Entire Route Research Articles

Monitoring Perishable Commodities Using Cellular IoT: An Intelligent Real-Time Conditions Tracker Design

Perishable product losses can occur throughout postharvest handling. Proper monitoring of key environmental conditions during this period is essential for predicting quality losses throughout their shelf life. This paper presents the design and testing of a portable and compact datalogger for the real-time monitoring of environmental conditions throughout the food supply chain. The device developed incorporates high-precision sensors to measure temperature, relative humidity, CO2 concentration, luminosity and vibrations, as well as wireless communication capabilities for data transmission, simplifying real-time monitoring over existing multi-component systems while keeping costs affordable. Strategies to optimize power consumption allow a month of battery life, being able to cover entire periods of transport and storage, according to the results of the autonomy test performed on the device. The datalogger uses NB-IoT and relies on other wireless communication protocols if not available to send sensor data to a cloud platform. Comparative testing with commercial dataloggers has been carried out to verify correct device measurements, and field testing has validated successful real-time data transmission along an entire refrigerated transport route. The functionality and autonomy of the proposed device meet the needs of live remote monitoring to help reduce food losses.

Optimizing turning logic of glass curtain wall cleaning robot

Abstract. In contemporary urban environments, there has been a notable increase in the construction of high-rise edifices with glass curtain walls. While glass curtain walls contribute to the aesthetic appeal of buildings, they also give rise to a number of challenges. In recent decades, cleaning robots have been developed to address the issue of maintaining glass curtain walls. However, the challenge of efficiently avoiding obstacles and gaps on the glass curtain remains. The research aims to optimize the trajectory of glass curtain wall cleaning robots. A series of simulations were conducted using MATLAB 2024b and the RobotCraft Robotics Playgrounds add-on. The robot is required to traverse a defined maze, which features a 90-degree turn. The time required for each operational logic to traverse the entire route from the initial point to the final destination has been meticulously documented. The results of these simulations are compared in a chart in order to identify a logic that will result in a faster average speed for the robot. The initial experiment yielded results indicating that the turning is excessively sharp and rigid. Accordingly, the distance detection has been increased in the subsequent iteration to facilitate an earlier turning point. Moreover, an increase in the rotational speed of the motor on the corresponding side was implemented to expand the turning radius, thereby facilitating a more seamless and fluid rotation. In essence, the robot has been optimized to achieve a balance between spatial utilization and high average speed. The refinement of the turning path has been shown to enhance the overall cleaning efficiency while maintaining an exceptional ability to avoid obstacles.

VibraSIG - Modeling railway structure-borne noise and vibrations and implementation in QGIS geographic information software

In the context of engineering studies for passenger rail line projects, a method for predicting vibration and structure-borne noise levels in buildings close to the line is needed on the scale of a town or territory. ACOUSTB has developed VibraSig, a method for calculating railway vibration and structure-borne noise, based on two numerical models (VibraFer, CSTB and MEFISSTO, CSTB). A numerical model in VibraFer is used to define a railway excitation source term. A numerical model in MEFISSTO is used to calculate the vibratory response of the tunnel and the ground up to the building on a cross-section. A statistical building response model is used to estimate structure-borne noise and floor vibration levels. Finally, the method for predicting vibration and structure-borne noise levels is extended to the entire project route, and the results are visualized for each building on a Geographic Information System (GIS).

Acoustic and vibrations measurments in an autonomous shuttle bus

In response to the ADEME's call for Autonomous Road Vehicle Experimentation projects, a consortium was created to propose the SAM project about Safety and Acceptability of Autonomous Driving and Mobility. It was composed of industrial and research teams, associated with local partners. SAM is a national project involving large-scale trials of autonomous driving and mobility on open roads. The assessments covered several topics, including environmental impacts, focusing on air pollution, noise and the life cycle of components. Cerema proposed a methodology to characterize acoustic and vibration levels for autonomous driving in the specific site near Paris. The tests consisted in instrumenting the interiors of an automated shuttle and a conventional car to determine the user's feelings. The vehicles were driven in a quiet area and in a high traffic area. The results displayed by Cerema are based on statistical studies on 20 vehicle passages for each experiment. The indicators were characterized for the entire route and by homogeneous sections. In fluid navigation situation, the measurements showed that the acoustic and vibration impacts are minimal. However, the tests have highlighted the effects of the lack of anticipation of an automated shuttle during specific events requiring rapid braking.

Multi-Horizon Model Predictive Control for Energy Management in Zero-Emission High-Speed Passenger Vessels

Abstract High-speed passenger vessels (HSPVs) play an important role in coastal regions due to their high energy consumption and emissions. This study develops an optimal energy management system (EMS) for a zero-emission hybrid power system, powered by a fuel cell (FC) and a battery energy storage system (BESS). The global optimal solution for loading the FC and operating the BESS is computed using a linear programming (LP) approach, assuming a priori knowledge of the complete operational profile. Since the global solution is not realizable in an onboard EMS, the main objective of this paper is to develop an algorithm for real-time application. A multi-horizon model predictive control (MH-MPC) algorithm is applied to a model of the power system to solve the optimization problem with a prediction mechanism over the entire route. This approach is benchmarked against the global LP solution to evaluate the effectiveness of the proposed EMS. The results highlight the potential of the MH-MPC approach for achieving a near-optimal EMS in a zero-emission HSPV.

GAP FILLING ALGORITHM FOR MOTION CAPTURE DATA TO CREATE REALISTIC VEHICLE ANIMATION

The dynamic development of the entertainment market entails the need to develop new methods enabling the application of current scientific achievements. Motion capture is one of the cutting-edge technologies that plays a key role in movement and trajectory computer mapping. The use of optical systems allows one to obtain highly precise motion data that is often applied in computer animations. This study aimed to define the research methodology proposed to analyze the movement of remotely controlled cars utilizing developed gap filling algorithm, a part of post-processing, for creating realistic vehicle animation. On a specially prepared model, six various types of movements were recorded, such as: driving straight line forward, driving straight line backwards, driving on a curve to the left, driving on a curve to the right and driving around a roundabout on both sides. These movements were recorded using a VICON passive motion capture system. As a result, three-dimensional models of vehicles were created that were further post-processed, mainly by filling in the gaps in the trajectories. The case study highlighted problems such as missing points at the beginning and end of the recordings. Therefore, algorithm was developed to solve the above-mentioned problem and allowed for obtaining an accurate movement trajectory throughout the entire route. Realistic animations were created from the prepared data. The preliminary studies allowed one for the verification of the research method and implemented algorithm for obtaining animations reflecting accurate movements.

A New Accurate Aircraft Trajectory Prediction in Terminal Airspace Based on Spatio-Temporal Attention Mechanism

Trajectory prediction serves as a prerequisite for future trajectory-based operation, significantly reducing the uncertainty of aircraft movement information within airspace by scientifically forecasting the three-dimensional positions of aircraft over a certain period. As convergence points in the aviation network, airport terminal airspace exhibits the most complex traffic conditions in the entire air route network. It has stronger mutual influences and interactions among aircraft compared to the en-route phase. Current research typically uses the trajectory time series information of a single aircraft as input for subsequent predictions. However, it often lacks consideration of the close-range spatial interactions between multiple aircraft in the terminal airspace. This results in a gap in the study of aircraft trajectory prediction that couples spatiotemporal features. This paper aims to predict the four-dimensional trajectories of aircraft in terminal airspace, constructing a Spatio-Temporal Transformer (ST-Transformer) prediction model based on temporal and spatial attention mechanisms. Using radar aircraft trajectory data from the Guangzhou Baiyun Airport terminal airspace, the results indicate that the proposed ST-Transformer model has a smaller prediction error compared to mainstream deep learning prediction models. This demonstrates that the model can better integrate the temporal sequence correlation of trajectory features and the potential spatial interaction information among trajectories for accurate prediction.

Увеличение продолжительности работы установки электроцентробежного насоса для повышения безопасности и сокращения рисков при спускоподъемных операциях

The study analyzes basic complications associated with generating mechanical impurities; numeric modeling to optimize the electrical submersible pump operation has been performed. Modeling the fluid flow in combination with erosion models has been used to determine the key factors facilitating the erosion of the electrical submersible pump action wheel impeller during oil production. In order to obtain a complete view of the flow and erosion properties, modeling has been performed for the entire fluid flow route. Modeling of the flow and the action wheel component erosion has been performed to determine the impact of the flow imbalance as well as to ensure the boundary conditions at the input for the modeling. The modeling results have shown: the rotational flow introduced in the mixing point at the action wheel input significantly impacts the strength properties of the modeled object; the area most exposed to erosion is the area of the action wheel impeller. The values of loss of material have been determined via the time sequence of geometry changes in the compounds in combination with the actual hydraulic operational parameters. The flow trajectories proposed for modeling show that the recirculating flow is the dominant. It is widely adopted that recirculation is one of the main causes of increased erosion in the compounds of the electrical submersible pump as it leads to the high frequency of high-speed impacts by sand particles. In order to reduce the erosion risk, the analysis aiming to identify the impeller geometrical parameters has revealed that the erosion rate in the compound can be reduced by decreasing the inclination of the action wheel impeller. The study has demonstrated that numerical modeling can provide a detailed and precise evaluation of erosion potential in cases associated with the high velocity of fluid flow with particles of mechanical impurities.

Research on an Autonomous Localization Method for Trains Based on Pulse Observation in a Tunnel Environment.

China's rail transit system is developing rapidly, but achieving seamless high-precision localization of trains throughout the entire route in closed environments such as tunnels and culverts still faces significant challenges. Traditional localization technologies cannot meet current demands, and the present paper proposes an autonomous localization method for trains based on pulse observation in a tunnel environment. First, the Letts criterion is used to eliminate abnormal gyro data, the CEEMDAN method is employed for signal decomposition, and the decomposed signals are classified using the continuous mean square error and norm method. Noise reduction is performed using forward linear filtering and dynamic threshold filtering, respectively, maximizing the retention of its effective signal components. A SINS/OD integrated localization model is established, and an observation equation is constructed based on velocity matching, resulting in an 18-dimensional complex state space model. Finally, the EM algorithm is used to address Non-Line-Of-Sight and multipath effect errors. The optimized model is then applied in the Kalman filter to better adapt to the system's observation conditions. By dynamically adjusting the noise covariance, the localization system can continue to maintain continuous high-precision position information output in a tunnel environment.

Sustainability of biomass pyrolysis for bio-aromatics and bio-phenols production: Life cycle assessment of stepwise catalytic approach

The high-valued utilization of biomass resources remains challenging due to their complex biochemical compositions and limited product selectivity. Herein, we propose a novel biomass stepwise catalytic pyrolysis process to efficiently produce aromatic hydrocarbons and phenols by leveraging the distinct thermal stability of biomass components and their compatibility with ZSM-5 and biochar-based catalysts. A life cycle assessment (LCA) is conducted to evaluate the energy consumption and environmental impact of this innovative process compared to conventional methods. Our findings reveal that this approach significantly reduces the energy consumption by 51.76–90.02 % across different application scenarios of by-product biochar. Additionally, using biochar as a soil amendment contributes to carbon negativity, achieving a net greenhouse gas (GHG) emission reduction of up to 6 t CO2 eq for producing 8.325 t aromatics and 1 t phenol. The first-stage catalytic pyrolysis for producing aromatic hydrocarbons is identified as the major contributor to environmental impact, mainly due to ZSM-5 catalyst usage and loss, while the second stage for phenol production has a comparatively minor impact. Finally, sensitivity analysis of the key parameters highlights areas for process optimization, including reducing catalyst dosage, minimizing energy consumption, and improving phenol yield, which are crucial for enhancing the environmental and economic viability of the entire route. This study provides a detailed LCA and offers insights for future improvements in biomass conversion technology.

Modifikasi Produksi dan Biaya Bahan Bakar Minyak pada Kapal Ciremai

Some of the main research problems are the lack of fuel efficiency use, difficulties in loading and unloading process, the refueling process tardiness and the ships route’s delay of the determined and planned routes that could affect the Ciremai Ship’s On Time Performance (OTP). The research aims to determine and analyze the effect of production and fuel oil cost modifications based on the income of Ciremai Ship and its implications for its financial performance after “Three in One” modification. This research used Descriptive statistical analysis method and hypothesis testing using SmartPLS-3. The research sample was taken from the entire routes of Ciremai Ship over the last four years of 48 months. The secondary research data was taken from the financial reports related to production modifications, fuel oil costs, the income and financial performance of the ship. Research findings show that the production modifications have a direct influence on financial performance while fuel costs and income do not have a direct influence on it. The production modifications do not have a direct effect on income instead fuel costs have a direct effect on income and production modifications do not have an indirect effect on financial performance through income.

Managing oversaturation in BRT corridors: A new approach of timetabling for resilience enhancement using a tailored integer L-shaped algorithm

Bus rapid transit (BRT) is a high-capacity public transport system that typically operates along urban transit corridors with dense travel demand. Maintaining the efficiency and stability of the BRT is paramount for daily transport operations. Owing to the difficulty in ensuring an exclusive right-of-way along the entire route, stochastic congestion events may occur resulting from road segments without dedicated BRT lanes. This may lead to volatility in travel time and resulting in passenger stranding, determined as common-case disruptions in this study. These common-case disruptions frequently occur in the daily operation of oversaturated BRT routes. To manage and mitigate their negative impacts, a novel timetabling problem for enhancing the resilience of a BRT system was proposed to assess the ability of the system to withstand and recover from these disruptions. We formulated the problem as a two-stage stochastic mixed-integer optimization model and designed an exact algorithm based on a tailored integer L-shaped method. We then analyzed the structural properties of our model and developed several acceleration techniques to further improve the efficiency of the algorithm. The computational results show that the proposed algorithm outperforms the commercial solver in large-scale instances and can provide near-optimal solutions when the commercial solver is invalid. Besides, external comparisons with dynamic programming also demonstrate the superiority of the proposed algorithm in solution efficiency. Compared with the benchmark timetabling problem, which aims to reduce passenger waiting time, the proposed method can efficiently reduce the duration of the oversaturation period by 35.3%.

Cultivated plants and their wild relatives of Central Russia and the North Caucasus (results of a collecting mission of 2023)

In 2023, field explorations of cultivated plants and their wild relatives were carried out in the regions of the Volga Upland, the western part of the Caspian Lowland and the Stavropol Upland with the aim of further replenishing seed and herbarium collections of VIR.A total of 525 samples of CWR and cultivated plants were collected, including 200 are herbarium sheets, 323 seed samples of cultivated plants and CWR, and a couple of cuttings. The collected material encompasses 145 species, including 91 cultivars. Seeds of the cultivars were purchased at markets, in supermarket chains and from local residents. The following areas were examined in detail: the left bank of the Lower Volga (Peschany anabranch, Kigach anabranch, as well as the “Novaya Roshcha” protected area). In the Republic of Ingushetia the team collected samples of cherry plum, Caucasian pear, barberry, viburnum, Lonicera orientalis, sea buckthorn, raspberry, and Malus orientalis, which local residents use in their diet. Also, samples of spicy herbs such as savory, catnip, oregano, thyme, etc. were collected. Hops were sampled in the Tambov and Volgograd provinces, the Republics of Ingushetia, North Ossetia and Adygea, from abandoned household plots in Botanika village in Gulkevichi District (Krasnodar Territory). The exploration in vicinities of Derbent and of the wall of Naryn-Kala fortress in Derbent resulted in collecting a rare specimen of Secale sylvestre Host., which previously used to be a fairly common plant in the North Caucasus, but is very rare now. Vegetable crops were collected along the entire route of the collecting mission. It was not always possible to collect seeds, so a part of the material enriched the herbarium collection. The collected material reflects the use of a vast range of vegetable and spicy plant species by the local population.Collecting missions help to understand which species are of primary importance for the conservation of natural processes, biodiversity and the maintenance of local ecosystems. The genetic diversity of a region is a key object of research for geneticists and plant breeders. Landraces of vegetable, cereal and other crops may have unique properties, such as adaptation to local climate conditions or disease resistance. Work on the mobilization and conservation of the plant genetic diversity is the basis for modern breeding and genetic research.

DEVELOPMENT OF THE OPTIMUM TECHNOLOGY FOR THE TRANSPORTATION OF GRAIN LOADS TAKING INTO ACCOUNT THE EXISTING TRENDS OF THE INDUSTRY

An algorithm and management procedure for the distribution of grain cargoes at port stations have been developed. A list of necessary conditions has been created under which the introduction of graded routes eliminates the problem of direct distribution of cargo by unloading points in the port infrastructure. The proposed technology for the distribution of bulk cargo allows to attract a larger number of participants in the transportation process and create conditions for the attraction of other accompanying cargo.The above problems of railway transport, a significant reduction in the volume of transportation against the background of the existence of a fairly wide network of railways form a trend for route shipments, the vast majority of which, in turn, go to the port.The introduction of staged loads as a compromise in the conditions of the trends acquired by the industry requires the creation of the necessary conditions along the entire route of the cargo.Market conditions as the main driver of the transportation process require a proactive response to variability. It is this approach with the use of transitional phases in the view of port stations that gives the technology such qualities that it becomes especially relevant when the operator of port stations becomes effective.Areas of concentration of freight work, potential infrastructure facilities and port stations, where the formation of groups of wagons for unloading at the ports will take place, were determined by systematizing the collected information and identifying patterns that can be introduced taking into account the existing system of restrictions.Looking directly at the composition of the transport sector for the above-mentioned period, it turns out that the share of cargo processed in Ukrainian ports is 159 million tons. For comparison, in the same period, rail transport was 314.3 million tons, road 222.6 million tons. The above problems of railway transport, a significant reduction in the volume of transportation against the background of the existence of a fairly wide network of railways form a trend for route shipments, the vast majority of which, in turn, go to the port. Analyzing the above in the existing conditions, it is the ports that should set the vector for both the formation of sending and step routes based on the principles of resource conservation.

Global Navigation Satellite System/Inertial Measurement Unit/Camera/HD Map Integrated Localization for Autonomous Vehicles in Challenging Urban Tunnel Scenarios

Lane-level localization is critical for autonomous vehicles (AVs). However, complex urban scenarios, particularly tunnels, pose significant challenges to AVs’ localization systems. In this paper, we propose a fusion localization method that integrates multiple mass-production sensors, including Global Navigation Satellite Systems (GNSSs), Inertial Measurement Units (IMUs), cameras, and high-definition (HD) maps. Firstly, we use a novel electronic horizon module to assess GNSS integrity and concurrently load the HD map data surrounding the AVs. This map data are then transformed into a visual space to match the corresponding lane lines captured by the on-board camera using an improved BiSeNet. Consequently, the matched HD map data are used to correct our localization algorithm, which is driven by an extended Kalman filter that integrates multiple sources of information, encompassing a GNSS, IMU, speedometer, camera, and HD maps. Our system is designed with redundancy to handle challenging city tunnel scenarios. To evaluate the proposed system, real-world experiments were conducted on a 36-kilometer city route that includes nine consecutive tunnels, totaling near 13 km and accounting for 35% of the entire route. The experimental results reveal that 99% of lateral localization errors are less than 0.29 m, and 90% of longitudinal localization errors are less than 3.25 m, ensuring reliable lane-level localization for AVs in challenging urban tunnel scenarios.

Investigating visual navigation using spiking neural network models of the insect mushroom bodies.

Ants are capable of learning long visually guided foraging routes with limited neural resources. The visual scene memory needed for this behaviour is mediated by the mushroom bodies; an insect brain region important for learning and memory. In a visual navigation context, the mushroom bodies are theorised to act as familiarity detectors, guiding ants to views that are similar to those previously learned when first travelling along a foraging route. Evidence from behavioural experiments, computational studies and brain lesions all support this idea. Here we further investigate the role of mushroom bodies in visual navigation with a spiking neural network model learning complex natural scenes. By implementing these networks in GeNN-a library for building GPU accelerated spiking neural networks-we were able to test these models offline on an image database representing navigation through a complex outdoor natural environment, and also online embodied on a robot. The mushroom body model successfully learnt a large series of visual scenes (400 scenes corresponding to a 27 m route) and used these memories to choose accurate heading directions during route recapitulation in both complex environments. Through analysing our model's Kenyon cell (KC) activity, we were able to demonstrate that KC activity is directly related to the respective novelty of input images. Through conducting a parameter search we found that there is a non-linear dependence between optimal KC to visual projection neuron (VPN) connection sparsity and the length of time the model is presented with an image stimulus. The parameter search also showed training the model on lower proportions of a route generally produced better accuracy when testing on the entire route. We embodied the mushroom body model and comparator visual navigation algorithms on a Quanser Q-car robot with all processing running on an Nvidia Jetson TX2. On a 6.5 m route, the mushroom body model had a mean distance to training route (error) of 0.144 ± 0.088 m over 5 trials, which was performance comparable to standard visual-only navigation algorithms. Thus, we have demonstrated that a biologically plausible model of the ant mushroom body can navigate complex environments both in simulation and the real world. Understanding the neural basis of this behaviour will provide insight into how neural circuits are tuned to rapidly learn behaviourally relevant information from complex environments and provide inspiration for creating bio-mimetic computer/robotic systems that can learn rapidly with low energy requirements.

Identifying the influence of land logistic driver cognitive energy impact on supply chain performance through agent-based simulation

Logistic transports link demand generators, distributors, and producers in a supply chain network (SCN). The existence of logistic transports is critical to ensure whole nodes’ economic sustainability. This study explores the impact of human factors on SCN performance through cognitive energy expenditure (CEE) tracking. Agent-based model (ABM) simulation was used to analyze the impact of CEE from truck driver’s electroencephalography (EEG) data to obtain the postsynaptic potential values, which were then transformed to calorific energy. The fleet agents, retailers and distributor models were built based on the East Java, Indonesia, logistic transport route around Karanglo, Gempol, Bungurasih, and Gubeng. The frequency and the peak value of the EEG data, postsynaptic potential, and energy data indicate the same information. All data indicate that more challenging routes have higher frequency and higher peak values. The ABM simulation of the fleet agents shows balanced CEE throughout entire routes due to the precise rest period and eat scheduling. The average delivery success rate was 8 out of 30 or 26.7 % in each simulation time step. Hence, most goods delivery tasks can be completed by fleet agents in a balanced system. As a consequence, the SCN performance is also balanced due to the fluid inventory shift without overstock and stockouts. The rest and eat periods of a fleet agent were scheduled after the CEE has been peaked. The time lag between rest periods and transport operations has to be maintained to overcome fleet agents task buildup. Task buildup has a potential to decay both transport safety and inventory shift rates. Therefore, the upgrade in SCN performance is possible through proper fleet agents scheduling

A novel energy-efficient dynamic programming routing protocol in wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) have characteristics that may influence the routing decisions, such as limited energy resources, storage and computing capacity. Therefore, a routing optimization needs to be done to match the characteristics of the WMSNs. Existing routing protocols only consider energy efficiency regardless of energy threshold, maximum energy, and link cost collectively as the primary basis of routing. In this work, the energy-efficient dynamic programming (EEDP) protocol is proposed to optimize routing decisions that take into account the energy threshold, the maximum energy, and the link cost. Then, the protocol is compared with the dynamic programming (DP), and the ant colony optimization (ACO) protocol. The simulation results show that the EEDP protocol can improve energy efficiency of nodes and network lifetime of the WMSNs. Then, the EEDP protocol is also implemented into a network topology of 10 NodeMCU ESP32 devices. As a result, the EEDP protocol can work very well by selecting routes based on nodes that have the remaining energy above 50 and has the shortest distance. The average delay in sending data for the entire route for the 10 iterations of sending data is 3.99 seconds.

Автоматизація побудови, порівняння та вибору маршрутів та схем доставки в системі мультимодальних перевезень


 The article proposes the application of a methodical approach to choosing the optimal route of multimodal transportation based on a module integrated into the information system of a freight forwarding company. The functions of the module are to build an optimal delivery scheme and meet all customer requirements, both domestic and international multimodal transportation, taking into account the changing circumstances in the conditions of instability caused by the state of war and the need to reorient the usual delivery routes.
 In the conditions of military operations, this method of automated search and comparison of alternative routes allows taking into account changing conditions that develop in real time, while the cargo flow should be accompanied by an information flow that would also be available in real time. The proposed structure of the database, the structures of requests for development routes., developed forms of source documents. The criteria for comparing routes of different dimensions are defined: the difference in the distance of cargo transportation, the costs of changing the existing system of cargo transportation, increasing the level of transportation safety, delivery time, reducing the cost of delivering a batch of goods, the difference in delivery time. A solution to the multi-criteria decision-making problem by normalizing the criteria and the additive optimization method is proposed. The method of determining the best route and supply scheme is implemented in the "decision-making" module, which is integrated into the information system of the transport forwarding company.
 The result of the practical implementation of the proposed method of construction, comparison and selection of routes and delivery schemes in the system of multimodal transportation based on the integrated module in the information system of the transport and forwarding company is the possibility of quick response to changes in external circumstances, warnings of emergency and conflict situations, control of the transportation process along the entire route and , if necessary, making adjustments to the route and delivery scheme, choosing a safe and effective option by the operator of multimodal transportation.

Towards Negative Emissions: Hydrothermal Carbonization of Biomass for Sustainable Carbon Materials.

The contemporary production of carbon materials heavily relies on fossil fuels, contributing significantly to the greenhouse effect. Biomass is a carbon-neutral resource whose organic carbon is formed from atmospheric CO2. Employing biomass as a precursor for synthetic carbon materials can fix atmospheric CO2 into solid materials, achieving negative carbon emissions. Hydrothermal carbonization (HTC) presents an attractive method for converting biomass into carbon materials, by which biomass can be transformed into materials with favorable properties in a distinct hydrothermal environment, and these carbon materials have made extensive progress in many fields. However, the HTC of biomass is a complex and interdisciplinary problem, involving simultaneously the physical properties of the underlying biomass and sub/supercritical water, the chemical mechanisms of hydrothermal synthesis, diverse applications of resulting carbon materials, and the sustainability of the entire technological routes. This review starts with the analysis of biomass composition and distinctive characteristics of the hydrothermal environment. Then, the factors influencing the HTC of biomass, the reaction mechanism, and the properties of resulting carbon materials are discussed in depth, especially the different formation mechanisms of primary and secondary hydrochars. Furthermore, the application and sustainability of biomass-derived carbon materials are summarized, and some insights into future directions are provided.