bluuebunny/crossref_metadata_2025 huggingface dataset:
Detecting activity type from GPS traces using spatial and temporal information
Authors: Feng Tao , Timmermans Harry J.P.
Published: November 2023

Detecting activity types from GPS traces has been important topic in travel surveys. Compared to inferring transport mode, existing methods are still relatively inaccurate in detecting activity types due to the simplicity of their assumptions and/or lack of background information. To reduce this gap, this paper reports the results of an endeavour to infer activity type by incorporating both spatial information and aggregated temporal information. Three machine learning algorithms, Bayesian belief network, decision tree and random forest, are used to investigate the performance of these approaches in detecting activity types. The test is based on GPS traces and prompted recall data, collected in the Rijnmond region, The Netherlands. Results show that the random forest model has the highest accuracy. The model incorporating spatial and temporal information can predict activity types with an accuracy of 96.8% for the used dataset. These findings are expected to benefit research on the use of GPS technology to collect activity-travel diary data.
Editorial: Data-driven innovations in policy-oriented freight transport models and planning methods
Authors: Gonzalez-Feliu Jesus , Goodchild Anne , Guerrero David
Published: November 2023

Freight transport is a challenging economic sector, as it is essential for the functioning of production and distribution systems but and the same time is at the origin of many nuisances such as congestion, greenhouse gas emissions, pollution and noise. When responding to these issues, planners dispose nowadays of a growing body of freight data that can be used for the implementation of policies towards achieving smart mobility. Because contrary to current practice and dominant discourse, smart mobility is not just a matter of passengers: it also largely relies on more sustainable freight plays an transport. Policy makers see in those new sources of data an opportunity to increase their knowledge on freight transport as well as to have suitable decision support tools to the choices they need to make. In developed countries this trend is illustrated by the increasing requirement of data by recent legislation on freight transport.
Use of discrete choice to obtain urban freight evaluation data
Authors: Muñuzuri Jesús , Guadix José , Cortés Pablo , Onieva Luis
Published: November 2023

The ex-ante evaluation of urban freight solutions is a complex task, due to the interference of different stakeholder groups with different views and objectives. The multi-actor multi-criteria methods have developed as a response to this scenario, but the determination of the weights required by them remains an unclear and controversial task. We propose the use of discrete choice methods as a powerful tool to confront these multi-faced evaluation problems, since the resulting surveys are flexible and easy to respond, and do not give away the final quantitative results. We have applied this methodology to the selection of urban freight solutions in the city of Seville, in Spain, followed by the determination of the relative weights associated to different objectives, both analyses carried out from the side of the carriers stakeholder group.
Editorial: Special Issue on Climate Adaptation of Infrastructure Networks
Authors: Tavasszy Lori , Bollinger L. Andrew , Dijkema Gerard P.J.
Published: November 2023

Climate change affects transportation infrastructures in different ways. Sea level rise and extreme weather may reduce the availability or the quality of parts of the network. Impacts may be felt by all modes of transport (e.g. roads, railroads, waterways, pipelines), by all transport motives (people, freight, utilities) and by different components of the system (the physical construction or user behaviour). Ultimately, failure of infrastructures can also occur at the system level, across modes, motives and components: infrastructures are connected and their performance is interdependent. On top of this wide variety of possible impacts of climate change, large uncertainties about the timing, intensity and location of effects also introduce the question of how to deal with uncertainty itself, in planning and design. This special issue deals with the identification of 1) of the expected impacts of climate change and 2) promising approaches to reduce its impacts.
Innovations in weather services as a crucial building block for climate change adaptation in road transport
Authors: Pilli-Sihvola Karoliina , Nurmi Väinö , Perrels Adriaan , Harjanne Atte , Bösch Patrick , Ciari Francesco
Published: November 2023

The road transport sector is facing rising uncertainties in planning and operations due to climate change induced changes in weather variability and extreme events. However, because of the high level of uncertainty related to the future climate, adaptation measures should be robust so as to retain the option value of the portfolio of measures. As an example of such a measure, this paper evaluates how foreseen innovations in weather services could reduce weather sensitivity and, consequently reduce the negative effects of climate change in the sector. The study is based on a theoretical framework on climate change adaptation and valuation of weather and climate services using the Weather Service Chain Analysis. We apply these frameworks to the road transport sector with a special emphasis on drivers’ decision making before and during a trip. We show that improved weather information, including more accurate weather forecasts, new applications and information dissemination channels can decrease the vulnerability of the mode to projected shifts in extreme weather patterns due to climate change.
A layered approach to model interconnected infrastructure and its significance for asset management
Authors: Bhamidipati Srirama , Lei Telli Van Der , Herder Paulien
Published: November 2023

Physical infrastructures facilitate much of societal and economic wellbeing of countries, regions and urban areas. In our increasingly urbanizing world, infrastructures in urban areas are densely located and interconnected. The effects of this interconnectedness are being studied increasingly, particularly in light of climate change effects. In this paper, we develop an agent-based simulation model that allows us to study interconnected infrastructure. We present a layered approach that is analogous to GIS overlay approaches, which allows us to integrate representations of different infrastructures. We explore how this approach can help asset managers to gain insights in interconnected infrastructure by estimating their total damage and repair requirements during a flood event. The results show a difference in these estimates, when compared to non-integrated models, highlighting the need for asset managers to consider interconnectedness in infrastructure.
Catchment areas of high-speed rail stations: a model based on spatial analysis using ridership surveys
Authors: Martínez Héctor S. , Moyano Amparo , Coronado José M , Garmendia Maddi
Published: November 2023

This paper focuses on the spatial influence of High-Speed Rail stations, based on the notion of catchment area. Given the features of High-Speed Rail, its operations can and must serve a role beyond the station and the city in which it is located. Using a spatial systemic approach, this paper proposes a method to analyse the factors that may affect the size and shape of the catchment areas according to the relationship between distance and ridership. This study employs data from surveys of six stations of the Spanish high-speed rail system to apply the model and demonstrates that the context is crucial for regional use. The outcome also proves that other relevant factors should be considered in addition to the network to extend the use of highspeed services and increase its profits, which is a potential approach for future research.
Opportunities and challenges for rail transport of solid wood biofuel
Authors: Flodén Jonas
Published: November 2023

The use of solid biofuel for energy in heating plants has increased drastically during the last decades. This substantial and increasing demand has placed focus on delivering biofuel to the plants, as logistics issues are considered one of the key challenges for further increased use of biofuel. Problems in sourcing enough fuel locally due to the increasing size of power plants and environmental concerns has sparked an interest in using multimodal road-rail transport as a cost effective and environmentally friendly way of long-haul transport. A case study is performed at a Swedish district heating plant to investigate the potential of introducing multimodal transport. Extensive calculations are performed in the design and operation of a multimodal system, showing both costs and CO2 emissions. This is analysed in relation to key logistical challenges in the industry. A best case scenario is identified. Conclusions are that the potential for multimodal transport is greatest among the largest plants with large volumes to achieve high resource utilisation of the transport equipment. A shift from road to multimodal transport is facilitated by that a large share of the current road transport flows already pass through a terminal, which improves multimodal transport competitiveness against road transport as this reduced the cost difference. This study leads to better understanding of the strengths and weaknesses of multimodal biofuel transport and has practical implications for anyone in the process of designing such systems.
Viability of electric vehicles in combined day and night delivery: a total cost of ownership example in Germany
Authors: Taefi Tessa T.
Published: November 2023

A review of the body of literature yields general indications that electric freight vehicles can improve emissions and costs in off-hour delivery schemes. However, the literature fails to quantify the savings potential in a combined day and off-hours double-shift usage. Hence, this article qualitatively clusters the advantages of electric vehicles in off-hours delivery schemes and provides quantitative exemplary model calculations on the total costs of ownership in single- and double- shift usage. Surprisingly, the calculations contradict the hypothesis that is commonly deduced in the literature that with a higher utilisation, electric vehicles generally become more competitive compared to their conventional siblings. This study finds that electric medium-duty vehicles are only financially competitive at higher mileages, if the savings achieved by lower operational costs are greater than the costs for battery replacements. These become more frequent at higher mileages; hence a long battery warranty is essential when planning to operate EVs in double-shifts. An elasticity analysis finds that further important parameters influencing the competitiveness of medium-duty electric vehicle compared to conventional diesel models are the discount rate, purchase prices, and the cost of diesel fuel. In conclusion, financial subsidies for purchasing freight EVs might lead to higher numbers of these vehicles. However, increasing the per-kilometre cost advantage of electric freight vehicles would support their utilisation, i.e. in combined day and night shifts, and hence would further mitigate the road freight transport emissions in cities.
Analyzing model uncertainty and economies of scale of the Swedish national freight model to changes in transport demand
Authors: Westin Jonas , Vierth Inge , Jong Gerard De , Karlsson Rune , Krüger Niclas A. , Johansson Magnus
Published: November 2023

The purpose of the paper is to analyze model uncertainty and economies of scale of the Swedish national freight transport model system Samgods to changes in its zone-to-zone base matrices. Even though economies of scale is important for freight transport, few studies analyze model uncertainty and economies of scale at a national level. Compared to many large scale networkbased freight models working on aggregated transport flows, an important feature in Samgods is that it simulates logistics behavior at a disaggregated firm level. The paper studies effects on total tonne- and vehicle-kilometre, modal split, consolidation and logistics costs when the base matrices are scaled up and down and estimates economies of scale for Swedish freight transports. The results indicate that the logistics model can find new logistics solutions for larger demand volumes, mainly by shifting freight to sea transport. If transport volume increases with one percent, average logistics cost per tonne is reduced by around 0.5 percent. Part of the cost reduction comes from increased consolidation of shipments due to larger transport volumes. The results derived in the paper can serve as a reference for empirical validation and comparisons with other large scale freight models. The paper is a first contribution that tries to fill the knowledge gap on the impact of base matrices on transport model outcomes, such as economies of scale, in the context of a full-fledged real-world freight transport model.
Modelling activity-travel behaviour dynamics with panel data: The state-of-the-art
Authors: Kroesen Maarten , Goulias Konstadinos G.
Published: November 2023

The field of travel behaviour dynamics represented a vibrant research area in the 1980s and the 1990s (Golob & Meurs, 1987; Golob, Kitamura, & Long, 1997; Kitamura, 1990), but has since, probably due to lack of mobility panel data, received relatively little attention by transportation researchers. Nevertheless, through the use of panel data (repeated measures of the same individuals) many new insights may be gained with respect to travel behaviour, insights that are fundamentally different from those that can possibly be gained from cross-sectional data.
Causal effects of built environment characteristics on travel behaviour: a longitudinal approach
Authors: Coevering Paul Van De , Maat Kees , Kroesen Maarten , Wee Bert Van
Published: November 2023

The influence of the built environment on travel behaviour and the role of intervening variables such as socio-demographics and travel-related attitudes have long been debated in the literature. To date, most empirical studies have applied cross-sectional designs to investigate their bidirectional relationships. However, these designs provide limited evidence for causality. This study represents one of the first attempts to employ a longitudinal design on these relationships. We applied cross lagged panel structural equation models to a two-wave longitudinal dataset to assess the directions and strengths of the relationships between the built environment, travel behaviour and travel-related attitudes. Results show that the residential built environment has a small but significant influence on car use and travel attitudes. In addition, the built environment influenced travel-related attitudes indicating that people tend to adjust their attitudes to their built environment. This provides some support for land use policies that aim to influence travel behaviour.
Using automatic number plate recognition data to investigate the regularity of vehicle arrivals
Authors: McLeod Fraser N. , Cherrett Tom J. , Box Simon , Waterson Ben J. , Pritchard James A.
Published: November 2023

This paper uses automatically-recorded vehicle number plate data from a network of 22 cameras in Dorset, UK, to investigate the extent to which regular trip making can be determined using the regularity of individual vehicle arrival times across the same sites and time intervals over extended periods of several months and illustrates how a cohort of recognised regular vehicles may provide indicative evidence of traffic delays. Regularity was defined based on minimum numbers of observations over a given period and with specified maximum values of standard deviation in arrival time, with sensitivity to different values being tested. It was found that around one-fifth of all vehicles were regular during the morning peak where the definition required at least 30 observations out of 210 working days and with a standard deviation in arrival time of no more than ten minutes; significantly fewer vehicles were found to be regular in the afternoon peak. The turnover, or churn, of regular vehicles was found to be considerable, with only one-tenth of defined regular vehicles being continuously regular throughout the period and with identified pools of regular drivers halving in size every three months, as vehicles ceased to be regular and where the pool was not updated. This suggests that any database of regular drivers should be updated at least quarterly to ensure that new regular vehicles are included and that old ones are discarded. These findings may have inferences for traffic information systems tailored for different driver groups according to assumed levels of network knowledge.
Scale effect in a LUTI model of Brussels: challenges for policy evaluation
Authors: Jones Jonathan , Peeters Dominique , Thomas Isabelle
Published: November 2023

The aim of this paper is to assess the reliability of policy evaluation based on Land Use and Transport Interactions models, relative to the choice of the Basic Spatial Units. An UrbanSim (+ MATsim) model applied to Brussels (Belgium) is used as the case study. The evolution of the study area over twenty years is forecasted for four levels of Basic Spatial Units and five scenarios (businessas-usual and four alternatives). Results show larger variations between Basic Spatial Units levels than across scenarios. These findings are valid for various sustainability indicators and for a simple cost-benefit analysis aiming at ranking the scenarios. The direction of the variations resulting from the implementation of the scenarios remains, however, the same for all Basic Spatial Units levels. Hence, the influence of the scale on policy evaluation based on Land Use and Transport Interactions models appears limited when it is only intended to compare scenarios, but it will have a crucial role when evaluations are based on absolute variations or threshold values.
Model-based estimation of private charging demand at public charging stations
Authors: Schüßler Maximilian , Niels Tanja , Bogenberger Klaus
Published: November 2023

In recent years, many concepts have been developed on how to build a sufficient charging infrastructure to satisfy the demand of Battery Electric Vehicle (BEV) users. However, the focus of these approaches often lies on the spatial distribution of charging stations and the amount of charging demand is often given beforehand. In this paper, we describe a model to estimate the future private charging demand at public charging stations for different regions. Several aspects that influence the needed amount of charging stations are considered, e.g. a growing range of BEVs and the behavior of different user groups. For example, we distinguish between BEV users with or without a home charging possibility. The spatial distribution of these user groups is modeled using an agent-based approach, respecting sociodemographic properties. Forecasting the spread of BEVs strongly depends on the assumptions made regarding these influencing factors, where different current studies obtain deviant results. Therefore, in a case study for the city of Munich, we consider three different scenarios assuming a pessimistic, a realistic and an optimistic spread of BEVs in the year 2020. Additionally, we present a sensitivity analysis of the influencing factors and identify the ones that have the highest impact on the future charging demand: the overall adoption rate of BEVs is the parameter that influences the output the most. In fact, an adoption rate that is 10% higher than expected leads to an increase in charging demand of about 16%. This means, that our model strongly depends on reliable input data. The output of our model is the expected number of charging events requested in a certain region on an average day. Together with the average parking time and the temporal distribution of car arrivals at public charging stations, it is possible to obtain the necessary size of the charging infrastructure such that the demand can be satisfied even during peak hours. These results can be used as an input to existing optimization algorithms for the allocation of charging stations.
Assessing the effects of a growing electric vehicle fleet using a microscopic travel demand model
Authors: Weiss Christine , Heilig Michael , Mallig Nicolai , Chlond Bastian , Franke Thomas , Schneidereit Tina , Vortisch Peter
Published: November 2023

The German government seeks to increase the number of electric vehicles (EV) in the German car fleet to one million by 2020. Since some characteristics of EVs differ from conventional cars, there is an increasing need to assess the various impacts of a growing EV fleet. In this work, we have focused on possible effects related to the field of transport. We identified three important aspects and evaluated them over a period of one week using the microscopic travel demand model mobiTopp. First, we modelled the potential EV user groups of the near future by developing an EV user model; this model considers both interest in EVs and suitability for EV usage. Second, we simulated the travel behaviour of EV users; we used an EV usage model to consider the restrictions of EVs in choice decisions and also compared the usage behaviour of EV and conventional cars users. Third, we analysed the power consumption of the simulated EVs and evaluated the load peaks based on the simulated travel patterns. Our results indicate that a growing EV fleet implies a more heterogeneous distribution of EVs among car owners. They also indicate that the trip chain length of battery electric vehicles (BEVs) is much lower than that of extended range electric vehicles (EREVs) and conventional cars on average.
Impacts of real-time feedback on driving behaviour: a casestudy of bus passenger drivers
Authors: Rolim Catarina , Baptista Patrícia , Duarte Gonçalo , Farias Tiago , Pereira João
Published: November 2023

Over the years, there has been an increase in the focus on driving behaviour as a solution to minimize the road transportation high levels of energy consumption, as well as the emission of pollutants. The aim of this study was to analyse the impacts of real-time feedback on the driving behaviour of bus drivers, and to assess the potential impact of the characteristics of these subjects (age and time working at the company) on such behaviour. Data was collected with an on-board device installed in buses of a Portuguese urban transport operator. Three monitoring periods were considered: an initial phase, in which real-time feedback was given to drivers (phase 1), followed by a period of no feedback (phase 2), and then a final stage in which feedback was resumed (phase 3). A repeated measures analysis of variance was performed to assess the impacts of feedback in several driving indicators across the aforementioned phases. The results revealed that bus drivers accrue benefits from the feedback received, with significant differences between the three monitoring periods for all driving indicators analysed. After suspending the feedback, increases between 6% and 55% of the incidence of undesired driving indicators were observed, mainly in extreme brakes, extreme accelerations, excess RPM, and hard stops. Such insights can provide bus operators with new tools to develop programs promoting efficient driving behaviours.
How bicycling sharing system usage is affected by land use and urban form: analysis from system and user perspectives
Authors: Faghih-Imani Ahmadreza , Eluru Naveen , Paleti Rajesh
Published: November 2023

There is a rapid growth of bicycle-sharing systems (BSS) around the world. Cities are supporting these systems as a more sustainable transport mode for short trips. Given the relatively recent adoption of BSS, there is substantial interest in understanding how these systems impact urban transportation. In this paper, we examine the functioning of the hugely successful New York City CitiBike system. We focus on the interaction of BSS with land-use and built environment attributes and the influence of weather condition and temporal characteristics on BSS usage. Towards this end, CitiBike system is analyzed along two dimensions: (1) at the system level, we examine the hourly station level arrival and departure rates using a linear mixed model and (2) at the trip level, we investigate users’ destination station choice preferences after they pick up a bicycle from a station employing a random utility maximization approach. The results highlight clear spatial and temporal differences in the usage of CitiBike by users with annual membership and users with temporary passes. Overall, our analysis provides a framework and useful insights for cities that are planning to install a new bicycle sharing system or to expand an existing system
Editorial: Special issue of the 5th Symposium of the European Association of Research in Transportation
Authors: Cranenburgh Sander Van , Dekker Thijs
Published: November 2023

This special issue presents seven selected papers from the 5th Symposium of the European Association of Research in Transportation (hEART) which was held in September 2016 in Delft, The Netherlands, and was organised by Delft University of Technology. The contributions cover a wide range of topics in transportation, reflecting the broad scope of the hEART symposium series, including but not limited to travel behaviour, travel survey methods, railway freight as well as (terminal) logistics. As editors of this special issue we are very grateful for the efforts made by the authors, in particular their enduring efforts to push the quality of their contributions to a higher level during the review process. Also, we like to take the opportunity to thank all the reviewers for their constructive feedback and suggestions for improvement. This editorial provides a brief overview of the hEART2016 symposium. After that, an overview is given of the seven contributions that form this special issue.
Application of aggregate container terminal data for the development of time-of-day models predicting truck arrivals
Authors: Kourounioti Ioanna , Polydoropoulou Amalia
Published: November 2023

Workload forecasting related to truck arrivals is of essential importance not only for optimal resource allocation but also for encountering delays and bottlenecks in the landside operations of terminals. In order to increase their efficiency, some ports have tried to implement various methods such as Truck Appointment Systems (TAS) but, in general, information on the arrival times of trucks to pick up containers remains unreliable and scarce. This paper sought to develop pick-up time-of-day models for import containers using data easily retrieved from Terminal Operating Systems (TOS). Model results indicate that the receiver of goods and container characteristics are among the main factors affecting pick-up time-of-day. Differentiation is observed between the different days of the week. The developed Time-Of- Day (TOD) models can be used to calculate the probability of drayage truck arrival times. The application of the proposed methodology proves helpful when reliable information of truck arrivals is unavailable, and can also be used alongside TAS implementation to assist terminal operators.
Bayesian networks for constrained location choice modeling using structural restrictions and model averaging
Authors: Ma Tai-Yu , Klein Sylvain
Published: November 2023

In this work, we propose a Bayesian network approach by using structural restrictions and a model averaging algorithm for modeling the location choice of discretionary activities. In a first stage, we delimit individuals’ location choice which is set by generating an ellipse that uses empirical detour factors and a home-work axis. The choice set is further refined by an individual’s space-time constraints in order to identify the constrained destination choice set. We use structural restrictions and a model averaging method to learn the network structure of the Bayesian network in order to predict the heuristics of individuals’ location selection. The empirical study shows the proposed method can effectively obtain Bayesian networks with a consistent dependency structure. The empirical study suggests activity schedule factors significantly influence location choice decisions.
Table of contents
Authors: - -
Published: November 2023

Table of contents for Volume 19, Issue 1.
Editorial
Authors: van Nunen Karolien , Reniers Genserik , van Gelder Pieter , Goerlandt Floris , Li Jie
Published: November 2023

In 2017, the Journal of Integrated Security Science was founded at the Safety and Security Science section at Delft University of Technology, the Netherlands. Now, in 2021, we are happy to announce that we are rebranding the journal by taking it into an adjusted thematic and theoretical avenue: with a new journal name, a revised scope and updated editorial board, we aim for the journal to become an established value within the field of security and safety science, that guarantees high quality standards. In this editorial, we will elaborate upon the implemented changes, and our goals for the future.
Blockchain adoption factors for SMEs in supply chain management
Authors: Lanzini Filippo , Ubacht Jolien , De Greeff Joachim
Published: November 2023

Blockchain-based applications can enhance the sharing of information in processes involving multiple types of stakeholders, as in Supply Chain Management (SCM). A supply chain network can benefit from the visibility of the flow of goods, money, and information enabled by blockchain technology. So far, only limited evidence is available on the perspective of Small and Medium-sized Enterprises (SMEs) on the adoption of blockchain-based applications in their business processes. This may lead to a heavily diminished role for SMEs in SCM if large consortia unilaterally decide to adopt a blockchain-based architecture to improve the performance of the entire supply chain. Therefore, we conducted a study to explore which factors influence SMEs’ intention to adopt blockchain technology. Based on a literature review into technology adoption frameworks, we derived the technological, organizational, and environmental (TOE) factors that can play a role in their decision-making process. We distributed a survey amongst European SMEs using the multi-criteria decision-making method of the Best-Worst Method (BWM) to elicit the relative weights of these factors. The data analyses show that in contrast to other studies into technology adoption, the SMEs’ intention to adopt blockchain-based applications is primarily influenced by organizational rather than by technological and environmental factors. This implies that SMEs are best supported by showing blockchain’s organizational benefits and by training senior executives at their company.
A systematic review of multi-objective optimization applications in reverse logistics
Authors: Arab Alireza
Published: November 2023

Reverse logistics (RL) have received the attention of the practitioners and researchers of the fields of supply chain and logistics due to, inter alia, the increase in public awareness, boundless waste generation, and environmental issues. To formulate RL issues, multi-objective decision-making (MODM) techniques are of the most practical approaches. MODM methods refer to an optimization problem with multiple objectives that usually conflict with each other and must be satisfied simultaneously. However, no literature review had yet undertaken a comprehensive systematic review of the utilization of MODM methods in RL. Therefore, 205 relevant papers published in scientific journals are considered and investigated from descriptive and technical content dimensions in this paper. The results clearly illustrate the quantitative increase in the number of papers published in this field over the last 20 years. This increase depicts that the researchers' focus on this field has been increasing in the last decade. Content analysis on the main focus areas, case study sector, solution methodology, uncertainty modeling, period(s), product(s), and numerous objectives that these 205 papers considered in their study helped to visualize the current state of this field and reveal research gaps and introduce future directions. Finally, some potential topics are provided based on the results that cover all reverse logistics activities and also content analysis categories.
Madeleine Férat ou la mémoire dans la peau : l’imprégnation comme procédé mémoriel dans le roman naturaliste
Authors: Rondou Katherine
Published: November 2023

À l’époque où Émile Zola publie Madeleine Férat (1868), le motif de la courtisane amoureuse constitue déjà un poncif romantique. Le futur chef de file des naturalistes souhaite par conséquent prendre ses distances avec une conception dépassée de la femme perdue repentie et s’empare de l’incarnation par excellence de la pécheresse convertie dans l’imaginaire judéo-chrétien, sainte Marie-Madeleine, afin de la détourner. Alors que les évangiles construisent le personnage sur la dichotomie de la chute et de la rédemption, le romancier refuse à son héroïne l’oubli de son passé. L’écrivain suggère d’un chapitre à l’autre la progression implacable de la destinée dramatique de Madeleine Férat et modernise le Fatum antique, comme il le fera par la suite dans les Rougon-Macquart, en s’inspirant des théories médicales de son temps, ici les publications du Dr Prosper Lucas sur l’imprégnation séminale. Madeleine Férat subit malgré elle la domination de lois physiologiques qui s’opposent à ses valeurs morales, et le suicide semble dès lors son unique échappatoire. Sous la plume de Zola, Marie de Magdala devient une héroïne tragique.
Green Plants as a Sustainable Solution to Air Pollution
Authors: Joshi Nitin , Gupta Charu Khosla , Mangla Yash , Chowdhuri Arijit
Published: November 2023

In today’s global context, the escalation of air pollution stands out as an immensely critical environmental challenge that has attained a worldwide magnitude. This pressing issue not only impacts every living organism on our planet but is also intricately linked to the phenomenon of climate change. The significant increase in vehicular traffic, rapid urbanization, and infrastructure development have indirectly contributed to a higher concentration of harmful gaseous and particulate pollutants in the atmosphere, posing serious risks to human health. Extensive research has thoroughly documented the adverse effects of these air pollutants, with mortality and morbidity rates varying depending on the type of pollutant and the duration of exposure. However, amidst this crisis, green plants emerge as a cost-effective and promising solution to combat environmental pollution, presenting several additional benefits. Specifically, pollutiontolerant plant species are crucial in reducing ambient air pollution and the urban heat island effect. To assess a plant’s tolerance towards air pollution, experts use the air pollution tolerance index (APTI), which calculates crucial factors such as ascorbic acid, total chlorophyll, pH, and relative water content in the plant. This determination provides a reliable method for categorizing plants into either tolerant or sensitive types in the face of air pollution. Moreover, the morphological characteristics of leaves, such as stomata distribution and density, cuticle thickness, and trichome density, play an essential role in adsorbing and absorbing particulate matter from the air. These inherent qualities further enhance plants’ potential to combat air pollution in a sustainable manner, making them valuable assets for the future. In light of this, the present review highlights the impressive capacity of plants to remediate air pollutants and explores the various strategies employed in this crucial endeavor. By leveraging the remarkable capabilities of green plants, we have the opportunity to address the air pollution crisis and embrace a sustainable path for the times to come. These remarkable organisms could be the sustainable saviors we need to protect our environment and secure a healthier future for all.
Comparison of Total Nitrogen estimation by Kjeldahl Method and CHNS Analyzer in Dry Tropical Grassland
Authors: Gautam Vijay P. , Mishra Swati , Ahmed Haseen
Published: November 2023

The Dumas method (CHNS analyzer) is replacing the traditional Kjeldahl method as the method of choice for N analysis due to advancements in dry combustion nitrogen (N) analyzer technology and the high cost of disposing of hazardous laboratory waste chemicals. As a result, a comparison of the Dumas method (CHNS analyzer) with the Kjeldahl method is critical. Typically, such comparisons were conducted on a small number of distinct samples. The goal of this study was to compare the performance of instruments that use the automated Dumas method (CHNS analyzer) and the Kjeldahl method for N analysis of agricultural materials in a high-throughput laboratory setting. Using both instruments, N concentrations in manure, sewage sludge, plant tissue, plant seeds, and feedstuff fibres were determined. We collected samples for the analysis of organic matter from the horticulture area at the Banaras Hindu University campus in Varanasi, and total Nitrogen (N) was estimated using the Kjeldahl (wet oxidation) and Perkin-Elmer 2.400 Series II-CHN Mode techniques (dry oxidation or combustion). The positive correlation (r = 0.94**) of the Kjeldahl method with N- determination from a CHNS analyzer demonstrates that the method is practical for routinely determining the total nitrogen content of soils
Use of Janus Kinase (JAK) Inhibitors in the Treatment of Rheumatoid Arthritis: A Review of Efficacy and Safety Compared to Conventional Therapies
Authors: Gomez Maria Isabel
Published: November 2023

Rheumatoid Arthritis (RA) is a complex autoimmune disorder characterized by chronic synovial inflammation, leading to progressive joint deterioration and substantial morbidity. While conventional disease-modifying antirheumatic drugs (DMARDs) have been the cornerstone of RA management, the emergence of Janus Kinase (JAK) inhibitors has revolutionized the treatment paradigm. This comprehensive review paper analyzes the efficacy, safety, and practical considerations associated with JAK inhibitors in managing RA juxtaposed with conventional therapies. Through an exploration of the mechanism of action, the efficacy of JAK inhibitors in ameliorating disease activity and improving patient outcomes is underscored. The review also addresses the safety concerns surrounding using JAK inhibitors, emphasizing the need to monitor potential adverse events. Furthermore, the paper discusses the role of nonsteroidal anti-inflammatory drugs (NSAIDs), corticosteroids, and DMARDs in RA management, highlighting their limitations and benefits. Practical clinical recommendations for using JAK inhibitors are elucidated, considering their positioning as a second-line therapy for patients with inadequate response or intolerance to conventional DMARDs. Finally, the abstract emphasizes the importance of ongoing research and post-marketing surveillance to comprehensively evaluate the long-term implications of JAK inhibitors, aiming to optimize their integration within personalized treatment strategies for RA.
Deslocamento e destruição
Authors: Abreu Clara Habib de Salles
Published: November 2023

Este artigo visa investigar possíveis relações entre transferência de objetos culturais, destruição e repatriação. Nosso principal interesse é pensar sobre como deslocamentos violentos de objetos de seus contextos originários operam destruições materiais e simbólicas de caráter iconoclasta e como alternativas de restituição podem funcionar como instrumentos de reparação histórica. Para refletirmos sobre essas questões trabalhamos com objetos africanos que estão no cerne do debate sobre repatriação como, por exemplo, a Máscara de Idia e também objetos brasileiros de tradição africana que nos ajudam a pensar em possibilidades de restituição dentro do contexto de um mesmo país, como os pertencentes à coleção “Nosso Sagrado”.
Survival Analysis and Hazard of Log Logistic Distribution on Type I Censored Data Parametrically
Authors: Kurniawan Ardi , Hosana Ruth , Sari Ni Wayan Widya Septia
Published: November 2023

Survival Analysis is a research method that examines the survival time of individuals or experimental units in relation to events such as death, disease, recovery, or other experiences. This study utilizes a parametric survival analysis model with a 2 parameter log logistic distribution and Maximum Likelihood Estimation (MLE) method to analyze the survival of students during their study period. The log logistic distribution is chosen due to its ability to capture early or late failure patterns. The objective of this research is to analyze type I censored survival data using the log logistic distribution applied to secondary data on student study duration. The dataset consists of 98 observations. The calculated values for the β and γ parameters of the 2 parameters log logistic distribution are 2.12831 and 0.0918891, respectively. The probability of students completing their studies by semester 8 (hazard function h(8)) is 0.370102, while the probability of students continuing their studies in semester 9 (survival function s(9)) is 0.320817.
Detection by super-resolution microscopy of viral proteins inside bloodborne extracellular vesicles
Authors: Singh Rakesh K. , Santos Mark F. , Herndon Charles , Gieler Brandon A. , Lee Isaac , Chen Jiahui , Lorico Aurelio
Published: November 2023

Aim: Extracellular vesicles (EVs) are small particles released by all cells, including virally infected cells, into the extracellular space. They play a role in various cellular processes, including intercellular communication, signaling, and immunity, and carry several biomolecules like proteins, lipids, and nucleic acids that can modulate cellular functions mostly by releasing their cargo inside the target cells via the endocytic pathway. One of the most exciting aspects of EV physiology is its potential in liquid biopsy as a diagnostic and prognostic marker. However, due to their extremely small size and lack of a molecular approach to examine intravesicular content or cargo, we cannot fully utilize their potential in healthcare. Methods: Here, we present a novel approach that allows examining bloodborne EVs at a single-particle level with the ability to examine their cargo without disrupting structural integrity. Our technique utilizes super-resolution microscopy and a unique permeabilization process that maintains structural integrity while facilitating the examination of EV cargo. We used a mild-detergent-based permeabilization buffer that protects the integrity of EVs, minimizes background, and improves detection. Results: Utilizing this approach, we were able to recognize viral proteins of SARS-CoV-2 virus in COVID-19 patients, including spike and nucleocapsid. Surprisingly, we found an almost equal amount of spike protein inside and on the surface of bloodborne EVs. This would have proven difficult to determine using other conventional methods. Conclusion: To summarize, we have developed an easy-to-perform, sensitive, and highly efficient method that offers a mechanism to examine bloodborne EV cargo without disrupting their structural integrity.
Baya Project: Building Structural Shells in Wicker
Authors: Leyral Marc , Chef Quentin , Hymans Marc
Published: November 2023

The growing of natural fibres ‐ such as wicker ‐ is deeply virtuous: it helps to diversify the forest cover, itrequires limited inputs ??? even in water, little maintenance, and its CO2 emissions are minimal. Their uses in basketry date back to the Neolithic period, and
even probably before. People around the world have employed braiding technics and basketry craft to design a large panel of objects, clothes, furniture, boats, etc. In the field of architecture and construction, we can identify natural fibre uses in numerous of vernacular shelters, but they
are generally limited to non-structural filling elements. The scarcity of mechanical characterization of wicker material in the literature is underlying that, since now, these kinds of materials are not commonly used to a structural purpose. The aim of our research is to demonstrate the feasibility
to design and build structural wicker braided shells for architectural purposes, and to provide designers with the necessary tools for this process. Thanks to wicker mechanical characterization and to experimental measurements, we developed a law which defines a relation between density and
orientation of the stems and the fields of principal stresses on an idealized continuous surface: “each field of stress is related to an optimal braiding”. These data have supplied an algorithm, BAYA, making design and optimization of braided shells accessible and easy to use for
architects and practitioners. Even if our research focused on wicker, it should be easily adaptable to other fibres and plants as, for instance ,rattan or reed. This innovative research is demonstrated by the realization of a full-scale public pavilion hanging from trees on the belvedere of
the Butte du Chapeau Rouge park (Paris XIX), and a 12.8‐meter-long footbridge for the Utopies Constructives festival in Richelieu’s Park.
Disproof of Several Recently Published Results in Ring Theory
Authors: Pandey S K
Published: November 2023

In this note we consolidate and give a brief description of several recently published results in ring theory having disproof. These results have been published during 2016 to 2021 in the so called non-predatory reputed mathematical journals indexed in the well known database like Scopus. We have considered results on rings in which each element is a sum of two idempotents appeared in Canad. Math. Bull. (2016), weakly tripotent rings appeared in Bull. Korean Math. Soc. (2018) and Rendiconti Sem. Mat. Univ. Pol. Torino (2021), involution t-clean rings appeared in Eur. J. Pure Appl. Math (2022) and strongly 2-nil clean rings with units of order two appeared in Eur. J. Pure Appl. Math (2023).
Intelligent Feedrate Optimization using an Uncertainty-aware Digital Twin within a Model Predictive Control Framework
Authors: Kim Heejin , Kontar Raed , Okwudire Chinedum
Published: November 2023

The future of intelligent manufacturing machines involves autonomous selection of process parameters to maximize productivity while maintaining quality within specified constraints. To effectively optimize process parameters, these machines need to adapt to existing uncertainties in the physical system. This paper proposes a novel framework and methodology for feedrate optimization that is based on a physics-informed data-driven digital twin with quantified uncertainty. The servo dynamics are modeled using a digital twin, which incorporates the known uncertainty in the physics-based models and predicts the distribution of contour error using a data-driven model that learns the unknown uncertainty on-the-fly by sensor measurements. Using the quantified uncertainty, the proposed feedrate optimization maximizes productivity while maintaining quality under desired servo error constraints and stringency (i.e., the tolerance for constraint violation under uncertainty) using a model predictive control framework. Experimental results obtained using a 3-axis desktop CNC machine tool and a desktop 3D printer demonstrate significant cycle time reductions of up to 38% and 17% respectively, while staying close to the error tolerances compared to the existing methods.