文旅产业国际传播策略提供数据支持。结论:面对外国社交媒体平台上“China travel”的爆火,我国的文旅产业建设及国际传播推广应从情感角度入手,把握受众的评价与态度,借助媒体融合的发展趋势建立细分化的国际传播矩阵。

“China Travel”打开中国国际传播新维度

随着中国免签“朋友圈”的不断扩容,越来越多的外国游客在72/144小时过境免签政策的鼓励下来到中国。外国游客沉浸体验实时现场展开的中国故事,“city不city”的“热梗”在网上病毒式传播,还在攀升中的“China Travel”正在打开中国国际传播的一个新维度。

ON MONOTONE TRAVELING WAVES FOR NICHOLSON'S BLOWFLIES EQUATION WITH DEGENERATE p-LAPLACIAN DIFFUSION

We study the existence and stability of monotone traveling wave solutions of Nicholson's blowflies equation with degenerate p-Laplacian diffusion.We prove the existence and nonexistence of non-decreasing smooth traveling wave solutions by phase plane analysis methods.Moreover,we show the existence and regularity of an original solution via a compactness analysis.Finally,we prove the stability and exponential convergence rate of traveling waves by an approximated weighted energy method.

Coexisting fast–slow dendritic traveling waves in a 3D-array electric field coupled neuronal network

Coexistence of fast and slow traveling waves without synaptic transmission has been found in hhhippocampal tissues,which is closely related to both normal brain activity and abnormal neural activity such as epileptic discharge. However, the propagation mechanism behind this coexistence phenomenon remains unclear. In this paper, a three-dimensional electric field coupled hippocampal neural network is established to investigate generation of coexisting spontaneous fast and slow traveling waves. This model captures two types of dendritic traveling waves propagating in both transverse and longitude directions: the N-methyl-D-aspartate(NMDA)-dependent wave with a speed of about 0.1 m/s and the Ca-dependent wave with a speed of about 0.009 m/s. These traveling waves are synaptic-independent and could be conducted only by the electric fields generated by neighboring neurons, which are basically consistent with the in vitro data measured experiments. It is also found that the slow Ca wave could trigger generation of fast NMDA waves in the propagation path of slow waves whereas fast NMDA waves cannot affect the propagation of slow Ca waves. These results suggest that dendritic Ca waves could acted as the source of the coexistence fast and slow waves. Furthermore, we also confirm the impact of cellular spacing heterogeneity on the onset of coexisting fast and slow waves. The local region with decreasing distances among neighbor neurons is more liable to promote the onset of spontaneous slow waves which, as sources, excite propagation of fast waves. These modeling studies provide possible biophysical mechanisms underlying the neural dynamics of spontaneous traveling waves in brain tissues.

浮式海上风电助力可再生能源发展

Nearly 150 km off the coast of Norway,in one of the windiest places on Earth,stands Hywind Tampen,the world’s largest floating wind power farm.Each weighing 8800 t and 190 m tall,with roughly one-third of that height sitting below the waterline,Hywind Tampen’s 11 turbines can generate 94.6 MW(Fig.1)[1].The blades—each 80 m long—travel at a blistering 290 km∙h–1,yet because of their size they complete only about 10 to 15 full rotations per minute.A single rotation provides enough electricity to power an average home for a day.However,Hywind Tampen,which became fully operational in August 2023,will not power houses.Instead,the installation built by energy company Equinor(Stavanger,Norway)will provide 38%of the annual electricity consumed by five nearby offshore oil platforms in the North Sea[1].

Enhancing the resolution of sparse rock property measurements using machine learning and random field theory

The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad measurements but lack finer resolution.Laboratory-based rock core measurements offer higher resolution but are resource-intensive.Conventionally,wireline logging and rock core measurements have been used independently.This study introduces a novel approach that integrates both data sources.The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data.By combining machine learning with random field theory,the method allows for probabilistic predictions in regions with sparse data sampling.In this framework,12 parameters from wireline tests are used to predict trends in rock core data.The residuals are modeled using random field theory.The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual.By utilizing unconditional and conditional random field theories,this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates.This integrated approach optimizes the use of existing core and logging data.Its applicability is confirmed in an oil project in West China.

Higher-dimensional Chen-Lee-Liu equation and asymmetric peakon soliton

Integrable systems play a crucial role in physics and mathematics.In particular,the traditional(1+1)-dimensional and(2+1)-dimensional integrable systems have received significant attention due to the rarity of integrable systems in higher dimensions.Recent studies have shown that abundant higher-dimensional integrable systems can be constructed from(1+1)-dimensional integrable systems by using a deformation algorithm.Here we establish a new(2+1)-dimensional Chen-Lee-Liu(C-L-L)equation using the deformation algorithm from the(1+1)-dimensional C-L-L equation.The new system is integrable with its Lax pair obtained by applying the deformation algorithm to that of the(1+1)-dimension.It is challenging to obtain the exact solutions for the new integrable system because the new system combines both the original C-L-L equation and its reciprocal transformation.The traveling wave solutions are derived in implicit function expression,and some asymmetry peakon solutions are found.

Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples

The collision cross-sections(CCS)measurement using ion mobility spectrometry(IMS)in combination with mass spectrometry(MS)offers a great opportunity to increase confidence in metabolite identification.However,owing to the lack of sensitivity and resolution,IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites(VLMs250 Da).Here,we describe an analytical method using ultrahigh-performance liquid chromatography(UPLC)coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples.The experimental CCS values,along with mass spectral properties,were reported for the 174 metabolites.The experimental data included the mass-to-charge ratio(m/z),retention time(RT),tandem MS(MS/MS)spectra,and CCS values.Among the studied metabolites,263 traveling wave ion mobility spectrometry(TWIMS)-derived CCS values(TWCCSN2)were reported for the first time,and more than 70%of these were CCS values of VLMs.The TWCCSN2 values were highly repeatable,with inter-day variations of<1%relative standard deviation(RSD).The developed method revealed excellent TWCCSN2 accuracy with a CCS difference(DCCS)within±2%of the reported drift tube IMS(DTIMS)and TWIMS CCS values.The complexity of the urine matrix did not affect the precision of the method,as evidenced by DCCS within±1.92%.According to the Metabolomics Standards Initiative,55 urinary metabolites were identified with a confidence level of 1.Among these 55 metabolites,53(96%)were VLMs.The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values,which clearly increased metabolite identification confidence.

Harmonic balance simulation of the influence of component uniformity and reliability on the performance of a Josephson traveling wave parametric amplifier

A Josephson traveling wave parametric amplifier(JTWPA),which is a quantum-limited amplifier with high gain and large bandwidth,is the core device of large-scale measurement and control systems for quantum computing.A typical JTWPA consists of thousands of Josephson junctions connected in series to form a transmission line and hundreds of shunt LC resonators periodically loaded along the line for phase matching.Because the variation of these capacitors and inductors can be detrimental to their high-frequency characteristics,the fabrication of a JTWPA typically necessitates precise processing equipment.To guide the fabrication process and further improve the design for manufacturability,it is necessary to understand how each electronic component affects the amplifier.In this paper,we use the harmonic balance method to conduct a comprehensive study on the impact of nonuniformity and fabrication yield of the electronic components on the performance of a JTWPA.The results provide insightful and scientific guidance for device design and fabrication processes.

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.