Routing Options Research Articles

Radial Forearm Free Flap with Parapharyngeal Pedicle Corridor for Reconstruction of Anterior Skull Base Defects

The radial forearm free flap (RFFF) is an indispensable tool for the reconstruction of a range of defects, including those of the skull base. Several options for routing of the RFFF pedicle have been described, and the parapharyngeal corridor (PC) has been proposed as an option and employed for a nasopharyngeal defect. However, there are no reports of its use for the reconstruction of anterior skull base defects. The objective of this study is to describe the technique for free tissue reconstruction of anterior skull base defects using the RFFF and routing of the pedicle via the PC. Relevant neurovascular landmarks and critical surgical steps for reconstruction of anterior skull base defects with an RFFF and routing of the pedicle via the PC are reported using an illustrative clinical case and cadaveric dissections. We present a case of a 70-year-old man who underwent endoscopic transcribriform resection of cT4N0 sinonasal squamous cell carcinoma and was left with a large anterior skull base defect that persisted despite several repair attempts. An RFFF was utilized to repair the defect. This report is the first description of the clinical use of the PC for free tissue repair of an anterior skull base defect. The PC is an option for routing the pedicle during the reconstruction of anterior skull base defects. When the corridor is prepared as described in this case, a direct route exists from the anterior skull base to cervical vessels, simultaneously maximizing the reach of the pedicle and minimizing the risk of kinking.

Reconstruction of Co/Ni metal-organic-framework based electrode materials with excellent conductivity and integral stability via extended hydrothermal treatment toward improved performance of supercapacitors

Recently, although metal-organic-framework (MOF) had been widely used in the field of energy storage, their poor electronic conductivity and unstable structure limited their further application. In order to tackle these issues above, it is necessary to enhance the conductivity and stability of the MOF based electrode materials. Herein, reconstruction of bimetal Co/Ni metal-organic-framework (Co/Ni-MOF) based electrode materials with excellent conductivity and integral stability were achieved via a facile single-step hydrothermal process. In details, it was found that the part of Co/Ni-MOF can be transformed into graphite carbon and crystallized NiCo2O4 under the extended hydrothermal treatment. Through this strategy, the impedance of the electrode material had been significantly improved. The reconstructed electrode material was proved to exhibit an ultra-high specific capacity of 680.6 C g−1 at 1 A g−1 and great cycle stability. Moreover, the corresponding assembled asymmetric supercapacitor also demonstrated an outstanding performance. The maximum energy density of 79.6 Wh kg−1 could be achieved at a power density of 0.8 kW kg−1, and the 88.6 % initial capacity could be remained even after 5000 cycles. All in all, this work provided an optional route to modify the poor conductivity and tune the inferior integral stability of MOF-based electrode materials toward improved performance of supercapacitors.

Transport and economic justification of road routing options (on the example of Arkhangelsk - Naryan-Mar automobile route)

The Arctic region has received increasing attention in recent years. One of the topical areas of transport system development in the Russian Federation is the transit potential of the Arctic region as well as transport connections with the Barents region countries. The purpose of the research is to make a transport and economic research of variants of automobile transport network development in the Barents region - the transport route Arkhangelsk - Naryan-Mar. The research objectives are: to analyse regional transport network of Nenets Autonomous District; to develop versions of Arkhangelsk - Naryan-Mar transport routes; to estimate transport and economic characteristics and choose a variant of motor transport route. Two variants of the Arkhangelsk - Naryan-Mar road route have been considered in the course of this work. The first one is 887 kilometres long and goes along the sparsely populated territory, through the village Volokovaya. The second route is 940 km long. It is situated in the north through 10 settlements, including the town of Mezen, the administrative centre of Mezen municipal district. A more feasible route is the second option, which runs along the shores of the Mezen Bay of the White Sea and the Chesh Bay of the Pechora Sea. In spite of the fact that this route is 77 km longer than Route 1, it will be a transport artery, passing through 10 settlements, among which is the town of Mezen, the administrative centre of Mezen municipal district.

Indonesian Regional Water Utility Company Optimum Pipe Route Planning Using Analytical Hierarchy Process and Cost Path Analysis (Case Study: Zone 1 to Zone 3 PDAM Service)

Zone 3 Indonesian Regional Water Utility Company (PDAM) Surya Sembada Surabaya which including Semampir District, Kenjeran District, Simokerto District, and surroundings has lowest water pressure and water discharge compared to the other zones. This problem makes some areas in zone 3 lack of water. To minimize this problem, the company makes a plan to provide more water in zone 3 by installing a new distribution pipe. This paper purposes to make the most optimum pipe route using Analytical Hierarchy Process Method and Cost Path Analysis based on some criterion, which are slope, aspect, land-use, road network, river network, flood-prone area and soil types. Analytical Hierarchy Process (AHP) is used to get the weight of criterion and sub-criterion based on expert opinions. While cost path analysis is processed to load the most optimum pipe route based on the weight of all criterion. Based on AHP processing, the most important criterion is road network which has 44% influence. It is followed by land-use which has 22% influence. The other criterion have 4% - 10% influence in determining the most optimum pipe route. The processing of cost path analysis uses some end-points to get some pipe route options. The result shows some parts of pipe routes intersect with the settlement and do not parallel with road network. Because of those reasons, the pipe routes require to be modified.

Economic assessment of the cost of reducing the delivery time for cargo owners when sending goods through the international transport corridor “North-South”

Purpose: substantiation of the author's methodology for assessing the economic effect of saving time in supply chains, analysis based on the proposed methodology for saving time of commodity producers when sending goods from St. Petersburg (North-Western Federal District of Russia) to India, the cargo is sent along the eastern branch of the international transport corridor “North-South” to compared with the option of delivery via the “deep sea” technology via the Mediterranean Sea and the Suez Canal. Methods: economic modeling, statistical parameterization, analysis and optimization of supply chains. As a result of the conducted research: the parameters of cargo shipments from the North-Western Economic District, the region of the St. Petersburg agglomeration to India for five different delivery options are systematized; the author's methodology for assessing the economic effect of saving time is disclosed, on the basis of which the effects of saving time for goods sent to India from St. Petersburg are determined, when switching from the “deep sea” supply option to the “North-South” multimodal eastern route option. Conclusion: as a result of the study, high-yield cargoes were identified, in particular, pulp, paper, metal structures, the dispatch of which from Russia to India via the international transport corridor is economically attractive, since the effect of saving time overrides the higher cost of delivery.

Route Planning for Autonomous Mobile Robots Using a Reinforcement Learning Algorithm

This research suggests a new robotic system technique that works specifically in settings such as hospitals or emergency situations when prompt action and preserving human life are crucial. Our framework largely focuses on the precise and prompt delivery of medical supplies or medication inside a defined area while avoiding robot collisions or other obstacles. The suggested route planning algorithm (RPA) based on reinforcement learning makes medical services effective by gathering and sending data between robots and human healthcare professionals. In contrast, humans are kept out of the patients’ field. Three key modules make up the RPA: (i) the Robot Finding Module (RFM), (ii) Robot Charging Module (RCM), and (iii) Route Selection Module (RSM). Using such autonomous systems as RPA in places where there is a need for human gathering is essential, particularly in the medical field, which could reduce the risk of spreading viruses, which could save thousands of lives. The simulation results using the proposed framework show the flexible and efficient movement of the robots compared to conventional methods under various environments. The RSM is contrasted with the leading cutting-edge topology routing options. The RSM’s primary benefit is the much-reduced calculations and updating of routing tables. In contrast to earlier algorithms, the RSM produces a lower AQD. The RSM is hence an appropriate algorithm for real-time systems.

Optimization Modeling of Urban Freight Transportation Network by Using a Metaheuristic Approach, Genetic Local Search Procedure

Creating a transportation network that reduces the cost of urban freight is highly challenging. Freight route is determined by the amount of congestion generated by the vehicle type. Furthermore, it must compete with other users to locate the optimal path for their traffic on the city's restricted road network infrastructure system. Freight network routing begins with identifying and determining the optimum route. The freight network is optimized by introducing a heavy traffic restriction mechanism in metropolitan areas, and an attempt is made to propose a set of routes as a set of freight traffic modes. The primary goal of freight routing in this research is making a freight network model optimization to find a set of freight routing by optimizing (efficiency) trip prices due to limited road infrastructure and the difficulties of constructing road infrastructure in metropolitan areas. Therefore, selecting a group of routes as the journey of the commodities is a realistic alternative to minimizing costs. The problem of route selection is one of combinatorial optimization. The challenge is to narrow the pool of action options to a set of recommended actions. Due to vehicle characteristics and traffic flow, route selection carefully considers vehicle behavior. A two-level mathematical model that was created by formulating route options served as the framework for the research. The combination of chosen routes is maximized using a genetic algorithm such as a Genetic Local Search. The model is examined via its application to a fictitious network. The result converges to the target value of 246,311.9 IDR. It shows that the model satisfies the convergence condition of producing in 0.76 seconds. As a result, a model with a genetic local search technique that can search more effectively in the city's freight network's ideal path is created. The GLS combinatorial optimization model shows us it could find the best set of urban freight networks with the best performance. This is consistent with Yamada et al. GLS methods perform well in solving combinatorial problems.

Multiclass dynamic emergency traffic collaborative optimization considering multiple solutions with stage-based algorithm

Multiclass dynamic emergency traffic consisting of evacuation and rescue vehicles is a common situation on the road network in the response of the sudden local disaster, e.g., fire disaster, hazardous chemical disaster, etc. However, there are several options for the optimal rescue traffic routes sharing the same optimum objective value during the evacuation, and it is not clear how different optimal rescue traffic routes will affect evacuation traffic. Our motivation is based on the possibility for the dynamic rescue traffic optimum to have multiple solutions on the road network shared by multiple vehicle classes, which differ in when and which roads are occupied by how many rescue vehicles during the evacuation. To this end, we formulate multiclass dynamic emergency traffic collaborative optimization problem considering multiple solutions and traffic priority as the MMILP-RRO formulation, which consists of multi-objective mixed integer linear programming formulation (MMILP) and risk-based rescue traffic optimization formulation (RRO), and is solved by a stage-based optimization algorithm. The numerical results are conducted on the Beijing’s Zhongguancun​ road network to provide some insights into the effects of multiple optimal rescue traffic routes on evacuation traffic for multiclass dynamic emergency traffic network flow collaborative management.

Calico

We explore Calico, a miniature relocatable wearable system with fast and precise locomotion for on-body interaction, actuation and sensing. Calico consists of a two-wheel robot and an on-cloth track mechanism or "railway," on which the robot travels. The robot is self-contained, small in size, and has additional sensor expansion options. The track system allows the robot to move along the user's body and reach any predetermined location. It also includes rotational switches to enable complex routing options when diverging tracks are presented. We report the design and implementation of Calico with a series of technical evaluations for system performance. We then present a few application scenarios, and user studies to understand the potential of Calico as a dance trainer and also explore the qualitative perception of our scenarios to inform future research in this space.

Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse

The routing strategy for order picking is an important factor in the efficiency of warehouse picking, and improvements to the warehouse layout provide more routing options for picking. The number of storage locations to be visited during the picking operation also has an impact on the selection of routing strategies. In order to achieve an effective improvement in the efficiency of picking operations in warehouse distribution centers, this paper focuses on the leaf warehouse layout based on the previous single-command operation strategy and extends it to study the multi-command operation strategy, in which three heuristic routing strategies, the S-shape, the return, and the composite, are introduced to solve the walking distance problem of picking operations, with the study of the selection of the routing strategy for different numbers of storage locations to be visited. Based on the distance equation between any two storage locations to be visited in the leaf layout warehouse, travel distance models corresponding to the three routing strategies in the picking operation are constructed, and the cuckoo search algorithm is introduced to solve and calculate the travel distance of the composite strategies for the experiments. In addition, the computational experiments of the three path strategies are carried out according to the different numbers of storage locations to be visited in the picking operation. By analyzing the numerical results, we find that the composite strategy has the best overall results among the three routing strategies, with the average values of optimization rates exceeding 30% (the S-shape) and 40% (the return), respectively. At the same time, the return strategy outperforms the S-shape strategy when the number of locations to be visited is less than seven. As the number of locations to be visited increases, the S-shape strategy gradually outperforms the return strategy. From a managerial and practical perspective, compared to the single-command operation strategy that is the focus of the current research, the multi-command operation strategy we studied is more relevant to the actual situation of order merging picking in warehouses and can effectively improve the efficiency of picking operations, the competitiveness of enterprises, and customer satisfaction of e-commerce enterprises.

Organic phosphorescent nanoscintillator for low-dose X-ray-induced photodynamic therapy

X-ray-induced photodynamic therapy utilizes penetrating X-rays to activate reactive oxygen species in deep tissues for cancer treatment, which combines the advantages of photodynamic therapy and radiotherapy. Conventional therapy usually requires heavy-metal-containing inorganic scintillators and organic photosensitizers to generate singlet oxygen. Here, we report a more convenient strategy for X-ray-induced photodynamic therapy based on a class of organic phosphorescence nanoscintillators, that act in a dual capacity as scintillators and photosensitizers. The resulting low dose of 0.4 Gy and negligible adverse effects demonstrate the great potential for the treatment of deep tumours. These findings provide an optional route that leverages the optical properties of purely organic scintillators for deep-tissue photodynamic therapy. Furthermore, these organic nanoscintillators offer an opportunity to expand applications in the fields of biomaterials and nanobiotechnology.

Contextualization of the Concept of Fraud Victimization for the Crime of Fraud in Trade Activities Indonesia – China (Victimization Study from the Perspective of Indonesian Exporters)

This study aims to examine fraud cases in Indonesia-China trade relations from the point of view of the Indonesian exporters as victims. Empirically and theoretically, the research focuses on gaps in trade relations that trigger the victimization of Indonesian exporters and seeks to uncover economic, political, legal, and cultural asymmetries in accordance with the stages and typology of fraud victimization initiated by Michael Levi (2009). This study contextualizes fraud victimization on the phenomenon of criminogenic asymmetries in Indonesia-China trade relations. The study uses a qualitative approach with an explanatory method, while the data analysis uses a triangulation technique. The results of the study reveal several essential things. First, the victimization cases of Indonesian exporters occur because of the existence of non-legal route options in trade with China that puts the exporters in the category of diffuse victimization. This option is available because it is a rational choice of cost-effective, duty-free, and with no licensing. It is even more dramatic when the government and law enforcement commit victim blaming, then see cases of default as negligence, not fraud. Second, there is a lack of coordination between international trade stakeholders in Indonesia, creating difficulties in assisting entrepreneurs’ processes, especially if the exporters become victims of fraud. Third, the role of groups of perpetrators of organized fraud exists by using the guise of business in Indonesia-China trade relations. Fourth, the fraud victimization experienced by Indonesian exporters is inseparable from the existence of asymmetric criminogenic factors, namely the legal system, technology, knowledge, and culture between the two countries. Fifth, there are empirical and theoretical differences and gaps related to the contextualization of Levi's concept of fraud victimization when placed within the framework of criminogenic asymmetries in the Indonesia-China trade case. This gap is due to the occurence of three export routes that significantly affect the concept of victimization typology.

EXPLORING JITTERING AND ROUTING OPTIONS FOR CONVERTING ORIGIN-DESTINATION DATA INTO ROUTE NETWORKS: TOWARDS ACCURATE ESTIMATES OF MOVEMENT AT THE STREET LEVEL

Abstract. Origin-Destination (OD) datasets provide vital information on how people travel between areas in many cities, regions and countries worldwide. OD datasets are usually represented geographically with straight lines or routes between zone centroids. For active travel, this geographic representation has substantial limitations, especially when zone origins and centroids are large: only using a single centroid origin/destination for each large zone results in sparse route networks covering only a small fraction of likely walking and cycling routes. This paper implements and explores the use of jittering and different routing options to overcome this limitation, thereby adding value to aggregate OD data to support investment in sustainable transport infrastructure. The route network results — generated from on an open dataset representing cycling trips in Lisbon, Portugal — were compared with a ground-truth dataset from 67 count locations distributed throughout the city. This approach enabled exploration of which jittering parameters and routing options lead to the most accurate route network results approximating the real geographic distribution of cycling trips in the study area. We found that jittering and disaggregating OD data, combined with routing using low level of traffic stress (quieter) preferences resulted in the most accurate route networks. We conclude that a combined approach involving 1) jittering with intermediate levels of disaggregation and 2) careful selection of routing options can lead to much more realistic route networks than using established OD processing techniques. The methods can be deployed to support evidence-based investment in strategic cycling and other sustainable transport networks in cities worldwide.

Enhancing the interaction of railway timetabling and line planning with infrastructure awareness

Planning a railway system is done in multiple stages that are typically intractable to optimize in an integrated manner. This work develops a novel iterative approach to tackle two of these stages jointly: line planning and timetabling. Compared to existing approaches that iteratively ban a whole conflicting line plan when the timetable is found infeasible, our method can accurately identify the smallest set of incompatible services. Besides, by efficiently exploiting the available railway infrastructure, our method accounts for all the possible routing options of trains, a feature commonly neglected to reduce complexity but that helps gaining timetable feasibility. Using real data from a railway company in Switzerland, we find that our approach is (i) practical for solving real-life instances, (ii) an order of magnitude faster than existing benchmarks, and (iii) able to solve more instances. Our insights shed light on the necessity of considering infrastructure and banning conflicts rather than line plans in the joint line planning and timetabling problem.

Route planning decisions: evaluating reliance on spatial heuristics under risk

ABSTRACT Spatial heuristics play a vital role in the decision-making process of route planning, but the crucial component of risk is often not considered. Whether in transportation logistics or military asset path planning, routes are evaluated in part based on the potential adverse outcomes of each route option. Drivers or dispatchers must consider the risks of inclement weather, adversarial threats, and unsafe roads, among other negative consequences that could negatively impact safe arrival to a destination. In a series of three studies, we replicated well-established route planning heuristics: preferences for shorter paths, initially straight paths, and avoiding regional crossings. We further demonstrated that when probabilistic risk outcomes are associated with paths, known risk probabilities had a dominating effect on decision-making.

Traffic ahead: Navigating the road to carbon neutrality

The journey to carbon neutrality will require trillions of dollars of capital investment over many years. Analytical models based on foresight offer guidance, but an overreliance on them can lead to a myopic focus on a single pathway. Some argue that the solution is to develop higher-resolution models, fed with increasingly granular data. Here, we note that real-time feedback is an important and underappreciated complement to this approach.We discuss how nations and corporations are currently embarking on the energy transition with the equivalent of a high-level map. The ambition is clear, but there is a lack of confidence in the best route. Routing options and conditions are changing rapidly. We outline the features of a navigation app for the energy transition that offers real-time, actionable guidance for the energy transition would be hugely beneficial. The essential function of such an app would be to collect, secure, process, and present data in a way that can support decisions by relevant actors. Such a capability would require three essential elements: route topology awareness with high-resolution details of the benefits and costs of different decarbonization options; data platforms that provide insight into the real-time situation; and trade-off tools that readily convey accurate, up-to-date, and easily-interpretable estimates of switching costs. These elements exist at varying levels of maturity, and improvement and integration is needed to deliver the utility and convenience of a road travel app.This Perspective draws on our collective experience mapping paths to carbon neutrality for the Princeton Net-Zero America study and one of China's largest energy companies (China Energy) to develop the idea of navigation apps for the energy transition. Starting with a resolved accounting of CO2 emissions, we illustrate the importance of accounting for differing motivations and leverage among actors. We discuss the essential features of a navigation app and show how progress in these areas can help address bottlenecks in large-scale clean energy deployment. We conclude with a call for increased collaboration with tech companies to accelerate development of these capabilities.

Developing and analyzing eco-driving strategies for on-road emission reduction in urban transport systems - A VR-enabled digital-twin approach

A vast number of pollutants are generated from on-road commuting vehicles, and there is an increasing need to explore vehicle emission monitoring and mitigation strategies. Traditionally, vehicle emissions can be monitored and measured directly from on-vehicle devices such as a sensor at the tailpipe, or based on expensive data collection tools such as roadside units; while another mainstream research estimates vehicle emissions by relying on the connection to the vehicle motions, which can approximately calculate vehicle emissions under certain traffic conditions. This paper proposes a virtual reality (VR) enabled digital twin platform for on-road emission monitoring, and it develops and evaluates eco-driving strategies within a specific area. The proposed approach, integrating a VR-based digital environment, a micro-simulation model for background traffic, and a Motor Vehicle Emission Simulator for emission estimation, offers an alternative to collect and examine vehicle emissions such as NOx under various traffic conditions. A case study on a central business area in Melbourne is conducted and eco-driving strategies are tested in two scenarios. The first scenario concerns the impact of hybrid electric vehicles and connected autonomous vehicles, which points to the long-term benefit of having controllable and cleaner modes of transportation as a strategy. Results showed that manipulating the penetration rate of emission-friendly engines or motions could reduce vehicle emissions effectively. The second scenario concerns the real-time eco-routing based on emission-optimum, which points to the short-term benefit of emission control strategies. Human-in-the-loop experiments were conducted to test drivers’ responses toward routing options. Results showed that over 90% of participants would follow the eco-routing recommendations completely. The presented study offers an alternative to data-generating, analyzing, and managing approaches for on-road emissions in urban transportation systems.

Математическая модель принятия решений на нечетком множестве данных в сфере логистики

Insufficiently effective management of transportation process is associated with the cases of irregularity and inconsistency of the work of transport various modes among themselves, insignificant development of processing capacities for cargo transshipment between transport modes as well as of insufficient number of terminals serving to «smooth» work inconsistency in time in transport flows. This article describes mathematical model for choosing a rational variant of cargo delivery from the position of a transportation client. The main advantage of the described mathematical model is the minimization of production and technological costs on the platform of fuzzy set theory with an “eye” on exact sets (topology on the set of parameters of real numbers R1). Sufficiently smooth function f ( x), x ∈ R1, is adopted. For it, the Taylor representation takes place locally at the point x0. Presented in the paper integrated approach allows to evaluate the rationality of routes and the choice of the best among them which takes into account wide range of criteria, limitations of transport parameters and cargo owner requirements. It is worth to note that the rationality of choice is sometimes formed not only from the best result, but also from emerging alternatives and factors affecting this or that choice and process. A client chooses a competitive route option according to the variation of claimed by him demands on logistics projects. The paper also presents existing method analysis on reveal of the rationalization of transport constituent in logistics field.

Implementation of Rate-Compatible QC-LDPC Encoder Based on FPGA

A rate-compatible LDPC encoder based on quasi-cyclic generation matrix is proposed. The encoder partitions and controls access to the ROM address, so it can be compatible with a variety of LDPC codes to generate matrix cyclic shift vectors. By adding routing options in the register cyclic shift circuit, it is compatible with matrix blocks of different sizes. Due to the adjustment of the initial shift count and the truncation of the check bit output, the virtual filling and shortening of the LDPC code is realized, which further expands the code length and code rate of the encoder. An LDPC encoder compatible with 4 code rates is implemented on a Xilinx Virtex5 xc5vfx130t FPGA, Compared with the existing design, this encoder requires only slightly more hardware resources than a single encoder to achieve the same data throughput. Compared with implementing all four different encoders, more than 40% of the hardware resources can be saved.

The Optimization Model of E-Commerce Logistics Distribution Path Based on GIS Technology

The optimization of the e-commerce logistics distribution path has always been an important research object in intelligent control. Based on the geographic information system (GIS) platform, this paper proposes an improved ant colony algorithm for the logistics distribution path optimization model based on the GIS platform. Firstly, ArcGIS software is used to solve the problem of complex networks and realize the selection and output of optional routes. Secondly, the basic ant colony algorithm is improved, and a dynamic path planning method combining global planning information and local planning is proposed. It mainly includes the improvement of the heuristic function and the improvement of the update method of pheromone. Finally, through simulation experiments and case validation experiments, it is concluded that the improved algorithm outperforms the traditional ant colony algorithm. In the case validation part, a local area of Beijing is selected to simulate a natural distribution environment, and the path optimization experiments are validated by building an actual road network model. The results show that the model can plan the optimal path for logistics distribution according to the road congestion. The data analysis shows that the route optimization model proposed in this paper can effectively reduce the distribution cost of enterprises, increase vehicle loading, and increase the profit and industry competitiveness of logistics enterprises.