Food supply chain resilience model for critical infrastructure collapses due to natural disasters

PurposeCritical infrastructure (CI) plays an essential role in reading, reacting and responding while dealing with natural disasters. This study address food supply chain resilience by proposing an FSC resilience model that explains the food product and transport flow via production, processing, distribution and retailing in circumstances of (CI) collapses post a natural disaster.Design/methodology/approachA combination of qualitative methods was conducted to obtain a comprehensive overview of the food and beverage sector in Puerto Rico. The full dataset comprised of seven focus groups for a total of 52 participants and 12 in-depth interviews.FindingsFSC resilience is seen in this study through the managerial actions taken by members of the Chain: innovating, transforming, adapting, and flexibilising business models and operations.Originality/valueThis study is the first to address FSC resilience from the perspective of net food importer economy in the context of natural disasters and prolonged Critical infrastructure (CI) breakdown, and the first one in proposing an FSC resilience model that explains the food product and transport flow via production, processing, distribution and retailing in circumstances of CI collapses post a natural disaster.

Development of an automated systemfor determining transport flow on video using a neural network

This article discusses the problem of determining traffic flows at an intersection by identifying vehicles using neural networks. A model of a neural network used to detect vehicles in the image is described. The paper describes an algorithm for identifying cars at an intersection. The article also describes an algorithm for obtaining the trajectory of the vehicle.

Supramolecular assembly of chloroplast NAD(P)H dehydrogenase-like complex with photosystem I from Arabidopsis thaliana

Cyclic electron transport/flow (CET/CEF) in chloroplasts is a regulatory mechanism crucial for optimization of plant photosynthetic efficiency. CET is catalyzed by a membrane-embedded NAD(P)H dehydrogenase-like (NDH) complex containing at least 29 protein subunits and associating with photosystem I (PSI) to form the NDH-PSI supercomplex. Here we report the 3.9 angstrom resolution structure of Arabidopsis thaliana NDH-PSI (AtNDH-PSI) supercomplex. We have constructed structural models for 26 AtNDH subunits, among which 11 subunits are unique to chloroplast and stabilize the core part of NDH complex. In the supercomplex, one NDH can bind up to two PSI-LHCI complexes at both sides of its membrane arm. Two minor LHCIs, Lhca5 and Lhca6, each present in one PSI-LHCI, interact with NDH and contribute to the supercomplex formation and stabilization. Our results showed structural details of the supercomplex assembly and provide molecular basis for further investigation of the regulatory mechanism of CEF in plants.

PETERSBURG (LENINGRAD) SCHOOL OF PASSENGER TRANSPORT FLOW ANALYSIS AND PROBLEMS OF ITS MODERN DEVELOPMENT

A brief analysis of the history and development prospects of mathematical models for forecasting passenger flows in the regional transport network is given. The reasons for the fundamentally different practice of using these models in urban planning in our country and abroad are analyzed. The current trends in the use of models for forecasting passenger flows in solving multifactorial problems of the development of the regional transport system in a market economy when changing local systems of settlement and job placement are presented.

Weighted Centrality and Retail Store Locations in Beijing, China: A Temporal Perspective from Dynamic Public Transport Flow Networks

The spatial relationship between transport networks and retail store locations is an important topic in studies related to commercial activities. Much effort has been made to study physical street networks, but they are seldom empirically discussed with considerations of transport flow networks from a temporal perspective. By using Beijing’s bus and subway smart card data (SCD) and point of interest (POI) data, this study examined the location patterns of various retail stores and their daily dynamic relationships with three weighted centrality indices in the networks of public transport flows: degree, betweenness, and closeness. The results indicate that most types of retail stores are highly correlated with weighted centrality indices. For the network constructed by total public transport flows in the week, supermarkets, convenience stores, electronics stores, and specialty stores had the highest weighted degree value. By contrast, building material stores and shopping malls had the weighted closeness and weighted betweenness values, respectively. From a temporal perspective, most retail types’ largest correlations on weekdays occurred during the after-work period of 19:00 to 21:00. On weekends, shopping malls and electronics stores changed their favorite periods to the daytime, while specialty stores favored the daytime on both weekdays and weekends. In general, the higher store type level of the shopping malls correlates more to weighted closeness or betweenness, and the lower-level store type of convenience stores correlates more to weighted degree. This study provides a temporal analysis that surpasses previous studies on street centrality and can help with urban commercial planning.

Effect of Error in SO2 Slant Column Density on the Accuracy of SO2 Transport Flow Rate Estimates Based on GEMS Synthetic Radiances

This study investigates the uncertainties associated with estimates of the long-range transport SO2 (LRT-SO2) flow rate calculated hourly using Geostationary Environment Monitoring Spectrometer (GEMS) synthetic radiances. These radiances were simulated over the Korean Peninsula and the surrounding regions using inputs from the GEOS-Chem model for January, April, July, and October 2016. The LRT-SO2 calculation method, which requires SO2 vertical column densities, wind data, and planetary boundary layer information, was used to quantify the effects of the SO2 slant column density (SCD) retrieval error and uncertainties in wind data on the accuracy of the LRT-SO2 estimates. The effects were estimated for simulations of three anthropogenic and three volcanic SO2 transport events. When there were no errors in the GEMS SO2 SCD and wind data, the average true LRT-SO2 flow rates (standard deviation) and those calculated for these events were 1.17 (± 0.44) and 1.21 (±0.44) Mg/h, respectively. However, the averages of the true LRT-SO2 flow rates and those calculated for the three anthropogenic (volcanic) SO2 events were 0.61 (1.17) and 0.64 (1.20) Mg/h, respectively, in the presence of GEMS SO2 SCD errors. In the presence of both errors in the GEMS SO2 SCD and wind data, the averages of the true LRT-SO2 flow rates and those calculated for the three anthropogenic (volcanic) SO2 events were 0.61 (1.17) and 0.61 (1.04) Mg/h, respectively. This corresponds to differences of 2.1% to 23.1% between the simulated and true mean LRT-SO2 flow rates. The mean correlation coefficient (R), intercept, and slope between the true and simulated LRT-SO2 flow rates were 0.51, 0.43, and 0.45 for the six simulated events, respectively. This study demonstrates that SO2 SCD accuracy is an important factor in improving estimates of LRT-SO2 flow rates.

METHODOLOGY FOR RECOVERY OF CORRESPONDENCE MATRICES TAKING INTO ACCOUNT TRANSPORT FLOW RESTRICTIONS

Travel demand forecasting models are a key analysis tool used in planning the operation of the transport network and the development of infrastructure facilities. Relevant research within this topic is aimed at reducing the time and minimizing costs associated with developing a forecasting model for travel demand. The study evaluates the possibility of recovering an exact correspondence matrix based on an overloaded network, which takes into account the base / original matrix, traffic flow and their impact on the quality of the generated matrix. By means of the assessment, the admissible per-centage of deviation of the restored traffic flows, necessary for the development of a statistically significant correspondence matrix, has been determined.