Search Results (12)

The national food consumption surveys are crucial for monitoring the nutritional status of population but are also time and resource consuming. The growing use of technology and web-based platforms can help to reduce the logistical burden and cost of conventional methods. This study aims to compare self-administered 24 h recall to those obtained from interviewer-led 24 h recall by examining food items, food group and nutrient intakes using the online software FOODCONS 1.0 in both cases. The volunteers (39 adults) were randomized in A and B groups. On study days, they completed a self-administered 24 h recall and 3 h later, an interviewer-led 24 h recall. After 15 days, the same process was repeated in the opposite way. The difference in the two-day mean of energy and macro- and micronutrients intakes between the two methods was not statistically significant. The Bland–Altman analysis found a good agreement for energy, carbohydrates and fiber. At the level of food groups, the correlation coefficients indicated good concordance between the two methods. The self-administered 24 h recall through FOODCONS 1.0 software could be a suitable alternative to an interviewer-led interview, allowing a higher participation rate and less time-consuming food consumption studies. Full article

Understanding sleep stages is crucial for diagnosing sleep disorders, developing treatments, and studying sleep’s impact on overall health. With the growing availability of affordable brain monitoring devices, the volume of collected brain data has increased significantly. However, analyzing these data, particularly when using the gold standard multi-lead electroencephalogram (EEG), remains resource-intensive and time-consuming. To address this challenge, automated brain monitoring has emerged as a crucial solution for cost-effective and efficient EEG data analysis. A critical component of sleep analysis is detecting transitions between wakefulness and sleep states. These transitions offer valuable insights into sleep quality and quantity, essential for diagnosing sleep disorders, designing effective interventions, enhancing overall health and well-being, and studying sleep’s effects on cognitive function, mood, and physical performance. This study presents a novel EEG feature extraction pipeline for the accurate classification of various wake and sleep stages. We propose a noise-robust model-based Kalman filtering (KF) approach to track changes in a time-varying auto-regressive model (TVAR) applied to EEG data during different wake and sleep stages. Our approach involves extracting features, including instantaneous frequency and instantaneous power from EEG, and implementing a two-step classifier for sleep staging. The first step classifies data into wake, REM, and non-REM categories, while the second step further classifies non-REM data into N1, N2, and N3 stages. Evaluation on the extended Sleep-EDF dataset (Sleep-EDFx), with 153 EEG recordings from 78 subjects, demonstrated compelling results with classifiers including Logistic Regression, Support Vector Machines, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LGBM). The best performance was achieved with the LGBM and XGBoost classifiers, yielding an overall accuracy of over 77%, a macro-averaged F1 score of 0.69, and a Cohen’s kappa of 0.68, highlighting the efficacy of the proposed method with a remarkably compact and interpretable feature set. Full article

This study aims to elucidate the implications of carbon peak and carbon neutrality targets on corridor logistics, with a focus on the burgeoning high-speed rail express sector. Acknowledging carbon emissions taxation as an integral component of transportation costs, it examines the competitive dynamics among four cargo transport modes: high-speed rail (HSR), conventional rail, aviation, and road transport. Within a strategic game framework, carriers are analyzed based on freight rates, speed, safety, reliability, and convenience to assess their utility. A dynamic game model and a solution approach are developed, aiming to optimize freight-related variables, maximize carriers’ generalized profits, and enhance shippers’ utility. Empirical validation is provided through case studies in Xi’an and Lanzhou, northwest China, affirming the model’s efficacy. The findings reveal the strong competitive edge of the high-speed rail express in the corridor, offering valuable insights for carrier pricing strategies, emission tax rate setting, and macro-policy adjustments in the transport sector. Full article

The diversification of business forms leads to functional and spatial complexity in cities. The efficient determination of the complexity of an urban system is the basis for the scientific monitoring of the multi-functional aggregation within cities. Previous studies on the urban spatial structure were limited by the difficulty of collecting micro-data and the high time cost, and they focused on the macro-spatial structure, lacking fine-grained investigations of the micro-spatial structure. Additionally, high-resolution remote sensing images, which mainly rely on the textural characteristics of the spectrum of ground objects, cannot detect the social and economic functions of ground objects. Thus, it is difficult to meet the actual needs of urban planning and management. The purpose of this paper is to automatically identify the spatial heterogeneity and temporal variation of urban land use functions in the context of complex urban systems. The TF-IDF (term frequency–inverse document frequency) algorithm, a machine learning classification algorithm, and other methods are applied to identify the urban functions and distribution characteristics of the main urban area based on the POI (point of interest) data and urban form data. The results show the following: (1) From 2012 to 2022, all types of land use in Yiwu city grew at different rates, with logistics and warehousing space growing the fastest, which is in line with Yiwu’s goal of building a national logistics center for trade and services. (2) The residential area has a spatial structure with a dense central circle and a scattered periphery extending from northeast to southwest and from east to west. (3) The commercial service sector shows clear spatial differentiation between the core and the periphery. The commercial functional areas of Niansanli, Houzhai, and Chengxi, where the number of commercial POIs is relatively small, are located at the intersection of the administrative subdistricts near the city center, indicating that the commercial economic activities of the downtown subdistrict have a certain spillover effect on adjacent subdistricts. (4) The public facilities of each subdistrict are generally located in the core of each subdistrict, which ensures better convenience and accessibility. (5) Industrial land with a large total area that is scattered and mixed with urban residential land gradually tends to be centralized, forming an industrial belt around the city. This study comprehensively considers the aggregation relationship between urban buildings and land use and improves the accuracy of land identification and functional zoning. Full article

International transport corridors (ITCs) are intricate logistical networks essential for global trade flows. The effective modeling of these corridors provides invaluable insights into optimizing the transport system. However, existing approaches have significant limitations in dynamically representing the complexities and uncertainties inherent in ITC operations and at the early stages of ITC development when data are limited. This gap is addressed through the application of Evaluation Petri Nets (E-Nets), which facilitate the detailed, flexible, and responsive macro-modeling of international transport corridors. This paper proposes a novel methodology for developing E-Net-based macro-models of corridors by incorporating key parameters like transportation time, costs, and logistics performance. The model is scalable, enabling analysis from an international perspective down to specific country segments. E-Nets overcome limitations of conventional transport models by capturing the interactive, stochastic nature of ITCs. The proposed modeling approach and scalability provide strategic insights into optimizing corridor efficiency. This research delivers a streamlined yet comprehensive methodology for ITC modeling using E-Nets. The presented framework has substantial potential for enhancing logistics system analysis and planning. Full article

Brazil’s transportation infrastructure did not follow the country’s agricultural development and the macro-logistics operations still rely on trucking. Even with a lack of roads, the service areas of the ports on the Atlantic coast, particularly the port of Santos, expanded to central Brazil, the country’s most productive agricultural area. Recently, the Federal Government released mid-term plans to build railways to reduce transportation costs until 2035. However, no simulation about port regionalization and competitiveness was performed. This research evaluated the effectiveness of the proposed transportation infrastructure regarding transportation cost and new routes that can reshape the ports’ influence areas. Our geographically explicit model used the Dinamica_EGO modeling platform and PostgreSQL, fed by official public data from transportation and agriculture authorities. Considering the hypothesis that new railways can increase port competitiveness, we computed scenarios considering the planned 2035 infrastructure and compared them to the current situation. The findings showed that the Ferrogrão railway can effectively reduce transport costs, therefore changing the spatial configuration of macro-logistics basins. In conclusion, a geospatial model can predict short-cheaper routes, port regionalization, and competitiveness regarding the geographic aspects of the supply chain. The long-distance and importance of Brazilian agriculture exportation justify and value the investigation. Full article

With the ageing population, equitable access to medical care has proven to be paramount for the effective and efficient management of all diseases. Healthcare access can be hindered by cost barriers for drugs or exams, long waiting lists or difficult access to the place where the needed healthcare service is provided. The aim of this paper is to investigate whether the probability of facing one of these barriers varies among individuals with different socio-economic status and care needs, controlling for geographical variability. Methods. The sample for this study included 9629 interviews with Italian individuals, aged 15 and over, from the second wave (2015) of the European Health Interview Survey, which was conducted in all EU Member States. To model barriers to healthcare, two-level variance components of logistic regression models with a nested structure given by the four Italian macro-areas were considered. Results. Of the barriers considered in this study, only two were found to be significantly associated with healthcare utilization. Specifically, they are long waiting lists for specialist service accessibility (adjOR = 1.20, 95% CI (1.07; 1.35)) and very expensive exams for dental visit accessibility (adjOR = 0.84, 95% CI (0.73; 0.96)). Another important result was the evidence of an increasing north–south gradient for all of the considered barriers. Conclusion. In Italy, healthcare access is generally guaranteed for all of the services, except for specialist and dental visits that face a waiting time and financial barriers. However, barriers to healthcare were differentiated by income and sex. The north–south gradient for healthcare utilization could be explained through the existing differences in organizational characteristics of the several regional healthcare services throughout Italy. Full article

Background: Efforts made to calculate the logistics costs in Indonesia, at the macro level, are facing various problems, due to the fact that there have been no national agreements—to any models employed—to calculate those costs. Moreover, limited data and information due to the lack of use of such integrated information technology to reduce the information asymmetry on the logistics processes and activities have created some additional problems. Objective: This study is aimed at reviewing the measurement model, of the logistics costs used in Indonesia, at the macro level. Method: It provides a potential measurement approach proposed by several previous studies as an alternative option that may help develop the existing models by elaborating on their limitations. Results: The results of this study emphasize the recognition of the components of the logistics costs and the formulation of a more accurate, transparent, and comprehensive measurement framework to improve the standard used to assess the logistics costs. Conclusion: Thus, the calculation output of the logistics costs is expected to be able to provide stakeholders with reliable information to develop an efficient logistics system. Furthermore, logistics costs will be more controllable, allowing Indonesia to achieve such comparative advantages. Full article

The paper deals with the economic efficiency of decentralized and centralized strategies of distribution goods in terms of both internal efficiency of firms and external costs of logistics processes (first of all external costs of transport). The author developed a model (using an electronic spreadsheet) in order to calculate the economical efficiency in the micro and macro dimensions in order to find the distances on which distribution using one central warehouse is more profitable than decentralized distribution. The results of the simulations show that the strategy of centralized inventories can be in many cases an economically effective strategy although not for deliveries on very long distance. The results confirm that the benefits of centralization are lower inventories, although the simulations do not confirm the applicability of the square root law to calculate the level of inventories. However, they confirm a positive impact on the level of logistic customer service, measured by the availability of stocks. Better service is probably the main benefit of this strategy. In order to investigate the impact of individual parameters on the total costs of logistics processes 1300 simulations were carried out for various cases: The volume of annual sales, fluctuations in demand, the value of distributed goods, the number of warehouses in a decentralized system and the width of the product range, costs of warehousing, and maintaining stocks, and the distance of transport and in deliveries to customers. Full article

The beer production chain includes some crucial steps regarding processing, delivery, service, and consumption that can benefit from the implementation of IoT (Internet of Things) based technologies. Large breweries implemented the use of sensors and digitization before smaller ones among which are craft breweries. Internet of Beer (IoB) technologies are becoming accessible to mid and small sized brewing companies. Therefore, the objective of this work is to review mainly low-cost IoB smart technologies that can be implemented from the mash to the final product and its service, to improve the brewing production, control, delivery, and final quality increasing profitability. The reviewed applications were retrieved both from the scientific databases and from the web. The work is structured in three macro areas such as beer processing, product logistics and traceability, and service. The results show a future trend characterized by a very fast increase in the use of IoB (also open source) systems to drive efficiency, productivity, quality, and safety. This will be done by real-time monitoring and a data-driven decision support system (DSS). Crucial aspects needing further investigation are data ownership and data standardization. The access price of IoB devices and software is destined for a significant decrease while their diversification on the market will grow leading to a massive future implementation within all the production levels. Full article

Time restriction and logistics sprawl (e.g., relocating logistics facilities), as two popular urban policies, usually affect the urban freight and environmental burden, but their combination might lead to unexpected results. This paper analyzes the impact of time restriction and logistics sprawl on urban freight and local environments based on a Beijing agricultural freight case through traffic simulation. The data is derived through a freight demand forecasting method. Based on the data, this paper constructs four groups of scenarios to represent different policies (or combined policies) and then conducts macro-simulation to obtain the economic and environmental indicators. Results show that (1) time restriction can increase the freight costs and slightly decrease local emissions, while logistics sprawl can increase both costs and emissions; (2) the joint implementation of the two policies are proved to be positive in economic and environmental aspects because it helps freight carriers adopt a new strategy to improve delivery efficiency; (3) urban freight policies are closely related to the freight carriers because different responses from carriers can lead to different policy effects. Full article

Rapid increase in population and growing concentration of capital in urban areas has escalated both the severity and longer-term impact of natural disasters. As a result, Disaster Risk Management (DRM) and reduction have been gaining increasing importance for urban areas. Remote sensing plays a key role in providing information for urban DRM analysis due to its agile data acquisition, synoptic perspective, growing range of data types, and instrument sophistication, as well as low cost. As a consequence numerous methods have been developed to extract information for various phases of DRM analysis. However, given the diverse information needs, only few of the parameters of interest are extracted directly, while the majority have to be elicited indirectly using proxies. This paper provides a comprehensive review of the proxies developed for two risk elements typically associated with pre-disaster situations (vulnerability and resilience), and two post-disaster elements (damage and recovery), while focusing on urban DRM. The proxies were reviewed in the context of four main environments and their corresponding sub-categories: built-up (buildings, transport, and others), economic (macro, regional and urban economics, and logistics), social (services and infrastructures, and socio-economic status), and natural. All environments and the corresponding proxies are discussed and analyzed in terms of their reliability and sufficiency in comprehensively addressing the selected DRM assessments. We highlight strength and identify gaps and limitations in current proxies, including inconsistencies in terminology for indirect measurements. We present a systematic overview for each group of the reviewed proxies that could simplify cross-fertilization across different DRM domains and may assist the further development of methods. While systemizing examples from the wider remote sensing domain and insights from social and economic sciences, we suggest a direction for developing new proxies, also potentially suitable for capturing functional recovery. Full article