The heterogeneous impact of China-Europe railway express on the efficiency of logistics industry in node cities

Purpose-The spatiotemporal compression effect of China-Europe Railway Express(CR-Express)can reduce the filow costs of resources between China's node cities.Additionally,it can break through the limitations of low-added-value marine products,significantly impacting the logistics industry efficiency.However,there are few literature verifying and analyzing its heterogeneity.This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.Design/methodology/approach-First,this study uses panel data to measure the efficiency of node city logistics industry.Secondiy,this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model.Finally,according to the node city difference,the sample city experimental group is grouped for heterogeneity analysis.Findings-The results show that CR-Express can promote the urban logistics industry efficiency,with an average effect of 4.55%.According to the urban characteristics classification,the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious.The improvement effect of node cities and central cities in central and western China is stronger,especially in the sample of megacities and type I big cities.Compared with non-value chain industrial products,the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.Originality/value-Under the background of double cycle development,this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

Hourly Wage and the Likelihood of Stealing an Item

Researchers have extensively explored the impact of wages on individuals’ decisions to engage in property crimes. While most of these studies in the past have relied on macro-level data to investigate the relationship between crime rates and hourly wages, this paper takes a novel approach by utilizing micro-level data to examine the influence of hourly wages on the likelihood of stealing an item valued at least $50. The results obtained from the estimations reveal that an increase in hourly wage leads to a decrease in the probability of theft, all other factors being held constant. Further estimation by gender revealed that hourly wages given to both male and female have no bearing on the decision to steal. Additionally, the analysis of the differences in theft probabilities across gender and race demonstrates that males consistently exhibit a higher likelihood of engaging in theft when compared to females across various racial groups.

Integration of Multiple Spectral Data via a Logistic Regression Algorithm for Detection of Crop Residue Burned Areas:A Case Study of Songnen Plain,Northeast China

The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both crucial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area mapping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating multiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38%to 86.90%and 73.47%to 97.14%for the 52TCQ and 51TYM cases,respectively.In comparison,the accuracy of the burned area map was improved to 87.14%and 98.33%for the 52TCQ and 51TYM cases,respectively by multiple variable logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.

Exploration on the Construction of University Logistics Information Service Platform

Logistics information construction in colleges and universities is an important part of smart campus. This paper expounds the current situation and existing problems of the logistics information construction in colleges and universities. Taking China University of Geosciences (Beijing) as an example, this paper discusses the construction principles and Personnel organization structure of the logistics information construction, and provides the construction scheme of the logistics information service platform. It can be used for reference for the implementation of logistics information construction in other colleges and universities.

The Role of Chittagong Port Authority to Develop Other National Ports in Bangladesh to Provide Maritime Logistics Support in South Asia

Chittagong Port is the principal seaport in Bangladesh that has contributed to the national economy with the opportunity to be a world-class regional port in South Asia.Cooperation among the three national ports Chittagong,Mongla and Payra is essential to do maritime logistics business in the region after serving the nation proudly.Here,Chittagong Port Authority(CPA)has the opportunity to help others in the process of port development for increasing efficiency and productivity by providing financial and technical assistance because of its financial and technical capabilities as a pioneer seaport in the port world.This paper examines the role of CPA to bolster and develop the underutilized Mongla Port and newly established Payra Port,where qualitative research methodology is applied to explore the ways,by which CPA can assist,link and integrate with others effectively,especially in developing the port infrastructure and inland transport networks.In addition,the research found the prospectus of Mongla and Payra to supply port services to the neighbors India,Nepal,and Bhutan as well as serve the South-West part of China with the aim of increasing regional connectivity and promoting international trade in those basically landlocked areas and countries of Asia.

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

Drone logistics is a novel method of distribution that will become prevalent.The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption,resulting in cost savings for the company’s transportation operations.Logistics firms must discern the ideal location for establishing a logistics hub,which is challenging due to the simplicity of existing models and the intricate delivery factors.To simulate the drone logistics environment,this study presents a new mathematical model.The model not only retains the aspects of the current models,but also considers the degree of transportation difficulty from the logistics hub to the village,the capacity of drones for transportation,and the distribution of logistics hub locations.Moreover,this paper proposes an improved particle swarm optimization(PSO)algorithm which is a diversity-based hybrid PSO(DHPSO)algorithm to solve this model.In DHPSO,the Gaussian random walk can enhance global search in the model space,while the bubble-net attacking strategy can speed convergence.Besides,Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the algorithm.DHPSO maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current model.Comparing DHPSO with other state-of-the-art intelligent algorithms,the efficiency of the scheme can be improved by 42.58%.This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO’s location selection.All the results show the location of the drone logistics hub is solved by DHPSO effectively.

Association between people’s attitudes towards human-elephant conflict and their locational,demographic,and socio-economic characteristics in Buxa Tiger Reserve and its adjoining area,India

“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy makers.The rising conflict between human beings and wild elephants is common in Buxa Tiger Reserve(BTR)and its adjoining area in West Bengal State,India,making the area volatile.People’s attitudes towards elephant conservation activity are very crucial to get rid of HEC,because people’s proximity with wild elephants’habitat can trigger the occurrence of HEC.The aim of this study is to conduct an in-depth investigation about the association of people’s attitudes towards HEC with their locational,demographic,and socio-economic characteristics in BTR and its adjoining area by using Pearson’s bivariate chi-square test and binary logistic regression analysis.BTR is one of the constituent parts of Eastern Doors Elephant Reserve(EDER).We interviewed 500 respondents to understand their perceptions to HEC and investigated their locational,demographic,and socio-economic characteristics including location of village,gender,age,ethnicity,religion,caste,poverty level,education level,primary occupation,secondary occupation,household type,and source of firewood.The results indicate that respondents who are living in enclave forest villages(EFVs),peripheral forest villages(PFVs),corridor village(CVs),or forest and corridor villages(FCVs),mainly males,at the age of 18–48 years old,engaged with agriculture occupation,and living in kancha and mixed houses,have more likelihood to witness HEC.Besides,respondents who are illiterate or at primary education level are more likely to regard elephant as a main problematic animal around their villages and refuse to participate in elephant conservation activity.For the sake of a sustainable environment for both human beings and wildlife,people’s attitudes towards elephants must be friendly in a more prudent way,so that the two communities can live in harmony.

Utilization of Logistical Regression to the Modified Sine-Gordon Model in the MST Experiment

In this paper, a logistical regression statistical analysis (LR) is presented for a set of variables used in experimental measurements in reversed field pinch (RFP) machines, commonly known as “slinky mode” (SM), observed to travel around the torus in Madison Symmetric Torus (MST). The LR analysis is used to utilize the modified Sine-Gordon dynamic equation model to predict with high confidence whether the slinky mode will lock or not lock when compared to the experimentally measured motion of the slinky mode. It is observed that under certain conditions, the slinky mode “locks” at or near the intersection of poloidal and/or toroidal gaps in MST. However, locked mode cease to travel around the torus;while unlocked mode keeps traveling without a change in the energy, making it hard to determine an exact set of conditions to predict locking/unlocking behaviour. The significant key model parameters determined by LR analysis are shown to improve the Sine-Gordon model’s ability to determine the locking/unlocking of magnetohydrodyamic (MHD) modes. The LR analysis of measured variables provides high confidence in anticipating locking versus unlocking of slinky mode proven by relational comparisons between simulations and the experimentally measured motion of the slinky mode in MST.

Model fitting of the seasonal population dynamics of the soybean aphid, Aphis glycines Matsumura, in the field

The soybean aphid, Aphis glycines Matsumura(Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integrated pest management(IPM). Based on systematically investigating soybean aphid populations in the field from 2018 to 2020, this study adopted the inverse logistic model for the first time, and combined it with the classical logistic model to describe the changes in seasonal population abundance from colonization to extinction in the field. Then, the increasing and decreasing phases of the population fluctuation were divided by calculating the inflection points of the models, which exhibited distinct seasonal trends of the soybean aphid populations in each year. In addition, multifactor logistic models were then established for the first time, in which the abundance of soybean aphids in the field changed with time and relevant environmental conditions. This model enabled the prediction of instantaneous aphid abundance at a given time based on relevant meteorological data. Taken as a whole, the successful approaches implemented in this study could be used to build a theoretical framework for practical IPM strategies for controlling soybean aphids.

The Current Situation of Agricultural Products Logistics and the Conception of Logistics System in Henan Province:based on the Case of Zhengzhou

Based on the understanding of agricultural products, transportation sites and transportation market, this paper puts forward the concept of agricultural product logistics system, and discusses the background of the system and provides recommendations for subsequent protection. Through the research of this paper, we explore the development countenneasures of agricultural products logistics under the background of low-carbon economy to guide the development of agricultural products logistics, improve the economic benefits of agricultural products, promote agricultural development and farmers＇ income. Finally, the paper discusses the optimization of economic and social environmental benefits, which will contribute to the construction of new socialist countuside in Henan province.

A Study on Establishing a Cross-border E-commerce Logistics System for Agricultural Products in Sichuan Province in the Context of the Belt and Road Initiative

The rapid development of cross-border e-commerce,especially since Chengdu was listed as an Integrated Pilot Zone for Cross-Border E-Commerce in 2016,has led to a rising trade value of agricultural products in the metropolis.This upward trend is also attributed to the China-Europe Railway Express and the Chengdu International Aviation Hub Integrated Functional Area,two infrastructure systems that have opened more international logistics channels for agricultural products in Sichuan province.However,the development of cross-border logistics has failed to respond to the rapid growth of cross-border e-commerce for agricultural products.This problem has given rise to longer delivery cycles,higher costs,and reduced product quality,hindering the development of cross-border e-commerce for agricultural products.Currently,most research efforts are focused on selecting a logistics mode which has created an urgency is to establish a logistics system.To that end,we must utilize the opportunities and preferential policies brought about by the Belt and Road Initiative to advance the establishment of a cross-border logistics system for agricultural products,which will create more channels for selling Sichuan’s agricultural products overseas.This article analyzes the current situation of the cross-border logistics system for agricultural products produced by the province and studies the potential relationships between a logistics system and cross-border trade of agricultural products.It seeks to build a logistics system that meets the demands of cross-border transactions using economic theories focused on cross-border e-commerce and logistics.Such a logistic system will help shorten long delivery cycles,cut delivery costs,and guarantee the quality of agricultural products.Also,it can contribute to the rapid development of cross-border e-commerce of agricultural products and solve problems in developing the agricultural products logistics system of Sichuan province.

The Logistics of Production and Supply of Ag Pellets for Industrial Applications in Canada

In this work we analyze the supply of biomass from field to an in-land or port destination. The biomass is pelletized to increase its bulk density to extend its storage period and for ease of its transport. The pellet may be used for conversion to chemicals and animal bedding or for straight combustion. We analyzed supply chain in Saskatchewan where there are plenty of crop residues but widely dispersed and harvest seasons are short. We envisioned that the farmer collects bales from field and transports the bales to farmstead during the harvest season. The bales are then processed into pellets using small scale pellet equipment. A custom operator with expertise in pelletization may engage in handling and densifying the biomass. The business case for the mobile mill will be similar to the well established custom grain and forage harvesting operations. The pellets are stored in hopper bottom grain bins at the farmstead. From this point, the handling of pellets would be similar to the handling and marketing of grain. The farmer trucks a specified volume of pellets from farmstead to the nearest elevator where the pellets are transferred to larger bins or silos. Pellets are extracted from silos and loaded onto the rail cars. The Canadian freight rail companies (mainly CN) currently transport over 3 million dry tonne (dt) of wood pellets in rail cars. The pellets are hauled to marine ports on the West Coast or East Coast for export. The cost of delivering ag pellets to biorefinery or to the shipping port is $86.09/dt. This cost does not include the equivalent value of removing biomass from the farm (e.g. fertilizer replacement) and return on investment. The GHG emissions to produce and transport ag pellets add up to 185.9 kg of CO2 per dt of biomass. The cost of producing pellets without drying feedstock is $35.05/dt and the corresponding GHG for palletization amounts $146.30/dt.

Differential Calculus the Study of the Growth and Decay of an Entity’s Population

Population Growth and Decay study of the growth or the decrease of a population of a given entity, is carried out according to the environment. In an infinite environment, i.e. when the resources are unlimited, a population P believes according to the following differential equation P’ = KP, with the application of the differential calculus we obtasin an exponential function of the variable time (t). The function of which we can predict approximately a population according to the signs of k and time (t). If k > 0, we speak of the Malthusian croissant. On the other hand, in a finite environment i.e. when resources are limited, the population cannot exceed a certain value. and it satisfies the logistic equation proposed by the economist Francois Verhulst: P’ = P(1-P).

The Delegation of Foreign Sinologists Visits China

At the invitation of CAFIU,the delegation of 15 renowned sinologists from 15 countries including Iran,Spain,and Mexico visited China from September 4th to 15th.

Effects of the probability of pulse-like ground motions on landslide susceptibility assessment in near-fault areas

Earthquake-induced strong near-fault ground motion is typically accompanied by largevelocity pulse-like component,which causes serious damage to slopes and buildings.Although not all near-fault ground motions contain a pulse-like component,it is important to consider this factor in regional earthquake-induced landslide susceptibility assessment.In the present study,we considered the probability of the observed pulse-like ground motion at each site(PP)in the region of an earthquake as one of the conditioning factors for landslide susceptibility assessment.A subset of the area affected by the 1994Mw6.7 Northridge earthquake in California was examined.To explore and verify the effects of PP on landslide susceptibility assessment,seven models were established,consisting of six identical influencing factors(elevation,slope gradient,aspect,distance to drainage,distance to roads,and geology)and one or two factors characterizing the intensity of the earthquake(distance to fault,peak ground acceleration,peak ground velocity,and PP)in logistic regression analysis.The results showed that the model considering PP performed better in susceptibility assessment,with an area under the receiver operating characteristic curve value of 0.956.Based on the results of relative importance analysis,the contribution of the PP value to earthquakeinduced landslide susceptibility was ranked fourth after the slope gradient,elevation,and lithology.The prediction performance of the model considering the pulse-like effect was better than that reported previously.A logistic regression model that considers the pulse-like effect can be applied in disaster prevention,mitigation,and construction planning in near-fault areas.

Factors related to the functionality of community-based rural water supply and sanitation program in Indonesia

This study used multinomial logistic regression and Bayesian belief networks(BBN)to analyze factors influenc-ing the functionality of the community-based rural drinking water supply and sanitation program(PAMSIMAS)in Indonesia.28,936 PAMSIMAS projects in 33 provinces in Indonesia were analyzed.The data indicates that 85.4%of the water supply systems were fully functioning,9.1%were partially functioning,and 5.5%were not functioning.In the regression analysis,good management is positively associated with functionality and a high investment per capita is negatively associated with the functionality.The latter suggests the need for comprehen-sive economic analysis in the feasibility study in scattered housing sites and remote-undeveloped areas.We also found that high community participation at the beginning of the project was associated with the not functioning system,while women’s participation was positively associated with the functionality.Furthermore,the household connection is more likely to be functioning than communal connection.BBN analysis shows if the beneficiaries do not pay for water,the probability of not functioning systems is 20 times higher than systems with fee collec-tion.Moreover,the combination of strong management,strong financial status,and household connection rather than communal connection increases the probability of fully functioning to 98%.Improvement of data collection is also necessary to monitor the current conditions of all PAMSIMAS systems in Indonesia.This study offers a country-level perspective for better implementation of the community-based rural water supply and sanitation program in developing countries.

Abstract of Speech by Michael Crook,British Sinologist,Winner of the Chinese Government Friendship Award

Michael Crook,British sinologist and winner of the Chinese Government Friendship Award,made constructive proposals on the interpretation of Chinese modernisation in the new era.He pointed out that China has gained remarkable achievements in its development,and its successful experience will serve as useful reference for the international community.The story of Chinese modernisation is not only a significant part of Chinese stories,but also a major path for the world to understand the Communist Party of China,the country,and the Chinese nation.Therefore,fine interpretation of Chinese path to modernisation is of exceptional significance to countries all over the world.

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Air quality is a critical concern for public health and environmental regulation. The Air Quality Index (AQI), a widely adopted index by the US Environmental Protection Agency (EPA), serves as a crucial metric for reporting site-specific air pollution levels. Accurately predicting air quality, as measured by the AQI, is essential for effective air pollution management. In this study, we aim to identify the most reliable regression model among linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression, and K-nearest neighbors (KNN). We conducted four different regression analyses using a machine learning approach to determine the model with the best performance. By employing the confusion matrix and error percentages, we selected the best-performing model, which yielded prediction error rates of 22%, 23%, 20%, and 27%, respectively, for LDA, QDA, logistic regression, and KNN models. The logistic regression model outperformed the other three statistical models in predicting AQI. Understanding these models' performance can help address an existing gap in air quality research and contribute to the integration of regression techniques in AQI studies, ultimately benefiting stakeholders like environmental regulators, healthcare professionals, urban planners, and researchers.