Long-distance Delivery Research Articles

Lipid Specificity of the Fusion of Bacterial Extracellular Vesicles with the Host Membrane.

Bacterial membrane vesicles (MVs) facilitate the long-distance delivery of virulence factors crucial for pathogenicity. The entry and trafficking mechanisms of virulence factors inside host cells are recently emerging; however, whether bacterial MVs can fuse and modulate the physicochemical properties of the host lipid membrane and membrane lipid parameter for fusion remains unknown. In this study, we reconstituted the interaction of bacterial MVs with host cell lipid membranes and quantitatively showed that bacterial MV interaction increases the fluidity, dipole potential, and compressibility of a biologically relevant multicomponent host membrane upon fusion. The presence of cylindrical lipids, such as phosphatidylcholine, and a moderate acyl chain length of C16 help the MV interaction. While significant binding of bacterial MVs to the raft-like lipid membranes with phase-separated regions of the membrane was observed, however, MVs prefer binding to the liquid-disordered regions of the membrane. Furthermore, the elevated levels of cholesterol tend to hinder the interaction of bacterial MVs, as evident from the favorable excess Gibbs free energy of mixing bacterial MVs with host lipid membranes. The findings provide new insights that might have implications for the regulation of host machinery by bacterial pathogens through manipulation of the host membrane properties.

Route optimization of battery electric vehicles using dynamic charging on electrified roads

The Electric Road System (ERS) is an innovative technology enabling electric vehicles (EVs) to charge while in motion, offering increased EV range and cost-effective battery solutions. This advancement is particularly valuable for logistics companies seeking to enhance their EV adoption. To provide long-distance delivery routes for heavy-duty EVs through ERSs, we present a first-time attempt to solve the Electric Vehicle Travelling Salesman Problem with Dynamic Charging, where the EV can be charged while driving on the electrified road segments. We formulate this problem by considering path choices between consecutive customers and propose a network reduction heuristic (NRH) to solve large-size instances. We test our model and NRH on grid-like synthetic instances and real-world data developed from the UK road network. Our results demonstrate the effectiveness of the NRH and highlight the potential of ERSs in improving logistics activities and decarbonising road transport. Our experiments revealed that although the typical driving range of most EVs falls short of 400 kilometres, with the widespread deployment of ERS, EVs can traverse distances exceeding 2000 kilometres without requiring recharging stops. Our experiments also revealed that establishing infrastructure on approximately 30 % to 40 % of all roadways is adequate to ensure reliable access for EVs.

Survival and Functional Integration of Human Embryonic Stem Cell-Derived Retinal Organoids After Shipping and Transplantation into Retinal Degeneration Rats.

Because derivation of retinal organoids (ROs) and transplantation are frequently split between geographically distant locations, we developed a special shipping device and protocol capable of the organoids' delivery to any location. Human embryonic stem cell (hESC)-derived ROs were differentiated from the hESC line H1 (WA01), shipped overnight to another location, and then transplanted into the subretinal space of blind immunodeficient retinal degeneration (RD) rats. Development of transplants was monitored by spectral-domain optical coherence tomography. Visual function was accessed by optokinetic tests and superior colliculus (SC) electrophysiology. Cryostat sections through transplants were stained with hematoxylin and eosin; or processed for immunohistochemistry to label human donor cells, retinal cell types, and synaptic markers. After transplantation, ROs integrated into the host RD retina, formed functional photoreceptors, and improved vision in rats with advanced RD. The survival and vision improvement are comparable with our previous results of hESC-ROs without a long-distance delivery. Furthermore, for the first time in the stem cell transplantation field, we demonstrated that the response heatmap on the SC showed a similar shape to the location of the transplant in the host retina, which suggested the point-to-point projection of the transplant from the retina to SC. In conclusion, our results showed that using our special device and protocol, the hESC-derived ROs can be shipped over long distance and are capable of survival and visual improvement after transplantation into the RD rats. Our data provide a proof-of-concept for stem cell replacement as a therapy for RD patients.

A concentric tube magnetic continuum robot with multiple stiffness levels and high flexibility for potential endovascular intervention

Micromagnetic continuum robots (MCR), renowned for their simple structure and high flexibility, hold immense potential and scientific significance in the fields of biomedicine and clinical therapeutics. MCRs are exceptionally adept at navigating confined spaces to transport surgical instruments such as biological valves and drugs, which are crucial for minimally invasive surgeries and delivering nanomedicines over long distances. However, traditional MCRs suffer from a single stiffness and limited maneuverability in complex workspaces. To overcome this problem, we propose a novel multi-stiffness and highly flexible concentric tube magnetic continuum robot (CT-MCR). The CT-MCR consists of conduits of varying diameters, magnetic particles, and a bundle of magnetic thin flexible tubes. It offers the flexibility to be disassembled and assembled to build working channels, and it possesses diverse working modes and body stiffness levels to accommodate specific working requirements. Due to the excellent magnetic field performance of supporting N52 neodymium magnets, the CT-MCR has a significant bending angle and superior maneuverability. Experimental results demonstrate that the CT-MCR is capable of navigating and recovering foreign objects within complex branching vessel models in the workspace of a three-dimensional (3D) Helmholtz coil. The CT-MCR's exceptional maneuverability, flexibility, and adaptability, coupled with its low risk and extensive workspace, are expected to find applications in Transcatheter Aortic Valve Implantation (TAVI) and other minimally invasive surgeries, as well as in the long-distance delivery of targeted drugs.

Mesenchymal Stromal Cells Derived from Canine Adipose Tissue: Evaluation of the Effect of Different Shipping Vehicles Used for Clinical Administration.

Mesenchymal Stromal Cells (MSCs)-based therapies are rapidly gaining interest in veterinary medicine. Cellular therapy represents a new challenge for practitioners and requires precise coordination between the cell processing laboratory and the veterinary clinic. Cryopreservation is the best method to provide fast, in-time, and long-distance delivery of cells for therapeutic applications. However, potentially toxic cryoprotectants and xenobiotic products make the direct administration of cells impracticable for patients. Alternatively, the cells may be resuspended in a ready-to-use vehicle and shipped to the veterinary clinic. In this study, two nutrient-poor vehicles (physiologic saline and ringer lactate solutions) and two nutrient-rich vehicles (the releasate derived from autologous Platelet Poor Plasma and Platelet Rich Plasma) were tested on adipose tissue-derived canine MSCs (AD-MSCs). AD-MSCs stored for 2, 4, or 24 h in the different media were compared regarding mortality, metabolic activity, and replicative capacity. Furthermore, antioxidant activity and the pattern of expression of genes related to AD-MSCs function were performed following 24 h of storage. The results showed that all the different vehicles preserve cell vitality and replication following short-term storage. In long-term storage, the vehicle and cell density affect cell vitality, proliferation, and gene expression (CCL-2, CXCR-4, and TSG-6). Nutrient-rich vehicles seem better suited to preserve cell functionalities in this contest.

Helicobacter pylori Outer Membrane Vesicles: Biogenesis, Composition, and Biological Functions.

Helicobacter pylori has been recognized not only as a causative agent of a spectrum of gastroduodenal diseases including chronic gastritis, peptic ulcer, mucosa-associated lymphoid tissue lymphoma, and gastric cancer, but also as the culprit in several extra-gastric diseases. However, the association of H. pylori infection with extra-gastric diseases remains elusive, prompting a reevaluation of the role of H. pylori-derived outer membrane vesicles (OMVs). Like other gram-negative bacteria, H. pylori constitutively sheds biologically active OMVs for long-distance delivery of bacterial virulence factors in a concentrated and protected form, averting the need of direct bacterial contact with distant host cells to induce extra-gastric diseases associated with this gastric pathogen. Additionally, H. pylori-derived OMVs contribute to bacterial survival and chronic gastric pathogenesis. Moreover, the immunogenic activity, non-replicable nature, and anti-bacterial adhesion effect of H. pylori OMVs make them a desirable vaccine candidate against infection. The immunogenic potency and safety concerns of the OMV contents are challenges in the development of H. pylori OMV-based vaccines. In this review, we discuss recent advances regarding H. pylori OMVs, focusing on new insights into their biogenesis mechanisms and biological functions.

An Enhanced Backtracking Search Algorithm for the Flight Planning of a Multi-Drones-Assisted Commercial Parcel Delivery System

Using drones to carry out commercial parcel delivery can significantly promote the transformation and upgrading of the logistics industry thanks to the saving of human labor source, which is becoming a new component of intelligent transportation systems. However, the flight distance of drones is often constrained due to the limited battery capacity. To address this challenge, this paper designs a multi-drones-assisted commercial parcel delivery system, which supports long-distance delivery by a generalized service network (GSN). Each node of the GSN is equipped with charging piles to provide a charging service for drones. Given the limited number of charging piles at each node and the limited battery capacity of a drone, to ensure the efficient operation of the system, the flight planning problem of drones is converted into a large-scale optimization problem by a priority-based encoding mechanism. To solve this problem, an enhanced backtracking search algorithm (EBSA) is reported, which is inspired by the characteristics of the considered flight planning problem and the weak ability of the backtracking search algorithm to escape from a local optimum. The core components of EBSA are the designed comprehensive learning mechanism and local escape operator. Experimental results prove the validity of the improved strategies and the excellent performance of EBSA on the considered flight planning problem.

Drone Stations-Aided Beyond-Battery-Lifetime Flight Planning for Parcel Delivery

This paper considers using drones to conduct the last-mile parcel delivery. To enable the beyond-battery-lifetime flight, drone stations are considered to replace or recharge the battery for drones. We focus on the flight planning problem with the goal of minimizing the total travel time from the depot to a customer, a key indicator of the quality of service. We investigate four typical ways for the drone to get extra energy at drone stations: 1) replacing the battery with a fresh one, 2) recharging the battery to the full capacity, 3) recharging the battery to the optimal level, and 4) recharging the battery to the optimal level accounting for the availability of drone stations (i.e., whether a drone station is occupied by other drones). While the first two scenarios can be formulated following the framework of integer linear programming, the last two scenarios turn into mixed-integer nonlinear programming problems. To address the later problems, we present a framework in which discretized state graphs are constructed first and then the optimal paths are found by graph searching algorithms. We propose a dynamic version of Dijkstra’s algorithm to deal with the unavailability issue of drone stations. The algorithm can quickly find the optimal flight path for a drone, and extensive computer-based experimental results have been presented to demonstrate the effectiveness of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Multi-rotary unmanned aerial vehicles (UAVs), also known as drones, have been regarded as a promising means to reshape future logistics. To save human labour and reduce cost, many giant logistics companies have been dedicated to developing various drones to deliver light and small parcels during the past decade. However, due to the limitation of payload, the battery capacity is constrained, which prevents drones from long-distance flights. Practitioners have tried the drone-vehicle collaboration method, but this still requires human labour to participate. In this paper, we present a framework where drones autonomously conduct long-distance delivery with the assistance of drone stations. It is worth pointing out that such a framework is not to replace the ground delivery method but to serve as an alternative to the ground counterpart for small and light parcels. A particular focus is on the flight planning from the depot to a destination, which includes not only a sequence of drone stations to stop at but also the corresponding rest time to recharge the battery. Several typical scenarios about battery recharging are discussed, and a dynamic version of Dijkstra’s algorithm is presented to deal with the challenging case where drone station resources are limited. The presented approach is able to find out the optimal flight plan quickly.

Characteristics of long-distance mobile mRNAs from shoot to root in grafted plant species

Thousands of long-distance mobile mRNAs were identified from different grafting systems, based on high-throughput sequencing technology. Moreover, the long-distance delivery of RNAs was proved to involve multiple mechanisms. Here, we analyzed the homology, motif, and tRNA-like structure (TLS) of long-distance mobile mRNAs identified by RNA-seq as well as the RNA-binding protein (RBP) in nine grafting combinations including Arabidopsis thaliana, Vitis vinifera, Cucumis sativus, Citrullus lanatus, Nicotiana benthamiana, Malus domestica, Pyrus spp., Glycine max and Phaseolus vulgaris. Although several mRNAs were found to be shared in herbaceous, woody, and related species, the vast majority of long-distance mobile mRNAs were species-specific. Four non-specific movement-related motifs were identified, while the TLS was not necessary for mRNA long distance mobility. In addition, we found that RBPs were conserved among herbaceous and woody plants as well as related species. This paper reports a further in-depth analysis of the endogenous mechanisms by which the species-specific transportable mRNAs were selected by bioinformatics, in order to provide insights for future research on long-distance mobile mRNAs.

Comprehensive emergency management of obstetric and newborn care program implementation at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia, 2021: an evaluation study

BackgroundMaternal healthcare service is the care given for the woman during her gestation, delivery and postpartum period. The Maternal Mortality Ratio (MMR) was remains high and a public health problem in Ethiopia. Sub-Saharan African (SSA) countries account two-thirds of the global total maternal deaths. To curb such high burden related with child births, comprehensive emergency obstetric care is designed as one of the strategies for maternal healthcare services. However, its implementation status was not well investigated. This study aims to evaluate the implementation of comprehensive emergency obstetric and new born care program in terms of Availability, compliance and acceptability dimensions at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia.MethodsA single case study design was employed from 01 to 30 April 2021. A total of 265 mothers who gave birth at University of Gondar Comprehensive Specialized Hospital (UoGCSH) during the data collection period for acceptability, 13 key informant interviews (KIIs), 49 non-participatory observations (25 observations during C/S performance and 24 assisted spontaneous vaginal deliver) and 320 retrospective document review were conducted. Availability, compliance and acceptability dimensions were evaluated using 32 indicators. Binary logistic regression model was fitted to identify factors associated with acceptability of the services. Adjusted Odds Ratio (AOR) with 95% confidence interval (CI) and p-value < 0.05 were also used to identify associated variables with acceptability. The qualitative data were recorded using tape recorder, transcribed in Amharic and translated to English language. Thematic analysis was done to supplement the quantitative findings.ResultsThe overall implementation of comprehensive emergency obstetric and newborn care (CEmONC) was 81.6%. Moreover, acceptability, availability and care provider’s compliance with the guideline accounted 81, 88.9 and 74.8%, respectively. There were stocked-out of some essential drugs, such as methyldopa, nifidipine, gentamycin and vitamin K injection. CEmONC training gaps, inadequate number of autoclaves, shortage of water supply and long-distance delivery ward to laboratory unit were also the barriers for the CEmONC service. Short waiting time of clients (AOR = 2.40; 95%CI: 1.16, 4.90) and maternal educational level (AOR = 5.50, 95%CI: 1.95, 15.60) were positively associated with acceptability of CEmONC services.ConclusionThe implementation status of CEmONC program was good as per our judgment parameter. Compliance of healthcare providers with the guideline was fair and needed improvement. Essential emergency drugs, equipment and supplies were stocked-out. The University of Gondar Comprehensive Specialized Hospital was therefore had better to give great emphasis to expand maternity rooms/ units. The hospital had better to avail the resources and provide continuous capacity building for healthcare providers to enhance the program implementation.

Novel Concentric Magnetic Continuum Robot with Multiple Stiffness Modes for Potential Delivery of Nanomedicine

The utilisation of miniature robots has become essential in the domain of minimally invasive surgery and long-distance delivery of nanomedicine. Among these, the miniature magnetic continuum robot (MCR) stands out because of its simple structure and dexterity, which allow it to penetrate small cavities, transport specialised tools such as a laser, and deliver medications to support surgical treatment. Nevertheless, because of their soft bodies with a single stiffness, conventional MCRs have limited controllability when navigating through intricate cavities. To address this limitation, we propose a novel concentric magnetic continuum robot (C-MCR) comprising a concentric magnetic catheter with a guidewire having varying stiffness. The C-MCR allows substantial curvature bending owing to its difference in stiffness, and its detachable nature allows it to have four working modes to adapt to specific application requirements with improved stiffness controllability. Experiments demonstrate the ability of the C-MCR to navigate complex pathways and deliver nanomedicines over long distances to specific areas via its internal channels using a large homemade eight-coil electromagnetic system. The C-MCR offers promising application prospects for the long-distance delivery of tailored nanomedicines because of its simple operation, reduced risks, and larger attainable workspace.

The Co-development of Offshore Wind and Hydrogen in the UK – A Case Study of Milford Haven South Wales

Green hydrogen produced from renewable energy resources can not only contribute to the decarbonisation of different energy sectors, but also serve as a carrier for long-distance delivery of renewable generation, offering a cost-effective way to exploit the renewables far from electrical grids. To facilitate the co-development of offshore wind and hydrogen, the paper develops a modelling framework to dispatch power and hydrogen flows across dedicated offshore wind hydrogen production systems to meet onshore hydrogen demands while keeping similar state of charge levels between multiple systems. Then the hydrogen supply to shore and the system investments and ongoing costs are discounted to their present values to calculate the levelised cost of hydrogen, which is minimised by the particle swarm optimsiation algorithm to suggest the best capacities of hydrogen system components including converters, desalination devices, electrolysers, compressors and storage assets. The proposed modelling framework is tested based on a case study at Milford Haven South Wales which is evaluated to have massive offshore wind resources in the Celtic Sea and comparable demands for hydrogen by 2040. The optimisation results are presented based on the techno-economic input parameters projected for 2030 and 2050 scenarios and discussed alongside the influences of technology advances on the system optimisation and resulting metrics including the levelised costs of hydrogen, net present values and potential levels of green hydrogen supply to Milford Haven.

Experimental and Numerical Studies on Bending and Failure Behaviour of Inflated Composite Fabric Membranes for Marine Applications

Owing to their excellent physical characteristics of lightweightiness, compactness and rapid deployment, the inflated membrane structures satisfy the demands of maritime salvage and military transportation for long-distance delivery and rapid response. Exploring the failure behaviour of inflated membrane structures can greatly contribute to their widespread applications in ocean engineering. In this research, the main objective is to comprehensively investigate the bending and failure behaviour of inflated membrane structures. Thus, the Surface-Based Fluid Cavity method is employed to set up the finite element model (FEM) which is compared to the experimental results to verify its reliability. In parallel, the effects of internal pressure and wrinkles are discussed. An empirical expression of the ultimate bending loading was fitted by face-centred composite designs of the Response Surface Methodology. The results of experiments and FEM show that the bearing capacity of the inflated membrane structure is positively correlated with the internal pressure but decreased obviously with the occurrence and propagation of wrinkles. The deformation behaviour and the stress distribution are similar to those of the traditional four-point bending beam, and the local instability induced by wrinkles will cause structural failure. In addition, the numerical model and the proposed expression showed deviations below 5% in relation to the experimental measures. Therefore, the FEM and proposed expression are high of reliability and have important engineering guiding significance for the application of inflated membrane structures in ocean engineering.

Incentive mechanism and path planning for Unmanned Aerial Vehicle (UAV) hitching over traffic networks

Package delivery via the Unmanned Aerial Vehicles (UAVs) is a promising transport mode to provide efficient and green logistic services, especially in urban areas or complicated topography. However, the UAV’s limited energy storage makes it difficult to perform long-distance delivery tasks. In this paper, we propose a novel multimodal logistics framework based on crowdsourcing, in which the UAVs can call on ground vehicles to provide hitch services for energy saving and extending their delivery distance. This multimodal logistics framework is formulated as a two-stage model to jointly consider the incentive mechanism design for crowdsourced ground vehicles and path planning for UAVs. In Stage I, to deal with the motivations for ground vehicles to assist UAV delivery, a dynamic pricing scheme is proposed to best balance the vehicle response time and payments to ground vehicles. It shows that a higher price should be decided if the vehicle response time is long to encourage more vehicles to offer a ride. In Stage II, the task allocation and path planning of the UAVs over the traffic network is studied on the basis of the vehicle response time obtained in Stage I. To address pathfinding with restrictions and the performance degradation of the pathfinding algorithm due to the rising number of conflicts in multi-agent pathfinding, we propose the suboptimal conflict avoidance-based path search (CABPS) algorithm, which has polynomial time complexity. Finally, we validate our results via simulations. It is shown that our approach is able to increase the success rate of UAV package delivery. Moreover, we estimate the delivery time of the UAV in a pessimistic case, it is still twice as fast as the delivery time of the ground vehicle only.

Biodistribution of 89Zr-DFO-labeled avian pathogenic Escherichia coli outer membrane vesicles by PET imaging in chickens

Avian pathogenic Escherichia coli (APEC) is a serious systemic infectious disease in poultry infections, causing severe economic losses to the poultry industry. Previous studies have shown that secretion of virulence proteins was required for the pathogenicity of APEC through the secretion system. Outer membrane vesicles (OMVs) are a generalized secretion system of Gram-negative bacteria that play a key role in the long-distance delivery of virulence factors, but whether they are associated with the pathogenic mechanism of APEC has not been determined. In this study, OMVs were purified and characterized from AE17 (O2 serotype) by ultracentrifugation and density gradient centrifugation and their protein cargo was identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, 89Zr was labeled after chelating AE17 OMVs by DFO and positron emission tomography PET imaging was used to track 89Zr-DFO-OMVs in chickens and to pathologically analyze the distribution sites. This study showed that AE17 OMVs were membrane vesicles ranging in size from 20 to 200 nm and proteomic analysis revealed the presence of virulence proteins, including adhesion proteins OmpA, OmpC, OmpF, OmpX, FimH, FimC and FigE, and serum resistance proteins OmpT and MliC and immune response regulator proteins (FliC). In addition, in vivo PET imaging to track the biodistribution of AE17 OMVs showed that AE17 OMVs were taken up by the lung region and the gastrointestinal and renal regions but were not detected in other areas. Pathological analysis of the tissue sites where AE17 OMVs were ingested showed inflammatory responses and damage. These findings suggested that AE17 OMVs not only contained a group of virulence proteins associated with AE17 infection but can also deliver these virulence proteins over long distances and caused tissue inflammatory damage. Our study revealed a previously unidentified causative microbial signal in the pathogenesis of APEC that could aid in the development of vaccines and antibiotics effective against APEC.

In Situ Produced Nanoparticles at the Oil-Water Interface for Conformance Control and Enhanced Oil Recovery.

Nanoparticle-assisted enhanced oil recovery (Nano-EOR) has attracted intensive interest in the laboratory as a promising oil recovery technology. However, the nanoparticles' stability and long-distance delivery of nanoparticles (NPs) in large-scale reservoirs are two main challenges. In this work, we developed a novel concept of in situ synthesizing NPs at the oil-water interface inside the reservoir for EOR instead of injecting presynthesized NPs from outside. The pore-scale flooding experiments show that EOR efficiencies for tertiary flooding were 6.3% without reaction (Case 3), 14.6% for slow reaction (Case 1), and 25.4% for relatively quick reaction (Case 4). Examination of the EOR mechanism shows that in situ produced SiO2 NPs in microchannels could alter the substrate wettability toward neutral wetting. Moreover, the produced NPs tended to assemble on the immiscible oil-water interface, forming a barrier toward interface deformation. As the reaction continued, excessive surface-modified NPs could also diffuse into aqueous brine and accumulate as a soft gel in the flowing path swept by brine. Collectively, these processes induced a "shut-off" effect and diverted displacing fluids to unswept areas, which consequently increased the sweep efficiency and improved the oil recovery efficiency. Auxiliary bulk-scale experiments also showed that the reaction-induced nanoparticle synthesis and assembly at an immiscible interface reduced the interfacial tension and generated an elastic oil-water interface.

Dynamic thermal modeling of the refrigerated liquified CO2 tanker in carbon capture, utilization, and storage chain: A truck transport case study

Proper estimation of the energy consumption of tanker-based methods for the storage and transport of liquified CO2 gas is a major concern in the techno-economic analysis and selection between the existing technologies within the carbon capture, utilization, and storage (CCUS) chain. In this study, the dynamic thermal modeling of a liquified CO2 insulated-body tanker truck equipped with a refrigeration unit is presented to simulate the transient thermal performance of the tanker truck during a typical long-distance delivery mission. The main purpose of this research is to provide a more precise estimation of the heat leak quantity to the tanker, pressure build-up, and the refrigeration cooling demand and energy consumption. A two-way coupled set of unsteady-state differential equations are established on the participating elements included in the non-equilibrium thermal system of the tanker and refrigeration unit. The dynamic variations of ambient condition parameters, including the ambient temperature, solar radiation levels, degree of cloudiness, and wind velocity are incorporated into the model based on the annual average meteorological data in three modes of ambient conditions: the warmest week, a moderate week, and the coldest week of the year. The computational fluid dynamic (CFD) modeling of the liquid and gas phase CO2 inside the vessel is also implemented in order to determine the required heat transfer coefficients used in the model. According to the modeling results, the average vessel inward heat leak changes from 11.08 W/m2 in the warmest week of the year to 8.18 W/m2 and 5.11 W/m2 for a moderate and the coldest week, respectively, with 26.17 % and 53.88 % decrease. On the other hand, the refrigeration coefficient of performance (COP) is improved from 1.10 in the warmest week to 1.23 and 1.36 in a moderate and the coldest week, respectively, by 11.82 % and 23.63 % increase. As a measure of energy consumption of the refrigerated CO2 tanker truck at different ambient conditions, the average compressor power consumption changes from 56 W/m3CO2 in the warmest week of the year to 41 W/m3CO2 and 28 W/m3CO2 in a moderate and the coldest week, respectively, with 26.78 % and 50.00 % decrease. The novel modeling approach proposed in this study could also be used to study various design aspects of the refrigerated CO2 transport and storage tankers.

Meal delivery routing optimization with order allocation strategy based on transfer stations for instant logistics services

The rapid development of instant logistics services has brought not only convenience to people's life but also a great challenge to traffic management. Due to the limited delivery range of instant delivery systems, customers are usually recommended the meals nearby or pay much higher delivery fees for long-distance delivery. This study proposes a novel order splitting strategy based on transfer stations for long-distance meal orders to satisfy the diverse customer demands. The meal delivery routing problem is addressed with an order allocation strategy based on transfer stations through developing a three-stage modelling framework consisting of order combination, splitting and delivery routing for the online-to-offline instant logistics services. Normal meal orders are combined by the DBSCAN algorithm, and the cross-regional long-distance orders are split by transfer stations. Based on order combination and splitting, a mixed integer programming model is constructed for the meal delivery routing problem and solved by the adaptive large neighbourhood search algorithm. The proposed algorithm converges quickly for the tested instances constructed based on real platform data. The proposed order allocation strategy can expand the delivery scopes of couriers effectively, stimulate more potential orders and guarantee the timeliness of meal delivery.

Research on Mathematical Model of Balancing the Interests of All Parties in Food Delivery

In this paper, we study the delivery order pattern of take-out riders in Chinese society, adopt a time window function to give a reward and punishment measure for the complete quality of riders under various factors, and adopt hierarchical analysis to obtain and quantify the degree of influence of different factors on delivery, and get the commission scheme design so that the riders can get the maximum commission. Then, from the perspective of game theory, we establish a two-stage game model under the non-cooperative game, with the first stage of the game being the takeaway demand realizer and the second stage of the game being the takeaway demander and the contacting platform, and finally select a win-win solution with a balanced game. Finally, the pricing model proposed in the previous paper is optimized iteratively, considering the addition of long-distance as well as cross-regional distance quantification factors, and considering the case of dedicated personnel working exclusively. This paper proposes an equilibrium state for the four ends of the platform, merchants, consumers, and riders, and proposes a cross-regional and long-distance delivery scheme with certain feasibility, giving the platform and riders the possibility to expand the sales area and delivery area.

Improved analytical bounds on delivery times of long-distance entanglement

The ability to distribute high-quality entanglement between remote parties is a necessary primitive for many quantum communication applications. A large range of schemes for realizing the long-distance delivery of remote entanglement has been proposed, both for bipartite and multipartite entanglement. For assessing the viability of these schemes, knowledge of the time at which entanglement is delivered is crucial. Specifically, if the communication task requires multiple remote-entangled quantum states and these states are generated at different times by the scheme, the earlier states will need to wait and thus their quality will decrease while being stored in an (imperfect) memory. For the remote-entanglement delivery schemes which are closest to experimental reach, this time assessment is challenging, as they consist of nondeterministic components such as probabilistic entanglement swaps. For many such protocols even the average time at which entanglement can be distributed is not known exactly, in particular when they consist of feedback loops and forced restarts. In this work, we provide improved analytical bounds on the average and on the quantiles of the completion time of entanglement distribution protocols in the case that all network components have success probabilities lower bounded by a constant. A canonical example of such a protocol is a nested quantum repeater scheme which consists of heralded entanglement generation and entanglement swaps. For this scheme specifically, our results imply that a common approximation to the mean entanglement distribution time, the 3-over-2 formula, is in essence an upper bound to the real time. Our results rely on a novel connection with reliability theory.