Commercial Delivery Research Articles

Two-Phase Fuzzy Real-Time Approach for Fuzzy Demand Electric Vehicle Routing Problem with Soft Time Windows

Environmental concerns have called for several measures to be taken within the logistics and transportation fields. Among these measures is the adoption of electric vehicles instead of diesel-operated vehicles for personal and commercial-delivery use. The optimized routing of electric vehicles for the commercial delivery of products is the focus of this paper. We study the effect of several practical challenges that are faced when routing electric vehicles. Electric vehicle routing faces the additional challenge of the potential need for recharging while en route, leading to more travel time, and hence cost. Therefore, in this work, we address the issue of electric vehicle routing problem, allowing for partial recharging while en route. In addition, the practical mandate of the time windows set by customers is also considered, where electric vehicle routing problems with soft time windows are studied. Real-life experience shows that the delivery of customers’ demands might be uncertain. In addition, real-time traffic conditions are usually uncertain due to congestion. Therefore, in this work, uncertainties in customers’ demands and traffic conditions are modeled and solved using fuzzy methods. The problems of fuzzy real-time, fuzzy demand, and electric vehicle routing problems with soft time windows are addressed. A mixed-integer programming mathematical model to represent the problem is developed. A novel two-phase solution approach is proposed to solve the problem. In phase I, the classical genetic algorithm (GA) is utilized to obtain an optimum/near-optimum solution for the fuzzy demand electric vehicle routing problem with soft time windows (FD-EVRPSTW). In phase II, a novel fuzzy real-time-adaptive optimizer (FRTAO) is developed to overcome the challenges of recharging and real-time traffic conditions facing FD-EVRPSTW. The proposed solution approach is tested on several modified benchmark instances, and the results show the significance of recharging and congestion challenges for routing costs. In addition, the results show the efficiency of the proposed two-phase approach in overcoming the challenges and reducing the total costs.

Creation of a complex multivariate integrated model of the oil interfield transport system

Background. In conditions of variability of external and internal factors that directly affect the loading of the existing hydrocarbon transport system, the risks arise associated with the productive capacity of the existing infrastructure and noncompliance with the requirements for the quality of delivered oil. Objective. To create a tool allowing to assess the degree of loading of existing infrastructure facilities and indicators of the commercial quality of oil at commercial delivery sites in the near and long term, the availability of which is essential for risk minimization. Materials and methods. An integrated model in combination with automation tools is an effective tool for making strategic decisions in order to develop the assets of a subsurface user company. Results. By the example of transport infrastructure, the paper describes an approach to using the gathering system model, which jointly with automation algorithms allows solving a number of strategic tasks of oil and gas producers, such as performing multivariate hydraulic calculations and monitoring oil quality in order to verify compliance with the requirements. Conclusions. An integrated model in combination with the developed automation tools is an auxiliary tool for management decision-making. The tool helps to significantly reduce the labor costs for performing calculations and primary processing of the results. The implemented approaches can be used for hydraulic calculations and monitoring of limitations of transportation networks of similar configuration.

ZOom Delivered Intervention Against Cognitive decline (ZODIAC) COVID-19 pandemic adaptations to the Post-Ischaemic Stroke Cardiovascular Exercise Study (PISCES): protocol for a randomised controlled trial of remotely delivered fitness training for brain health

BackgroundStroke increases subsequent dementia risk yet there are no specific post-stroke therapies to protect cognition. Cardiorespiratory exercise is recommended for secondary prevention of stroke and may be neuroprotective. The Post Ischaemic Stroke Cardiovascular Exercise Study (PISCES) aims to reduce post-stroke secondary neurodegeneration and cognitive decline. During the pandemic, we pivoted to a ZOom Delivered Intervention Against Cognitive decline (ZODIAC) protocol, reducing pandemic-amplified barriers to exercise.MethodsWe present pandemic adaptions for a multicentre phase IIb assessor-blinded randomised controlled trial of ischaemic stroke survivors testing the efficacy and feasibility of an 8-week home-based exercise intervention delivered at 2 months post-stroke. We compare cardiorespiratory exercise (intervention arm) versus balance and stretching (active control arm). Participants are assessed with magnetic resonance imaging (MRI), fitness, blood, microbiome, and neuropsychological tests at three study visits: before and after the exercise intervention and at 12 months. Modifications to the original protocol include pre-exercise safety home visits, commercial delivery of exercise equipment to facilitate assessor blinding, and reconsideration of statistical plan to allow pooling of the studies. We have reduced in-person study visits from 27 to 3. Primary outcome remains between-group (intervention versus control) difference in brain volume change; secondary outcome is between-group difference in global cognitive ability to allow remote administration of a validated cognitive scale.DiscussionRemotely delivered exercise interventions reduce participant burden and may reduce barriers to recruitment. A decrease in the number of in-person study visits can be supported by greater information capture via self-reported questionnaires and phone surveys.Trial registrationProspectively ACTRN12616000942459. Registered on July 2016.

Towards Preventing Anastomotic Leakage through the “No-perforation Virtual Staples”

Anastomotic leakage (AL) is a severe postoperative complication after gastrointestinal surgery, potentially leading to morbidity and mortality. The factors contributing to AL include poor blood flow to the suture line, tension, infection, underlying conditions, and surgeon-related factors. However, the stress concentration, which is a localized increase in stress due to discontinuities caused by sutures or staples, has often been overlooked. The working hypothesis is that by removing problematic stresses and simulating mechanical loadings on the anastomosis, improved recommendations for stapler design, surgical technique, and anastomotic construction can be derived to reduce the occurrence of leaks. The objective of this study is to develop and optimize "no-perforation" magnetic staples that can effectively minimize stress and prevent AL. In this study, magnet-metal bar couples coated with a biocompatible adhesive hydrogel were utilized to replace existing surgical staples. By employing magnetic forces, the tissue was deformed into a curved shape, which provided additional security for the new "magnetic staples". This technique aimed to eliminate complications such as high tension and poor blood flow often associated with traditional staples. To ensure safety, a double protection system consisting of the pectin adhesive (previously patented at BWH) and the "lock-in forces" of the magnetic staples was implemented. It was believed that relying solely on adhesion would not effectively prevent leaks. Preliminary data indicated that applying virtual staples for anastomoses was feasible. The primary innovation of this approach is the substantial reduction in stress concentration when the anastomosis is under tension. The conventional surgical teaching concerning bowel anastomoses has centered on the dangers posed by excessive tension and compromised blood supply. In contrast, virtual staples offer the advantage of adjustable shape and force, allowing for optimization of tension and blood supply. The study successfully identified the biomechanical forces and stress concentrations that contribute to anastomotic leaks and developed new "virtual staples" to address this issue. The new "virtual staples" are made of two magnetic compression rings crafted from medical-grade silicone and feature 8 strategically embedded magnets. These rings are engineered with a specific surface curvature to ensure optimal axial alignment and elimination of stress concentrations. Cases for delivery have also been designed and fabricated, which are compatible with standard commercial delivery devices used in surgical settings. This ensures a seamless integration into existing medical procedures and surgical workflows. Initial in-vitro experiments were conducted on sections of the porcine intestine to test the effectiveness of the Virtual Staples. These preliminary tests have shown promising results, including an absence of leakage at the joined or sealed tissue sites. Our research aims to predict the stress concentration sites in tissues and evaluate the effects of applying adhesive virtual staples under new conditions. Through a combination of experiments and simulations, we designed non-perforation staples and optimized the design by considering various factors such as staple size, shape, magnet strength, and stress distribution. Initial in-vitro experiments indicated the effectiveness of the design. With further optimization of the design, along with animal testing and clinical trials, this new technique has the potential to revolutionize surgical procedures. The MA Acorn Innovation Grant 2023. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

A distributed route network planning method with congestion pricing for drone delivery services in cities

Unmanned aerial vehicle (UAV)-based commercial services, exemplified by drone delivery, have captured wide interest in tech companies, entrepreneurs, and policymakers. Structured route-based UAV operations have been implemented for traffic management of UAVs in support of commercial delivery services in cities. Yet, its essence, multi-path planning with constraints is not well solved in the existing literature. Centralized planning might result in inefficiencies and unfairness in the allocation of precious urban airspace to individual routes. This paper describes a novel distributed route planning method to support UAV operations in a high-density urban environment. The method allows each origin–destination (OD) pair to compete against other OD pairs for an optimized route (e.g. shortest distance), coordinated by a system-level evaluation, leading to a network design that maximizes the performance of not only the individual routes but also the entire system. The core concept is the introduction of congestion pricing, a soft constraint to coordinate the allocation of airspace. The method is tested in standard 2D scenarios and compared with other state-of-the-art methods. The results show that (1) the method is able to generate routes with short individual distances as well as occupying the least airspace by the route network; (2) in some complex scenarios, the method is able to find a solution in a short period of time while other state-of-the-art method fails. The method has also been applied to a real urban environment (Mong Kok in Hong Kong) to demonstrate its capability.

Sorry for the Delay: How FAA Regulations in the U.S. are Stifling Innovation and Hindering the Growth of a Promising New Industry Based on Delivery Drones

From the creation of the transistor radio to robots powered by artificial intelligence, the rapid pace of technological advancements in a multitude of industries has ushered in an innumerable amount of economic, environmental, and social benefits that have collectively produced positive effects around the world. However, in addition to benefits, these rapid advancements in technology have created a particular problem affecting many industries in the United States—antiquated regulations that were promulgated for a particular industry become inefficient and impractical due to rapid technological advancements within that industry. The delivery drone industry, a blossoming new sector of air commerce that has grown exponentially in the past decade, has become the latest victim of regulatory stagnation. The Federal Aviation Administration (FAA) currently regulates commercial delivery drone operations in the U.S. by issuing highly restrictive Part 135 certifications that attach a variety of operating limitations to companies’ delivery drones, such as restricting the traveling distance and airspace location. If companies want to conduct any drone deliveries that fall outside of the strict limitations set by Part 135 certifications, which is the only way to expand their operations to an appropriate commercial scale, those companies must receive exemptions and waivers from the FAA. However, the FAA grants these crucial exemptions and waivers on a case-by-case basis with standards and limitations that vary drastically from company to company. As a result, the FAA has created an unpredictable regulatory minefield that has hindered the expansion of delivery drone operations in the U.S., thus deterring innovation within the drone industry as a whole. Rather than accepting regulatory standards that inhibit the growth of an entire industry, the FAA should adopt a streamlined, standardized certification and approval process for delivery drones that efficiently facilitates the advancement of commercial delivery drone operations in the U.S. This Comment examines the various issues plaguing the current regulatory framework for commercial drone delivery services within the U.S. and seeks to provide a possible solution to these obstructionist regulatory standards through the adoption of a streamlined regulatory scheme for commercial delivery drones. To conduct a full analysis on this topic, this Comment first examines the historical development of the FAA’s current regulations governing commercial drone delivery services, addresses how the current case-by-case exemption process established by the current regulatory regime places an illogical hindrance on the growth of a blossoming industry, and highlights other specific problems plaguing the current regulatory process, echoed by the outcries of various drone industry stakeholders. Additionally, as an alternative solution to the current piecemeal regulatory regime, this Comment argues that Congress, and subsequently the FAA, should adopt the Increasing Competitiveness for American Drones Act of 2023 (American Drones Act) that creates a comprehensive, streamlined regulatory framework for drone delivery services. Finally, this Comment explains how the adoption of the American Drones Act would produce various economic, environmental, and social benefits for millions of individuals across the U.S.—such as the ability to efficiently scale BVLOS drone operations, emissions reduction, and increased consumer access to healthy foods and vital medicines.

Prediction framework for parking search cruising time and emissions in dense urban areas

AbstractThe growing need for temporary pickups/drop-offs and commercial deliveries is crowding out the already inadequate on-street parking spaces designated for car trips, deteriorating the phenomenon of parking search. This paper: (1) uses empirical data and conducts descriptive and comparative analysis using a spatial lag model to analyze the factors influencing average cruising time (ACT) related to parking search, and (2) proposes a novel framework to predict grid-based ACT and to estimate average emission metrics (AEM). The study inputs an aggregated GPS dataset in a 6-month period to the framework and uses New York City and Los Angeles as case study cities. The descriptive and comparative analysis results support the spatial spillover effect of parking search and reveal that residential area, retail area, accommodation, and food services (hotels, restaurants, bars, etc.) employees are the most significant influencing factors on ACT and that temporary pickups/drop-offs and commercial delivery are also unneglectable sources of parking search. The prediction results show a concentrated distribution of ACT in New York City due to private vehicles’ spillover of parking searches. Los Angeles exhibits a relatively high degree of overlap between parking hotspots and emission blackspots, particularly in areas with intense truck activity, further substantiating the close relationship between truck activities and elevated emissions. Following the key findings, the paper proposes several policy recommendations. In practice, this prediction framework can ingest short-term data to provide ACT prediction maps to identify parking hotspots and emission blackspots.

A novel approach to the manufacture of dissolving microneedles arrays using aerosol jet printing

Despite much research over the last few decades, microneedle arrays for the transdermal delivery of drugs have failed to live up to their initial promise. This may be changing however as companies close in on the commercial delivery of vaccines via this technology. These breakthroughs will undoubtably increase the interest in the use of microneedles arrays for the delivery of biopharmaceuticals but will also drive research into the development of scalable manufacturing processes for their fabrication. While 3D printing is an exciting development in this field, conventional Additive Manufacturing (AM) techniques are unsuitable for biopharmaceuticals due to the harsh processing conditions which can cause degradation of the active ingredient.In this paper we report the first use of Aerosol Jet Printing (AJP) as an AM technique for the fabrication of dissolving microneedle arrays. A formulation of poly(vinyl pyrrolidone), trehalose and glycerol dissolved in water was prepared and characterised. The formulation was aerosolised using ultrasonication and deposited onto a silicon substrate. Critical process parameters such as Computer Aided Design (CAD) design, flow rate, temperature, print speed and focussing ratio were studied to determine their impact on the microneedle quality attributes. 4 × 4 microneedle arrays were printed, with needle heights > 500 µm achieved with print times of 30 mins or less. The resulting needles had sufficient strength and sharpness to penetrate porcine skin samples. Importantly, the microneedles can be fabricated under benign conditions which should be suitable for the processing and subsequent delivery of biopharmaceuticals across the skin.

Environmental and economic impacts of drone-assisted truck delivery under the carbon market price

Logistics delivery companies today are under high pressure from the carbon market. As an emerging commercial delivery tool, the drone has the advantages of low carbon emissions and cost. This study proposes an innovative dual-objective mixed-integer linear programming model to explore the environmental and economic impacts of drone-assisted truck delivery under the carbon market price. It uses JD.com in China as a case study to explore the company's benefits of adopting drone-assisted delivery. The results show that compared to traditional truck delivery, drone-assisted delivery reduced carbon emissions by 24.90%, reduced total cost by 22.13%, and shortened delivery time by 20.65%. In addition, the effects of some key elements on the total cost and carbon emissions are compared. The analysis shows that drone battery cycle life, fuel price, driver's wage, truck speed, and drone speed are vital for drone-assisted truck delivery.

Identifying Factors that Determine Effectiveness of Delivery Agents in Biolistic Delivery Using a Library of Amine-Containing Molecules.

Biolistic transfection is a popular and versatile tool for plant transformation. A key step in the biolistic process is the binding of DNA to the heavy microprojectile using a delivery agent, usually a positively charged molecule containing amine groups. Currently, the choice of the commercial delivery agent is mostly limited to spermidine. In addition, the detailed delivery mechanism has not been reported. To help broaden the selection of the delivery agent and reveal the fundamental mechanisms that lead to high delivery performance, a library of amine-containing molecules was investigated. A double-barrel biolistic delivery device was utilized for testing hundreds of samples with much-improved consistency. The performance was evaluated on onion epidermis. The binding and release of DNA were measured via direct high-performance liquid chromatography analysis. This study shows that the overwhelming majority of the amine library performed at the same level as spermidine. To further interpret these results, correlations were performed with thousands of molecular descriptors generated by chemical modeling. It was discovered that the overall charge is most likely the key factor to a successful binding and delivery. Furthermore, even after increasing the amount of the DNA concentration 50-fold to stress the binding capacity of the molecules, the amines in the library continued to deliver at a near identical level while binding all the DNA. The increased DNA was also demonstrated with a Cas9 editing test that required a large amount of DNA to be delivered, and the result was consistent with the previously determined amine performance. This study greatly expands the delivery agent selection for biolistic delivery, allowing alternatives to a commercial reagent that are more shelf-stable and cheaper. The library also offers an approach to investigate more challenging delivery of protein and CRISPR-Cas via the biolistic process in the future.

Effect of surfactants and Co-surfactants in formulation of noni fruit extract in virgin coconut oil-based emulsion

This study aims to formulate and characterize the emulsion of Morinda citrifolia L. (Noni fruit) extract in virgin coconut oil (VCO) using the Phase Inversion Composition method (PIC). The chemical compositions with bioactivities in noni fruit extracts obtained from Soxhlet extraction method were analyzed by using Gas Chromatography-Mass Spectrometry to understand their potential uses. To formulate VCO-based emulsion, different types of surfactants (Cremophor EL, Cremophor RH 40, and Tween 80) and co-surfactants (Propylene glycol, Ethylene glycol, and Ethanol) were varied in concentration. The characteristics of VCO-based emulsions in terms of droplet size and stability were analyzed to find the optimal condition for stable emulsion. Among three types of surfactants, Cremophor RH 40 mixed with propylene glycol or ethylene glycol provided the most stable VCO-based emulsion in nanoscale droplet size with the minimal droplet size at 332 nm. The noni extracts were mixed in the optimized VCO-based formula at the VCO's concentration of 6, 8, and 10%. The results showed that the addition of noni extracts increased the droplet size of emulsion from nanometer scale to micrometer scale and reduced the emulsion stability. At the optimal condition, the mixture containing 4.5% VCO, 1.5% propylene glycol, and 0.3% Noni extract showed the smallest droplet size (1.1–1.85 μm), which was in the range of most commercial emulsions, with good stability in a 5-day period. This study provides a promising approach to formulate stable emulsions with low levels of surfactant and co-surfactant, which is extensively significant for commercial delivery systems.

The human impact of commercial delivery cycling injuries: a pilot retrospective cohort study

BackgroundCommercial delivery cyclists represent a uniquely vulnerable and poorly understood road user. The primary aim of this study was to pilot whether cycling injuries could be categorised as either commercial or non-commercial using documentation entered into routine hospital medical records, in order to determine the feasibility of conducting a large cohort study of commercial cycling injuries in the future. A secondary aim was to determine which key demographic, incident and injury characteristics were associated with commercial versus non-commercial cycling injuries in emergency.MethodsPilot retrospective cohort study of adults presenting to an acute public hospital emergency department between May 2019 and April 2020 after sustaining a cycling-related injury. Multinomial logistic regression was used to examine the demographic, incident and injury characteristics associated with commercial compared to non-commercial cycling.ResultsOf the 368 people presenting to the emergency department with a cycling-related injury, we were able to categorise 43 (11.7%) as commercial delivery cyclists, 153 (41.6%) as non-commercial cyclists and the working status of 172 (46.7%) was unable to be confirmed. Both commercial and unconfirmed cyclists were more likely to be younger than non-commercial cyclists. Compared to non-commercial cyclists, commercial cyclists were 11 times more likely to speak a language other than English (AOR 11.3; 95% CI 4.07–31.30; p<0.001), less likely to be injured from non-collision incidents than vehicle collisions (AOR 0.36; 95% CI 0.15–0.91; p=0.030) and were over 13 times more likely to present to the emergency department between 8.00pm and 12.00am compared to the early morning hours (12.00 to 8.00am) (AOR 13.43; 95% CI 2.20–82.10; p=0.005).ConclusionsThe growth of commercial cycling, particularly through online food delivery services, has raised concern regarding commercial cyclist safety. Improvements in the recording of cycling injury commercial status is required to enable ongoing surveillance of commercial cyclist injuries and establish the extent and risk factors associated with commercial cycling.

Impact of low carbon fuels (LCF) on the fuel efficiency and NOx emissions of a light-duty series hybrid commercial delivery vehicle

This work evaluates the potential of using four different low carbon fuels (LCF) in a series hybrid vehicle concept and compares the results to a conventional diesel combustion counterpart. To do this experimental data from a low NOx emission calibration is obtained for each of the different fuels, and 0-D vehicle simulations of an OPEL Movano van model are made to evaluate the performance, in terms of fuel consumption and engine-out NOx, during the Worldwide harmonized Light vehicles Test Cycles (WLTC) using a simplified engine map strategy. The vehicle selection allows to evaluate the scenario of a delivery application with three different payloads 0%, 50% and 100%. The work is motivated by the current automotive industry’s need to reduce emissions and use energy resources efficiently, evaluating different strategies to fulfil both objectives. The evaluation of different energy sources –such as LCF– and powertrains, have been extensively researched topics, however the information is more scarce using a combination of both strategies. The results from this work show that series hybrid vehicle presents a reduction of fuel consumption of up to 5% with 100% payload, across all fuels tested. Nonetheless, engine-out emission levels of NOx show 16% worse performance for the hybrid case due to its operation at higher engine speeds and loads during the charging of the battery.

A Security Review in the UAVNet Era: Threats, Countermeasures, and Gap Analysis

Unmanned Aerial Vehicles (UAVs) are becoming one of the main technological supports for commercial applications, embracing many domains ranging from human safety to the medical field, agriculture and environment, multimedia production, and even commercial delivery. This rise in popularity, however, is causing an increasing interest from criminals, making UAVs the target of new attacks. To fully characterize the current UAV cybersecurity landscape, we perform a complete literature review, digging into drone security historic facts and scientific studies on the matter, reviewing specialized articles and scientific papers focusing on cybersecurity threats and gaps in the context of small UAVs in commercial applications. Being a recent research and development area, most of the articles have been published between 2016 and 2020 as a direct consequence of the increase of security concerns and interest in the drone field. Papers in this review deal with UAV cyberthreats and related vulnerabilities, identifying flaws experimented in a lab or describing incidents detected in the field. Communication, sensors, and system misconfigurations are among the most important threat vectors, while sensor spoofing/jamming and malware DoS/control are among the most cited threats. Threat vectors permit depicting a complete overview of the topic and potential countermeasures known to date, with related gap analysis, also accounting for the recent Unmanned Aircraft System evolution toward ad hoc or cloud-based UAV networks. Countermeasures include the adoption of traditional communication encryption and standard protocols, GPS spoofing/jamming mitigation, encryption and privacy-aware implementations, and counter-malware techniques, to name the most adopted. It also emerges that often attacks are simply ported or adapted from other attacks in similar domains, while peculiar attacks still remain such as targeted physical attacks, specific UAV malware, and GPS spoofing/jamming.

Leveraging Blockchain for Secure Drone-to-Everything Communications

The popularity of drones has increased their deployment in a wide range of applications like commercial delivery, industrial systems, monitoring, surveillance, and surveys. The facility of fast deployment and cost effectiveness make drones a potential choice for an aerial base station to serve user equipments (UEs) in a defined area. Drones are equipped with night vision cameras, advanced sensors, and GPS receivers, which make them able to capture data and either analyze it to discover new patterns or transmit it to the remote cloud for storage and processing. Furthermore, the drones data relaying system helps to extend the service coverage area to provide reliable communication connection to isolated UEs. However, the deployment of drones at remote locations relies only on GPS, and these systems are prone to various attacks that can lead to signal blockage. Data integrity and privacy are important issues that must be addressed before the deployment of drones in commercial sectors. Therefore, in this article, we propose a blockchain-based security approach for drone-to-everything communications wherein the location of drones is tracked based on the segment division of area under deployment. Moreover, we design a miner node selection algorithm that uses computational resources, battery status, and time of flight of a drone as parameters to select the miner node. The security evaluation of the proposed framework clearly shows the viability of blockchain in drone deployments across remote sites.

EXPLORATION OF LATENT DEMAND FOR CRAUDSHIPPING SERVICE USING FACTOR ANALYSIS

This paper presents the experimental study results on exploring the latent demand for crowdshipping service. Factor analysis has been used as the key methodology to reveal the basic attributes of the demand. Given the absence of crowdshipping-based services in Ukraine we focused on evaluation the intentions of online shoppers to use the proposed delivery system. To do this we used five-point Likert scale to evaluate 15 statements in regard to pros and cons attitudes towards crowdshipping. Pros online shopping behavior has been considered as the basic component to promote the crowdshipping service. In this case the formed statements for pros crowdshipping have been described the time, cost, ecology, flexibility of the proposed delivery service. In turn the anti-online shopping intentions have been presented with enjoy of physical stores visiting, social interaction needs, browsing the products and etc. As the results of the factor analysis, we revealed four factors and one of them has been identified as “ProCrowdShoppers”. This factor covers 38 % of variance for all data of the study. Such a high value allows us to make conclusion about high potential of crowdshipping deployment in Ukraine. The second factor has been identified as “Con_sustainable_shoppers” which covered people that do not care about ecology during the delivery fulfilment. This group allowed us to make conclusion that ecological problem and sustainable city development paradigm did not penetrate yet all social groups. The second factor covers 12 % of variance for data that should be taken into account when the crowdshipping service will be deployed in Ukrainian cities. The third factor has been identified as “Store_lovers” covering 8.99 % of variance. And the fourth factor was revealed as “Windows_shoppers”. So, the third and the fourth factors reflect the people’s intentions to remain shopping in the physical stores. The total variance covered by these two factors is 16.26 %. Summarizing we can say that crowdshipping has a high opportunity to be deployed in Ukrainian cities. To become widely used it should be grounded on flexible, reliable and ecologically friendly basis. Along with that the time saving should also be provided to compete with commercial delivery services.

Pursuing a fully closed cellular immunotherapy manufacturing model

<div class="authors authors-lg"><div class="author"><div class="author-img"><img src="https://cdn.insights.bio/uploads/Samuel-sq.jpg" data-image="1"></div><div class="author-det"> <b>Ed Samuel </b>serves as SVP Technical Operations at Achilles with responsibility for overseeing GMP operations for product delivery of its autologous T cell therapies, the expansion of the Achilles manufacturing footprint and the integration of automation and device technology driving the future platform for commercial delivery. Ed has over 18 years of industry and academic experience in process development, technology transfer, GMP manufacturing, QC and regulatory affairs in the field of cell and gene therapy. Before joining Achilles in December 2017, Ed was the Cell Therapy Operations Manager for Europe at Orchard Therapeutics where he was responsible for overseeing CDMO tech transfer and establishing the supply-chain infrastructure to support cell therapy manufacturing and regulatory submissions in the US and Europe. Previously, Ed held positions at Cognate BioServices Ltd as Director for Manufacturing and in post-doctoral translational research at University College London (UCL). Ed holds a PhD in T cell Immunology from UCL, and an MSc in Medical Immunology from King’s College London. </div></div></div>

Intent-driven cloud resource design framework to meet cloud performance requirements and its application to a cloud-sensor system

In cloud service delivery, the cloud user is concerned about “what” function and performance the cloud service could provide, while the cloud provider is concerned about “how” to design proper underlying cloud resources to meet the cloud user’s requirements. We take the cloud user’s requirement as intent and aim to translate the intent autonomously into cloud resource decisions. In recent years, intent-driven management has been a widely spread management concept which aims to close the gap between the operator’s high-level requirements and the underlying infrastructure configuration complexity. Intent-driven management has drawn attention from telecommunication industries, standards organizations, the open source software community and academic research. There are various application of intent-driven management which are being studied and implemented, including intent-driven Software Defined Network (SDN), intent-driven wireless network configuration, etc. However, application of intent-driven management into the cloud domain, especially the translation of cloud performance-related intent into the amount of cloud resource, has not been addressed by existing studies. In this work, we have proposed an Intent-based Cloud Service Management (ICSM) framework, and focused on realizing the RDF (Resource Design Function) to translate cloud performance-related intent into concrete cloud computation resource amount settings that are able to meet the intended performance requirement. Furthermore, we have also proposed an intent breach prevention mechanism, P-mode, which is essential for commercial cloud service delivery. We have validated the proposals in a sensor-cloud system, designed to meet the user’s intent to process a large quantity of images collected by the sensors in a restricted time interval. The validation results show that the framework achieved 88.93 ~ 90.63% precision for performance inference, and exceeds the conventional resource approach in the aspects of human cost, time cost and design results. Furthermore, the intent breach prevention mechanism P-mode significantly reduced the breach risk, at the same time keeping a high level of precision.

Making space for drones: The contested reregulation of airspace in Tanzania and Rwanda

AbstractIn contrast to their use in warfare and surveillance, there is growing interest in the potential of “drones for good” to deliver societal benefits, for example by delivering medical products and other essential goods. Yet development of medical and commercial delivery has been limited globally by restrictive regulation to protect airspace safety and security. In this paper we examine how certain African countries have become testbeds for new forms of drone infrastructure and regulation, driven by the overlapping interests of governments, drone operators, and international development agencies. In particular we explore the factors that have led to the development of an advanced medical delivery network in Rwanda and contrast that with the closing down of airspace for drones in Tanzania. The paper makes a distinctive contribution to research on the ongoing constitution of dronespace as a sphere of commercial and governmental activity. Rwanda’s drone delivery system is seen as the forerunner for the wider enclosure and parcelling up of the lower atmosphere into designated drone corridors that limit the democratic and disruptive potential of drone activity in line with prevailing logics of airspace regulation.

Enhancing gene editing efficiency for cells by CRISPR/Cas9 system-loaded multilayered nanoparticles assembled via microfluidics

Most non-viral carriers for in vitro delivery of nucleic acids suffer from low efficiency of introducing mRNA and other nucleic acids, especially large mRNA. Cas9 protein is the nuclease part of the powerful gene-editing tool, CRISPR/Cas9 system, Cas9 mRNA is particularly large, thus presents a big challenge for delivery. We assembled a multilayered biodegradable nanocarrier to load Cas9 mRNA inside to protect Cas9 mRNA from degradation. We used a microfluidic chip to synthesize a small, positively charged, and degradable core to attract negatively charged Cas9 mRNA. The microfluidic assembly allows the core to be small enough to incorporate into a cationic liposome. The multilayered nanocarriers elevated the delivery efficiency of Cas9 mRNA by over 2 folds and increased the expression by over 5 folds compared to commercially used non-viral carriers. In addition, the multilayered nanocarriers do not require reduced serum medium for transfection. When using the standard complete medium for transfection, the multilayered nanocarriers could increase the expression of Cas9 mRNA by over 15 folds compared to commercially used non-viral carriers. The co-delivery of Cas9 mRNA and sgRNA via LRC elevated the gene-editing efficiency by 3 folds compared to that via commercially used non-viral carriers. Based on the higher transfection efficiency of Cas9 mRNA/sgRNA than commercially used non-viral carriers, these multilayered nanocarriers may have a good prospect as efficient commercial delivery carriers for Cas9 mRNA/sgRNA and other nucleic acids.