Short Delivery Research Articles

Express shipments with autonomous robots and public transportation

Growing urbanization, exploding e-commerce, heightened customer expectations, and the need to reduce the environmental impact of transportation ask for innovative last-mile delivery solutions. This paper explores a new express shipment model that combines public transportation with Autonomous Robots (ARs) and studies its real-time management. Under dynamic demand arrivals with short delivery time promises, we propose a rolling horizon framework and devise a machine learning-enhanced Column Generation (CG) methodology to solve the real-time AR dispatching problem. The results of our numerical experiments with real-world delivery demand data show the significant potential of the proposed system to reduce travel time, vehicle traffic, emissions, and noise. Our results also reveal the efficacy of the learning-based CG methodology, which provides almost the same quality solutions as the classical CG approach with much less computational effort.

Integrating socioeconomic and ecological data into restoration practice.

Driven by the United Nations Decade on Restoration and international funding initiatives, such as the Mangrove Breakthrough, investment in mangrove restoration is expected to increase. Yet, mangrove restoration efforts frequently fail, usually because of ad hoc site-selection processes that do not consider mangrove ecology and the socioeconomic context. Using decision analysis, we developed an approach that accounts for socioeconomic and ecological data to identify sites with the highest likelihood of mangrove restoration success. We applied our approach in the Biosphere Reserve Marismas Nacionales Nayarit, Mexico, an area that recently received funding for implementing mangrove restoration actions. We identified 468 potential restoration sites, assessed their restorability potential based on socioeconomic and ecological metrics, and ranked sites for implementation with spatial optimization. The metrics we used included favorable conditions for propagules to establish and survive under sea-level rise, provision of ecosystem services, and community dynamics. Sites that were selected based on socioeconomic or ecological metrics alone had lower likelihood of mangrove restoration success than sites that were selected based on integrated socioeconomic and ecological metrics. For example, selecting sites based on only socioeconomic metrics captured 16% of the maximum attainable value of functioning mangroves able to provide propagules to potential restoration sites, whereas selecting sites based on ecological and socioeconomic metrics captured 46% of functioning mangroves. Our approach was developed as part of a collaboration between nongovernmental organizations, local government, and academics under rapid delivery time lines given preexisting mangrove restoration implementation commitments. The systematic decision process we used integrated socioeconomic and ecological considerations even under short delivery deadlines, and our approach can be adapted to help mangrove restoration site-selection decisions elsewhere.

Predicting adverse birth outcome among childbearing women in Sub-Saharan Africa: employing innovative machine learning techniques

BackgroundAdverse birth outcomes, including preterm birth, low birth weight, and stillbirth, remain a major global health challenge, particularly in developing regions. Understanding the possible risk factors is crucial for designing effective interventions for birth outcomes. Accordingly, this study aimed to develop a predictive model for adverse birth outcomes among childbearing women in Sub-Saharan Africa using advanced machine learning techniques. Additionally, this study aimed to employ a novel data science interpretability techniques to identify the key risk factors and quantify the impact of each feature on the model prediction.MethodsThe study population involved women of childbearing age from 26 Sub-Saharan African countries who had given birth within five years before the data collection, totaling 139,659 participants. Our data source was a recent Demographic Health Survey (DHS). We utilized various data balancing techniques. Ten advanced machine learning algorithms were employed, with the dataset split into 80% training and 20% testing sets. Model evaluation was conducted using various performance metrics, along with hyperparameter optimization. Association rule mining and SHAP analysis were employed to enhance model interpretability.ResultsBased on our findings, about 28.59% (95% CI: 28.36, 28.83) of childbearing women in Sub-Saharan Africa experienced adverse birth outcomes. After repeated experimentation and evaluation, the random forest model emerged as the top-performing machine learning algorithm, with an AUC of 0.95 and an accuracy of 88.0%. The key risk factors identified were home deliveries, lack of prenatal iron supplementation, fewer than four antenatal care (ANC) visits, short and long delivery intervals, unwanted pregnancy, primiparous mothers, and geographic location in the West African region.ConclusionThe region continues to face persistent adverse birth outcomes, emphasizing the urgent need for increased attention and action. Encouragingly, advanced machine learning methods, particularly the random forest algorithm, have uncovered crucial insights that can guide targeted actions. Specifically, the analysis identifies risky groups, including first-time mothers, women with short or long birth intervals, and those with unwanted pregnancies. To address the needs of these high-risk women, the researchers recommend immediately providing iron supplements, scheduling comprehensive prenatal care, and strongly encouraging facility-based deliveries or skilled birth attendance.

Part feeding scheduling for mixed-model assembly lines with autonomous mobile robots: benefits of using real-time data

ABSTRACT Mixed-model assembly is increasingly widespread to meet customer requirements for customisation and short delivery times. Flexible part feeding systems are required to timely replenish assembly stations with materials, avoid station idle times, and limit inventory levels on the shop floor. Part feeding scheduling is a complex and dynamic problem, affected by processing time fluctuations, equipment failures, and variations of product mix. Although real-time data of factory processes and resources is widely available and can be exploited using a digital twin of the part feeding system, there is a lack of scientific evidence on the benefits of using real-time data in part feeding scheduling. This research addresses this gap by developing an agent-based simulation model of a part feeding system with a fleet of autonomous mobile robots (AMRs) and comparing a real-time dynamic part feeding scheduling approach with static benchmark approaches. Numerical results indicate that using real-time data improves the performance of the part feeding system and the assembly system significantly, and allows improving the trade-off between the AMR fleet size and the total storage capacity on the shop floor, resulting in lower investment costs for AMRs given a certain storage capacity or lower required storage capacity given an AMR fleet.

Efficacy and safety of a novel temperature-controlled catheter for cavotricuspid isthmus ablation.

Maintaining an adequate temperature at the target site is essential for effective ablation. We hypothesized that a tissue temperature-controlled (T-Con) catheter for cavotricuspid isthmus (CTI) ablation could improve the procedural ablation parameters. To evaluate the efficacy and safety of the T-Con (DiamondTemp™) catheter for CTI ablation compared with non-irrigation (Non-Irri) and irrigation (Irri) catheters. We analyzed 150 patients who underwent prophylactic CTI ablation combined with pulmonary vein isolation. The Non-Irri, Irri, and T-Con catheter groups comprised 50 patients each, and the ablation procedural parameters and complications were compared between these groups. There were no significant differences in clinical background characteristics among the three groups. The Kruskal-Wallis and post hoc tests demonstrated that the T-Con group showed the lowest total radiofrequency energy delivery time among the three groups (median [25 and 75 percentiles]: 340 [209, 357], 147 [100, 199], and 83 [61, 109] s, respectively in the Non-Irri, Irri, and T-Con groups; T-Con versus Non-Irri, p < .01; T-Con versus Irri, p < .01). The total procedural time and acute reconnection rate in the T-Con group (264 s and 4%, respectively) were lower than those in the Non-Irri group (438 s and 24%) but were similar to those in the Irri group (268 s and 6%). No significant complications were observed in any group. The T-Con catheter achieved a short energy delivery time and a low acute reconnection rate, indicating its potential as an alternative catheter for CTI ablation.

Angiographic and clinical impact of balloon inflation time in percutaneous coronary interventions with sirolimus-coated balloon: A subanalysis of the EASTBOURNE study

IntroductionPercutaneous coronary intervention (PCI) with drug-coated balloon (DCB) is an attractive strategy for the treatment of obstructive coronary artery disease (CAD). The implantation technique strongly influences the outcome of DCB PCI: accurate and adequate lesion preparation, short delivery time and sufficient DCB inflation time are deemed crucial to warrant adequate drug transfer and mitigate the risk of immediate vessel recoil and flow-limiting dissections. However, the optimal DCB inflation time is unclear, current consensus documents suggesting 30–60 s based on Experts' opinion. However, clinical studies comparing the prognostic role of different inflation times are scarce and mainly involve paclitaxel-coated balloons. In this study we aimed to assess the impact of different inflation times in patients undergoing PCI with a sirolimus-coated balloon (SCB). MethodsWe conducted a post-hoc analysis of the prospective, multicenter, EASTBOURNE study, classified into two study groups according to balloon inflation time: long (>30 s) versus short (≤30 s). The primary endpoint was target lesion revascularization (TLR) at 24-month follow-up. Secondary clinical endpoints were major adverse clinical events (MACE), death, non-fatal myocardial infarction (MI), and BARC 2–5 bleedings. Furthermore, angiographic endpoints (the rate of bailout stenting and post-procedural TIMI flow <3) were also addressed. ResultsA total of 2289 lesions (2092 in the long inflation group, 197 in the short inflation group) were included in the analysis. Median balloon inflation time was 60 s in the long inflation and 30 s in the short inflation group. The two study groups experienced a similar rate of TLR [6.2 % in the short versus 6.3 % in the long inflation group, p = 1.00] as well MACE (p = 0.683), death (p = 0.102), non-fatal MI (p = 0.822), and BARC 2–5 bleedings (p = 0.252). These results were consistent when considering subpopulations with different target lesion phenotypes (in-stent restenosis, de-novo lesions, large and small vessels). Interesting, the rate of bailout stent implantation and post-procedural TIMI flow <3 was higher in the short SCB inflation time, as compared to the standard strategy. ConclusionsShort vs. long SCB inflation time is associated with a higher need of bailout stenting after PCI with SCB, with similar clinical outcomes at 24-month follow-up.

Bayes goes big: Distributed MCMC and the drivers of E-commerce conversion

This work researches the drivers of e-commerce conversion of one of the largest e-commerce companies in the Netherlands. We focus on product page conversion, i.e., the probability that a customer who visits a specific product page also buys the product. This probability differs between products, which we explain by a variety of factors like pricing, delivery times, reviews, seller type, and the quality of the content. Understanding the drivers of conversion is the first step in increasing it, and therefore an important step in increasing overall sales. We describe the process of transforming Big Data into valuable insights using Bayesian statistics and apply a Bayesian Binomial model to a dataset of 15 million records using a distributed MCMC algorithm. In addition, we apply a simple Binomial GLM on a small sample of these 15 million records for comparison. We find that using the full 15 million records results in a significant reduction in the variance of the estimated parameters. In terms of the actual drivers of e-commerce conversion, we observe that products with competitive pricing, short delivery times, and good content all achieve a higher conversion on average. Furthermore, reviews, average review score, and the number of reviews for a product have a large positive effect on conversion compared to other characteristics. This provides a unique insight into what makes people decide whether or not to purchase a product.

Exploring the Optimal Intertwin Delivery Interval for Vaginal Delivery.

The effect of prolonged intertwin delivery interval (IDI) is not well studied. This work aimed to assess the inflection point for Cesarean delivery (CD) and associated adverse maternal and neonatal outcomes. This was a retrospective cohort study at a single tertiary care center. The study included women with twin pregnancies in 2010-2019 who reached the second stage of labor, and assessed the most predictive cutoff for CD using Youden J statistic and compared adverse maternal and neonatal outcomes between short and prolonged intertwin delivery intervals. A total of 461 gravidas reached the second stage of labor and were included in the study. Using the ROC curve and Youden J statistic, the IDI cutoff was set at 15 min (80% sensitivity, 75% specificity, p < 0.001), with 312 women in the short and 149 in the prolonged IDI groups. Women in the prolonged IDI group were less likely to deliver the second twin vaginally (75.8% vs. 93.3%, p < 0.001). Postpartum hemorrhage (PPH) (39.1% vs. 24.7%, p = 0.01), and placental abruption (4% vs. 1%, p = 0.03) were more likely to occur in the prolonged IDI group. An increased rate of neonatal acidemia and low 5-min Apgar score were also found in the prolonged IDI group (15.7% vs. 4.3%, P = 0.01, 9.7% vs. 3.5%, p = 0.008; respectively). IDIs of more than 15 min are associated with increased risk of adverse maternal and neonatal outcomes. These findings should be used for counseling and managing twin pregnancies attempting vaginal delivery.

Update on the advances and challenges in bioequivalence testing methods for complex topical generic products.

Most of the government regulatory agencies, including the United States Food and Drug Administration and the European Medicine Agency, demand that the generic complex topical products prove pharmaceutical and bioequivalence. The evaluation of bioequivalence for complex topical dermatological formulations is a challenging task that requires careful consideration of several factors. Although comparative clinical studies are still considered the gold standard approach for establishing bioequivalence in most formulations, these studies can be costly and insensitive to detect formulation differences. Therefore, significant efforts have been made to develop and validate alternative approaches that demonstrate bioequivalence and expedite the availability of high-quality generic topical dermatological products. This article reviews the current methods for determining the bioequivalence of topical formulations in humans, with particular emphasis on recent advances in these methodologies. Most of the alternative methods are sensitive and reproducible, with the capability to ease the financial burden of comparative clinical studies within a short delivery time. The limitations associated with each technique are reviewed in detail.

Integrated model of product manufacturing cycle time estimation

In modern business conditions, companies engaged in individual and small-batch production are faced with one of the key tasks of production management, which refers to weekly and, very often, daily production planning. Short delivery times, limited prices, and high requirements regarding the quality and method of product delivery all require timely planning of production capacities, tools, and devices, as well as the number of workers and their allocation to individual jobs. In such production conditions, which are determined by the market, it is of particular importance to determine the production time of the product quickly and qualitatively, including the production price, within the framework of making an offer according to the customer's demand. The paper presents a cycle time estimation model as a part of the overall product manufacturing time, using ANN and fuzzy neural networks.

Digital Threads – benefits, challenges, and best practices

AbstractThe premise of Digital Engineering (DE) – a term coined by the US DoD, is to introduce efficiency and agility into engineering practices based on digital representations of complex systems under development. DE aims to foster early and virtual validations, virtual exploration of solutions and design robustness by automating current document centric engineering processes. As stated by the DoD, DE is expected to result in shortening delivery time, reduced cost of development driving increased quality and trust that the intended system will indeed satisfy the stakeholder needs. The core technological pillars of digital engineering are model based engineering, designation of authoritative sources of truth to avoid ambiguity and inconsistency and establishing technological platforms to facilitate collaboration, security, and IP protection across all stakeholders. “Digital Threads” is an information architecture that aims to establish digital continuity across product lifecycle activities, foster engineering integrity, effective change management, tradeoff analysis, and dissemination of operational data. Digital threads are an essential part of the DoD Digital Engineering strategy. There are technological challenges to implement digital threads, as it requires to establish a digital fabric across various modeling and engineering operational environments. As of today, this topic is still in its infancy and the industry is seeking solutions and standards for it.

Digital Twins: building your own virtual lab for enhanced vocational education training

The emergence, in the context of Industry 4.0, of tools for developing Digital Twins of automated industrial systems brings about a paradigm shift in the development of control systems. Their virtual commissioning allows for shortening delivery times of automated solutions, among other benefits, but also highlights the need for competent technicians in these technologies. The academic classroom is a breeding ground for future professionals. This article presents an initiative carried out by the Technological Innovation and Intelligent Systems area at Tknika to exploit and transfer results of projects and services developed with these tools to vocational training teachers.

Comparison of the Efficacy and Safety of Sublingual Versus Oral Misoprostol for the Induction of Labor: A Randomized Open-Label Study.

Introduction Misoprostol (prostaglandin E1 analog) is being used for the induction of labor by vaginal, oral, and sublingual routes. Oral misoprostol is the preferred route for induction of labor, but the use of sublingual misoprostol appears promising due to a faster onset of action. This study was done to compare the efficacy and safety of oral and sublingual misoprostol for induction of labor in term pregnancy. Materials and methods One hundred and sixty patients were randomly allocated to one of the two groups to receive 50 micrograms oforal and sublingual misoprostol four hourly for a maximum of six doses. Primigravida at 37-42 weeks of gestation with singleton pregnancy, cephalic presentation, Bishop score (<5), and reassuring fetal heart rate were included in the study. Misoprostol dose was withheldif the active phase of labor was reached or if the cervixwas favorable for amniotomy (Bishop score greater than or equal to eight). The change in the Bishop score with misoprostol was studied along with adverse effects and neonatal outcomes. Results The mean number of 50 mcg misoprostol doses required was significantly less in the sublingual group (2.94±0.97 versus 2.13±0.92; p<0.0001). The rate of change of the mean Bishop score was faster in the sublingual group. After four hours of the first dose, the mean Bishop score changed to 3.52±2.14 versus 4.68±2.34 (p=0.001), and, similarly, after eight hours, it was 10.48±2.59 versus 11.39±2.06, and this difference was statistically significant (p=0.015). The mean induction delivery interval was significantly lower in the sublingual group. The need for labor augmentation, mode of delivery, andadverse effects were similar in both groups. The incidence of meconium-stained liquor and NICU admission was also similar in both groups. Conclusion Sublingmisoprostolstol has a short induction delivery interval and comparable side effects when compared to omisoprostolstol. Sublingmisoprostolstol is recommended for induction of labor at term.

Lateness in production systems - In a nutshell: How to determine the causes of lateness at work systems?

Adherence to customer due dates is the yardstick for the performance of manufacturing companies. In the era of same-day delivery, consumers expect reliable delivery of ordered goods and short delivery times. Also, in the field of business-to-business supply, it is evident that adherence to delivery dates is a fundamental logistical objective for companies. Contract manufacturers, in particular, are confronted with significant challenges: strong fluctuations in customer demand, shorter requested delivery times, and high competitive pressure require appropriate organisation, planning and control of production. However, companies often miss their schedule reliability targets and fail to identify the right causes for these failures. This raises the question of what factors influence the failure to meet schedule reliability targets, how to identify such factors, and what options are available to counteract them. This contribution addresses this issue and focuses on ways to analyse the emerging lateness at work systems in production areas as a deviation of the actual form the planned throughput time. We present existing approaches to analysing the lateness behaviour at work systems and extend the current theory of logistical modelling to determine the three drivers of the so-called relative lateness – planning influences, variance of work-in-process (WIP) and sequence deviations – at work systems systematically. Through this analysis, we enable the practical applicator to initiate target-oriented countermeasures to improve the schedule reliability of their work systems with acceptable analysis expenditure.

Delivery time reduction for mixed photon-electron radiotherapy by using photon MLC collimated electron arcs

Objective. Electron arcs in mixed-beam radiotherapy (Arc-MBRT) consisting of intensity-modulated electron arcs with dynamic gantry rotation potentially reduce the delivery time compared to mixed-beam radiotherapy containing electron beams with static gantry angle (Static-MBRT). This study aims to develop and investigate a treatment planning process (TPP) for photon multileaf collimator (pMLC) based Arc-MBRT. Approach. An existing TPP for Static-MBRT plans is extended to integrate electron arcs with a dynamic gantry rotation and intensity modulation using a sliding window technique. The TPP consists of a manual setup of electron arcs, and either static photon beams or photon arcs, shortening of the source-to-surface distance for the electron arcs, initial intensity modulation optimization, selection of a user-defined number of electron beam energies based on dose contribution to the target volume and finally, simultaneous photon and electron intensity modulation optimization followed by full Monte Carlo dose calculation. Arc-MBRT plans, Static-MBRT plans, and photon-only plans were created and compared for four breast cases. Dosimetric validation of two Arc-MBRT plans was performed using film measurements. Main results. The generated Arc-MBRT plans are dosimetrically similar to the Static-MBRT plans while outperforming the photon-only plans. The mean heart dose is reduced by 32% on average in the MBRT plans compared to the photon-only plans. The estimated delivery times of the Arc-MBRT plans are similar to the photon-only plans but less than half the time of the Static-MBRT plans. Measured and calculated dose distributions agree with a gamma passing rate of over 98% (3% global, 2 mm) for both delivered Arc-MBRT plans. Significance. A TPP for Arc-MBRT is successfully developed and Arc-MBRT plans showed the potential to improve the dosimetric plan quality similar as Static-MBRT while maintaining short delivery times of photon-only treatments. This further facilitates integration of pMLC-based MBRT into clinical practice.

PERANAN BIMBINGAN PENYULUHAN ISLAM DALAM PEMBENTUKAN KARAKTER ANAK DI TAMAN PENDIDIKAN ALQUR’AN

Islamic counseling guidance is an effort to provide assistance in the form of directions delivered by someone who is more knowledgeable in his field, so that someone can optimize himself well. This study aims to determine the role of Islamic counseling guidance in the formation of children's character in the Al-Qur'an Education Park. This type of research is field research, with the nature of qualitative descriptive research. This study uses interview data collection techniques, observation and documentation. Interviews were conducted with ustadzahs, children, and parents of children who recited the Koran at the Al-Qur'an Education Park. All the data were analyzed deductively. This type of research is field research, with the nature of qualitative descriptive research. This study uses interview data collection techniques, observation and documentation. Based on the results of research on the role of Islamic counseling guidance in the formation of children's character in the Al-Qur'an Education Park, there are Islamic counseling activities in the Al-Qur'an Education Park, one of which is in the form of delivering material. As for the delivery of material related to character, namely commendable and despicable moral material. Likewise, at the beginning of the character of the children who recited the Koran at the Al-Qur'an Education Park, there were children who had negative characters such as being lazy, temperamental, and speaking harshly. Punishment and motivation. Apart from that, in the Al-Qur'an Education Park the ustadzah instill values such as religious and discipline to children who recite the Koran in the Al-Qur'an Education Park which can change the character of children from negative ones to better ones. Activities related to Islamic counseling guidance in the Al-Qur'an Education Park are recitation of the Qur'an, Arabic such as memorizing vocabulary, then short letters, prayer, gymnastics, natural meditation and delivery of material such as monotheism, fiqh, tajwid, reading and writing the Qur'an and morals. Activities related to Islamic extension guidance in the Al-Qur'an Education Park in strengthening character are the delivery of moral material (commendable and despicable). Handling for children who have both positive and negative characters such as exemplary, habituation, advice and punishment. Planting related to character building values such as responsibility, healthy, clean, religious, and discipline.

Ultrathin and porous CoP nanosheets as an efficient electrocatalyst for boosting hydrogen evolution behavior at a broad range of pH

Designing highly-efficient, stable and low-cost catalysts for electrocatalytic hydrogen evolution reaction (HER) plays an important role in renewable energy conversion technology. The particularly ultrathin and porous 2D architecture can provide plentiful activation sites, short delivery channels to improve reaction kinetic and promote HER procedure. High-performance transition metal phosphide (CoP) combined with unique and holey 2D ultrathin nanosheet structure is prepared by successively hydrothermal reaction, oxidation and phosphorization techniques, which presents remarkable stability and electrocatalytic HER properties in a wide pH range. The thickness and pore dimension of ultrathin and porous CoP nanosheets are ∼15 and 3–17 nm. The optimized CoP nanosheets only require 60, 128, 90 mV overpotentials to drive the current density of 10 mA cm−2 in acidic, neutral and alkaline environment, respectively, much better than those of oxide counterpart and the previously reported transition metal-based electrocatalysts. Moreover, the small Tafel slopes of porous CoP nanosheets are 54, 69.9 and 62.9 mV dec−1 in acidic, neutral and alkaline media. CoP nanosheets also exhibit high conductivity, large Cdl, and long-term stability for 20 h in pH-universal electrolyte.

Quality Comparison of Three Metal Additive Manufacturing Technologies on an Automotive Sealant Nozzle

Additive Manufacturing (AM) [1] is playing every day a bigger role in the automotive industry because of its cost competitiveness, short delivery lead times and potential for design flexibility and optimization. Plastics and polymers are the most common materials used to produce AM parts in this sector, however metal AM is increasing its importance as there are specific applications that require mechanical characteristics that can only be achieved with metals such as stainless steel, titanium, hard steel, copper, aluminum, and others. There is an increasing number of metal AM technologies and Original Equipment Manufacturers (OEMs) competing in the industry with a very widespread list of advantages and disadvantages of each of them. We are at a point where automotive manufacturers need to make a complex decision on which metal AM equipment to purchase. This paper describes the main metal AM technologies and highlight the advantages and disadvantages of each of them. Additionally, three of the most competitive Metal AM technologies are compared: Powder Bed Fusion (PBF), Metal Filament Deposition Modeling (MFDM) and Bound Metal Deposition (BMD) on a specific experimental sample. For this study, a very common and representative automotive part has been chosen that is well suited to be printed in metal and can be manufactured in the three chosen technologies. A nozzle from the automotive body plant used to distribute accuratey a sealant bead onto a body panel before the final assembly operation was selected. These sample parts have been trialed for function and evaluated in general terms from a quality point of view. The conclusions included in this paper will help the automotive industry players understand which technology to use for this specific part and other parts with similar characteristics. Additional work will focus on specific quality characteristics such as material composition, mechanical properties, dimensional accuracy, and specific defects found to compare these technologies in detail. Furthermore, a selection of other automotive parts and technologies will be necessary to enlarge the knowledge on the application of metal AM on this field.

Centralized supply chain network optimization with UAV-based last mile deliveries

This paper proposes a centralized supply chain network optimization model that maximizes the total profit obtained by a company that produces and/or outsources production, stores, ships and sells products to customers using a fleet made up of trucks and, in the last mile, also of drones. The model includes realistic features of unmanned aerial vehicles (UAVs) in the form of drones with fundamental limitations such as low battery capacities and short delivery ranges. The constrained nonlinear optimization problem is formulated as a variational inequality. Existence and uniqueness results for the solution of the variational inequality are provided along with the results of detailed numerical simulations that emphasize the advantages of the use of a hybrid fleet from enhanced profits to reduction in air pollution. Our quantitative results reveal great promise and insights for the logistics industry in the use of emerging UAV technologies for last mile parcel deliveries as a practical solution within a holistic supply chain network context.

Short Carbon Nanotube-Based Delivery of mRNA for HIV-1 Vaccines.

Developing a safe and effective preventive for HIV-1 remains the hope for controlling the global AIDS epidemic. Recently, mRNA vaccines have emerged as a promising alternative to conventional vaccine approaches, primarily due to their rapid development and potential for low-cost manufacture. Despite the advantages of mRNA vaccines, challenges remain, especially due to the adverse effects of the delivery vehicle and low delivery efficiency. As a result, Luna Labs is developing a short carbon nanotube-based delivery platform (NanoVac) that can co-deliver mRNA and HIV-1 glycoproteins to the immune system efficiently with negligible toxicity. Surface chemistries of NanoVac were optimized to guide antigen/mRNA loading density and presentation. Multiple formulations were engineered for compatibility with both intramuscular and intranasal administration. NanoVac candidates demonstrated immunogenicity in rabbits and generated human-derived humoral and cellular responses in humanized mice (HIS). Briefly, 33% of the HIV-1-infected HIS mice vaccinated with NanoVac-mRNA was cleared of virus infection by 8-weeks post-infection. Finally, NanoVac stabilized the loaded mRNA against degradation under refrigeration for at least three months, reducing the cold chain burden for vaccine deployment.