Payload Capacity Research Articles

Progress in Zero-gravity Unloading Test and System Research of Solar Wing

Aim: The solar wing undertakes the important task of providing energy for spacecraft. The deployment test of the solar wing in a zero gravity environment using a zero gravity system on the ground is an important link to ensure the safe and stable deployment of the solar wing in space. This article briefly describes the development process and research progress of solar wings, introduces the ground zero gravity test methods and test platforms for solar wings, including some patents for improving the ground zero gravity test platform for solar wings, and points out some urgent problems that need to be solved in the zero gravity unloading test and system at present. Background: The solar wing needs to be deployed in the weightlessness environment of space before working. Objective: The objective of this study is to summarize the zero gravity experimental methods and systems of solar wings, introduce their categories, characteristics, and development. Methods: This article summarizes various scientific research achievements in the zero gravity test of solar wings, and introduces the advantages and disadvantages of the zero gravity test method of solar wings. Conclusion: Although research on zero-gravity unloading test systems for solar wings is continuously advancing, there are still several technological bottlenecks that need to be overcome in terms of system precision, payload capacity, dynamic simulation, method optimization, diversifying zero-gravity test methods and system universality for different types of solar panel unloading.

Multi-Depot Electric Vehicle–Drone Collaborative-Delivery Routing Optimization with Time-Varying Vehicle Travel Time

This paper presents an electric vehicle-drone (EV–drone) collaborative-delivery routing optimization model that leverages the time-varying characteristics of electric vehicles and drones across multiple distribution centers (i.e., central depots) to address the logistics industry’s low-carbon transformation in the last-mile delivery. The model aims to minimize total delivery costs by formulating a mixed-integer programming (MIP) model that accounts for essential constraints such as nonlinear charging time, time-varying EV travel time, delivery time window, payload capacity, and maximum range. An improved adaptive large-neighborhood search (ALNS) algorithm is developed to solve the model. Experimental results validate the effectiveness of the proposed algorithm and highlight the impact of EV and drone technology parameters, along with the time-varying EV travel times, on the economic efficiency of delivery distribution and route planning.

A piezoelectric driven amphibious microrobot capable of fast and controllable movement

Abstract Due to its excellent adaptability to the environment and flexibility in narrow spaces, amphibious microrobots have become an important research direction recently. This study proposes an amphibious microrobot driven by piezoelectric actuators with a body length of 4.5 cm and a mass of 1.4 g. The microrobot consists of two active front legs, two passive rear legs, two caudal fins, and a support frame. Each front leg and each caudal fin are designed as structures integrated with their respective piezoelectric actuators. The microrobot has a tilted body, and the ground exerts an oblique upward impact force that makes it jump forward when its front legs swing backwards. The opposite swing of the two caudal fins generates propulsion for swimming. The components of the microrobot are manufactured based on the monolithic laminate process. The monolithic front actuator-leg and monolithic actuator-fin both emerge from a multi-layer material laminate. The support frame is designed and fabricated as a monolithic structure to improve assembly accuracy and reduce redundant assembly steps. The manufactured microrobot demonstrates its flexible and fast amphibious movements. Its maximum land walking speed reaches 15.3 cm/s and its turning speed reaches 48.2 degrees per second. The microrobot has a maximum payload capacity of 5 g moving on land. When the front legs and caudal fins work simultaneously, its underwater swimming speed reaches 9.1 cm/s, and the maximum turning speed is 20.5 degrees per second. The microrobot also confirms a maximum payload of 3 g during its underwater movement.

Drone Integration in Last-Mile Delivery Operations

Purpose: This research examines the integration of drone technology into last-mile delivery operations, focusing on its impact on supply chain efficiency, cost reduction, and sustainability. The study explores operational challenges, such as air traffic management, payload limitations, regulatory compliance, and public perception, providing a comprehensive understanding of how drones can reshape last-mile logistics. Methodology: The study employs a multi-faceted approach, combining historical analysis, in-depth case studies, and scenario planning to assess the impact of drone technology on last-mile delivery efficiency, cost optimization, and accessibility. Data is gathered from industry reports, interviews with logistics professionals, and regulatory documents. Thematic analysis is conducted to identify critical patterns, while scenario-based modeling offers insight into the potential outcomes of various integration strategies. A comparative evaluation of existing last-mile delivery methods against drone-based delivery models is also provided. Findings: The research reveals that drone technology offers significant potential for enhancing last-mile delivery efficiency, particularly in urban areas and remote locations, aligning with findings from studies like those by Murray & Chu (2015). However, the study identifies considerable obstacles, including regulatory challenges, limited payload capacities, and public acceptance issues. Solutions such as airspace regulation frameworks, collaborative logistics networks, and advanced battery technologies are highlighted as critical enablers for successful drone integration. Contribution to Theory, Policy and Practice: This study contributes to the growing body of knowledge on drone technology's role in logistics by providing a comprehensive framework for businesses and policymakers to navigate the complexities of drone integration. It recommends actionable steps for integrating drones into last-mile delivery, bridging the gap between theoretical innovation and practical application. It provides policy recommendations for regulatory bodies to develop airspace management systems that support drone operations. For practitioners, the research offers a strategic guide to overcoming operational challenges, facilitating the adoption of drones as a sustainable solution for last-mile delivery.

Use of UAVs in Earthquakes and UAV Base Location Selection for a Possible Marmara Earthquake

UAV’s are widely used in many fields today, and one of the most important of these fields is disaster management. The most significant disaster that comes to mind when mentioning disasters is undoubtedly earthquakes. UAV’s are used to support search and rescue operations before and especially after an earthquake. As Türkiye is located in an earthquake zone, earthquakes have affected and will continue to affect us from past to present. The Marmara earthquake, which is predicted to occur in the coming years, will cause great destruction considering the population density of the region. In this study, the use of UAV’s in earthquakes and the selection of the most suitable UAV base location for quick intervention without being affected by a potential Marmara earthquake was conducted using the TOPSIS method, which is one of the multi-criteria decision-making methods with criteria weights. As for the UAV class, MALE class UAV’s, which are produced by Türkiye and classified by NATO, were preferred due to their mission duration and payload capacity. While determining the alternatives, seven airports close to the Marmara region but not on the fault line were selected. The criteria and their weights were determined based on the opinions of five UAV pilots, and a total of six criteria were chosen. As a result of applying the TOPSIS method, Sivrihisar Aviation Center was determined to be the most suitable UAV base for intervention in a potential Marmara earthquake, being the closest to the ideal solution among the selected alternatives.

A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots

This paper aims to elucidate the state-of-the-art, prevailing priorities, and the focus of the industry, and identify both limitations and potential gaps regarding industrial robots and collaborative robots (cobots). Additionally, it outlines the advantages and disadvantages of cobots compared to traditional industrial robots. Furthermore, three novel factors are introduced in this survey as metrics to evaluate the efficiency and performance of industrial robots and cobots. To achieve these purposes, a statistical analysis and review of commercial articulated industrial robots and cobots are conducted based on their documented specifications, such as maximum payload, weight, reach, repeatability, average maximum angular speed, and degrees of freedom (DOF). Additionally, the statistical distributions of the efficiency factors are investigated to develop a systematic method for robot selection. Finally, specifications exhibiting strong correlations are compared in pairs using regressions to find out trends and relations between them, within each company and across them all. The investigation of the distribution of specifications demonstrates that the focus of the industry and robot makers is mostly on articulated industrial robots and cobots with higher reach, lower payload capacity, lower weight, better repeatability, lower angular speed, and six degrees of freedom. The regressions reveal that the weight of robots increases exponentially as the reach increases, primarily due to the added weight and torque resulting from the extended reach. They also indicate that the angular speed of robots linearly decreases with increasing reach, as robot manufacturers intentionally reduce the angular speed through reductive gearboxes to compensate for the additional torque required as the reach extends. The trends obtained from the regressions explain the reasons behind these interrelationships, the design purpose of robot makers, and the limitations of industrial robots and cobots. Additionally, they help industries predict the dependent specifications of articulated robots based on the specifications they require. Moreover, an accompanying program has been developed and uploaded on to GitHub, taking the required specifications and returning a list of proper and efficient robots sourced from different companies according to the aforementioned selection method.

PVA-Stabilized and Coassembled Nano/Microparticles with High Payload of Dual Phytochemicals for Enhanced Antibacterial and Targeting Effect.

The codelivery of multiple bioactive phytochemicals via nano/microparticles (NPs/MPs) represents a promising strategy for enhancing therapeutic efficacy. This study presents the development of novel poly(vinyl alcohol) (PVA)-stabilized hybrid particles designed for codelivery of palmatine hydrochloride (PAL) and glycyrrhizic acid (GL). Employing a straightforward coassembly method, we synthesized dual-drug particles achieving a high payload capacity of over 70%. The particles were characterized as uniform in size, within the nano/micron range, and exhibited a ζ-potential of -5.0 mV. The incorporation of PVA not only stabilized the particles but also refined the aggregation process, resulting in more uniform and finer particles approximately 1 μm in size. Spectral analysis and molecular dynamics simulations verified the presence of π-π stacking and hydrogen bonding between PAL and GL within the particles. In vitro antibacterial assays indicated that the hybrid particles had a lower minimum inhibitory concentration against Escherichia coli and Multidrug-Resistant Staphylococcus aureus than those of the pure drugs. In vivo biodistribution study in rats revealed that the PVA-stabilized particles revealed enhanced targeting to the liver, lung, and heart, demonstrating improved tissue selectivity compared with the solution group. In summary, the PVA-stabilized hybrid NPs/MPs represent an innovative and efficient platform for codelivery of multidrugs. These findings highlight the promise of coassembled particles for high loading, enhanced bioactivity, and targeted delivery, making them a strong candidate for future clinical applications.

Structure-guided engineering of type I-F CASTs for targeted gene insertion in human cells.

Conventional genome editing tools rely on DNA double-strand breaks (DSBs) and host recombination proteins to achieve large insertions, resulting in a heterogeneous mixture of undesirable editing outcomes. We recently leveraged a type I-F CRISPR-associated transposase (CAST) from the Pseudoalteromonas Tn7016 transposon (PseCAST) for DSB-free, RNA-guided DNA integration in human cells, taking advantage of its programmability and large payload capacity. PseCAST is the only characterized CAST system that has achieved human genomic DNA insertions, but multiple lines of evidence suggest that DNA binding may be a critical bottleneck that limits high-efficiency activity. Here we report structural determinants of target DNA recognition by the PseCAST QCascade complex using single-particle cryogenic electron microscopy (cryoEM), which revealed novel subtype-specific interactions and RNA-DNA heteroduplex features. By combining our structural data with target DNA library screens and rationally engineered protein mutations, we uncovered CAST variants that exhibit increased integration efficiency and modified PAM stringency. Structure predictions of key interfaces in the transpososome holoenzyme also revealed opportunities for the design of hybrid CASTs, which we leveraged to build chimeric systems that combine high-activity DNA binding and DNA integration modules. Collectively, our work provides unique structural insights into type I-F CAST systems while showcasing multiple diverse strategies to investigate and engineer new RNA-guided transposase architectures for human genome editing applications.

Development of a bionic hexapod robot with adaptive gait and clearance for enhanced agricultural field scouting.

High agility, maneuverability, and payload capacity, combined with small footprints, make legged robots well-suited for precision agriculture applications. In this study, we introduce a novel bionic hexapod robot designed for agricultural applications to address the limitations of traditional wheeled and aerial robots. The robot features a terrain-adaptive gait and adjustable clearance to ensure stability and robustness over various terrains and obstacles. Equipped with a high-precision Inertial Measurement Unit (IMU), the robot is able to monitor its attitude in real time to maintain balance. To enhance obstacle detection and self-navigation capabilities, we have designed an advanced version of the robot equipped with an optional advanced sensing system. This advanced version includes LiDAR, stereo cameras, and distance sensors to enable obstacle detection and self-navigation capabilities. We have tested the standard version of the robot under different ground conditions, including hard concrete floors, rugged grass, slopes, and uneven field with obstacles. The robot maintains good stability with pitch angle fluctuations ranging from -11.5° to 8.6° in all conditions and can walk on slopes with gradients up to 17°. These trials demonstrated the robot's adaptability to complex field environments and validated its ability to maintain stability and efficiency. In addition, the terrain-adaptive algorithm is more energy efficient than traditional obstacle avoidance algorithms, reducing energy consumption by 14.4% for each obstacle crossed. Combined with its flexible and lightweight design, our robot shows significant potential in improving agricultural practices by increasing efficiency, lowering labor costs, and enhancing sustainability. In our future work, we will further develop the robot's energy efficiency, durability in various environmental conditions, and compatibility with different crops and farming methods.

Centralized multi-robot logistic system: An approach using the island model genetic algorithm as task scheduler

The practicality allied with technological and logistical advances led customers increasingly to join e-commerce. This phenomenon was even more expanded during the COVID-19 pandemic. Because of the growing demand for logistic services, warehouses must adapt and seek faster and more efficient processes. A means to achieve that is to use mobile robots in transportation-related tasks. However, their effectiveness is only achieved if the system has an efficient work distributor. This research developed a centralized coordination architecture using the island model genetic algorithm for multi-robot logistic task allocation. The coordination receives, allocates, and monitors tasks performed by robots with different payload capacities and average speeds. The architecture was developed upon the robotic operating system. Thus, any robot with a robotic operating system-based internal system can work under the coordination of this architecture. On the results, the task scheduler, developed in previous work, had the evaluation complemented. The scheduler based on the island model genetic algorithm allocates more tasks than the standard genetic algorithm when using the same heuristic. Regarding coordination architecture, the system successfully managed a group of robots in a simulated environment. It also detected and notified failures during task execution. Therefore, this system provides a complete task scheduling, allocation, and monitoring solution.

Nanosatellite Design Considerations for a Mission to Explore the Propellant Sloshing Problem

Sloshing Platform for In-Orbit Controller Experimentation is an ambitious, student run mission to design and fly a cubesat to study fluid sloshing in spacecraft. The project will examine zero-g propellant sloshing from an experimental standpoint. Despite the small size and limited payload capacity, we intend to use the cubesat platform to mimic larger spacecraft and implement novel detection and computer vision methods in our analysis. Many modern spacecraft rely on propellant-filled tanks to perform attitude control and station-keeping maneuvers. When a large percentage of the spacecraft’s mass is comprised of liquid propellant, sloshing becomes a critical aspect of spacecraft attitude control and stability. The mission will study the tank/fluid dynamics using new methods to gain an enhanced understanding of low-gravity fluid disturbance effects and improve simulations using equivalent mechanical models (EMMs). Active control of the fluid leading to the reduction of propellant slosh settling times will improve the maneuverability and performance of spacecraft. This paper will focus on satellite payload research and design requirements used to inform other aspects of the SPICEsat design. In this paper, mission objectives will be discussed, numerical simulations for the proposed control algorithms are demonstrated, and a satellite experiment design is presented. Finally, we examine computational fluid dynamics models to validate the satellite design and propellant sensing components of the proposed spacecraft.

Stratospheric airship trajectory planning in wind field using deep reinforcement learning

Stratospheric airships, with their long endurance, high flight altitude, and large payload capacity, show promise in earth observation and mobile internet applications. However, challenges arise due to their low flight speed, limited maneuverability and energy constraints when planning trajectories in dynamic wind fields. This paper proposes a deep reinforcement learning-based method for trajectory planning of stratospheric airships. The model considers the motion characteristics of stratospheric airships and environmental factors like wind fields and solar radiation. The soft actor-critic (SAC) algorithm is utilized to assess the effectiveness of the method in various scenarios. A comparison between time-optimized and energy-optimized trajectories reveals that time-optimized trajectories are smoother with a higher speed, while energy-optimized trajectories can save up to 10% energy by utilizing wind fields and solar energy absorption. Overall, the deep reinforcement learning approach proves effective in trajectory planning for stratospheric airships in deterministic and dynamic wind fields, offering valuable insights for flight design and optimization.

Formulation Strategy and An Overview of Nano-Structured Lipid Carrier-Based Topical Gel as a Novel Drug Delivery System.

Nano-Structured Lipid Carriers (NLCs) are improved Solid Lipid Nanoparticles (SLNs) that recover the permanency and capacity of drug payload. There are 3 different types of NLCs which have been anticipated. The aforementioned Lipid Nano Particles (LNPs) possess possible tenders in drug delivery systems, cosmeceuticals, clinical research and many others. Here, we highlight the structure, ingredients, different manufacturing techniques and analysis of NLCs which are rudiments in formulating a unique drug delivery system. These types of formulations are therapeutically advantageous like skin hydration, occlusion and improved bioavailability as well as skin targeting. In this article, we have also discussed the features, and novelty of NLCs, different advantages as promising assistance in topical drug delivery systems, shortcomings and utilisations of LNPs by concentrating on NLCs.

The Synergistic Potential of Hydrogel Microneedles and Nanomaterials: Breaking Barriers in Transdermal Therapy.

The stratum corneum, which acts as a strong barrier against external agents, presents a significant challenge to transdermal drug delivery. In this regard, microneedle (MN) patches, designed as modern systems for drug delivery via permeation through the skin with the ability to pass through the stratum corneum, are known to be convenient, painless, and effective. In fact, MN have shown significant breakthroughs in transdermal drug delivery, and among the various types, hydrogel MN (HMNs) have demonstrated desirable inherent properties. Despite advancements, issues such as limited loading capacity, uncontrolled drug release rates, and non-uniform therapeutic approaches persist. Conversely, nanomaterials (NMs) have shown significant promise in medical applications, however, their efficacy and applicability are constrained by challenges including poor stability, low bioavailability, limited payload capacity, and rapid clearance by the immune system. Incorporation of NMs within HMNs offers new prospects to address the challenges associated with HMNs and NMs. This combination can provide a promising field of research for improved and effective delivery of therapeutic agents and mitigate certain adverse effects, addressing current clinical concerns. The current review highlights the use of NMs in HMNs for various therapeutic and diagnostic applications.

Property investigation of functionally graded materials leaf spring plate fabricated through stir casting process by using new gradient evaluation method

AbstractAutomobile and aviation industries require lightweight solutions in the suspension system to improve overall performance and payload capacity. This can be achieved by materials having high strength to weight ratio. Fiber composites, known for their lightweight and high strength, face a major issue of delamination, which shortens the lifespan of fiber‐reinforced polymer leaf springs. Current researchers are emphasizing the use of functionally graded materials as a promising alternative to tackle this problem. In the present work, a functionally graded leaf spring plate was fabricated using stir casting technique with five layered gradations in the mid portion. The amount of molten material required for each gradation was ensured using a novel experimental technique. On the other hand, the matrix and reinforcement have been adopted from the output of the analysis conducted using CES EduPack 2019 software. Low density and high fatigue strength were primary focal point for the consideration of matrix and reinforcement materials. Aluminium 7075 and boron carbide were considered as matrix and reinforcement materials respectively. Stir casting technique, used in the present work, is simple, suitable and cost effective technique which creates a gradation at central part of the leaf.

Strategic Developments in Polymer-Functionalized Liposomes for Targeted Colon Cancer Therapy: An Updated Review of Clinical Trial Data and Future Horizons.

Liposomes, made up of phospholipid bilayers, are efficient nanocarriers for drug delivery because they can encapsulate both hydrophilic and lipophilic drugs. Conventional cancer treatments sometimes involve considerable toxicities and adverse drug reactions (ADRs), which limits their clinical value. Despite liposomes' promise in addressing these concerns, clinical trials have revealed significant limitations, including stability, targeted distribution, and scaling challenges. Recent clinical trials have focused on enhancing liposome formulations to increase therapeutic efficacy while minimizing negative effects. Notably, the approval of liposomal medications like Doxil demonstrates their potential in cancer treatment. However, the intricacy of liposome preparation and the requirement for comprehensive regulatory approval remain substantial impediments. Current clinical trial updates show continued efforts to improve liposome stability, targeting mechanisms, and payload capacity in order to address these issues. The future of liposomal drug delivery in cancer therapy depends on addressing these challenges in order to provide patients with more effective and safer treatment alternatives.

Image-to-Image Steganography with Josephus Permutation and Least Significant Bit (LSB) 3-3-2 Embedding

In digital image security, the Josephus permutation is widely used in cryptography to enhance randomness. However, its application in steganography is underexplored. This study introduces a novel method integrating the Josephus permutation into the LSB 3-3-2 embedding technique for image steganography. This approach improves the randomness of the keystream generated by the chaotic logistic map, addressing vulnerabilities in basic logistic maps susceptible to steganalysis. Our algorithm is tested on RGB images as secret data, presenting higher complexity compared to grayscale images used in previous studies. Comparative analysis shows that the proposed algorithm offers higher payload capacity while maintaining image quality, outperforming traditional LSB techniques. This research advances the field of image steganography by demonstrating the effectiveness of the Josephus permutation in creating more secure and robust steganographic images.

Conceptual design and analysis of a box fan-in-split-wing tiltrotor eVTOL aircraft

PurposeWith the advancements in electric vertical take-off and landing (eVTOL) aircraft technology such as batteries, mechanisms, motors, configurations and so on, designers and engineers are encouraged to create unique and unconventional configurations of eVTOL aircraft to provide better capabilities and higher efficiencies to compete in the market. The box fan-in-split-wing tiltrotor eVTOL aircraft is an innovative design that aims to address the aerodynamic inefficiencies such as propeller effects in cruise and engine mounts drag that existed in traditional eVTOL aircraft designs such as vectored thrust, rotorcraft, lift + cruise and multi-copter configurations. This paper aims to propose a multi-disciplinary design process to conceptually design the box fan-in-split-wing Tiltrotor eVTOL aircraft.Design/methodology/approachAn unconventional methodology was used to design the UAM aircraft, and the following parameters are considered: capable of vertical take-off and landing, highly aerodynamic with a high lift-to-drag ratio, low Cd0 modern and appealing, rechargeable or battery swappable and feature to minimise or negate propeller drag. A heavy emphasis on improving performance and weight based on aerodynamics was enforced during the conceptual design phase. MAPLA and XFOIL were used to identify the aerodynamic properties of the aircraft.FindingsUpon determining the key parameters and the mission requirements and objectives, a list of possible VTOL configurations was derived from theoretical and existing designs. The fan in the wing/split wing was selected, as it could stow the propellers. A tiltrotor configuration was selected because of its ability to reduce the total number of lift props/motors, reducing powerplant weight and improving aerodynamic efficiency. For the propulsion configuration, a battery–motor configuration with a hexa-rotor layout was chosen because of its ability to complement the planform of the aircraft, providing redundant motors in case of failure and because of its reliability, efficiency and lack of emissions. Coupled with the fan-in-wing / split wing concept, the box wing seamlessly combines all chosen configurations.Originality/valueThe box fan-in-split-wing Tiltrotor eVTOL aircraft aims to address the aerodynamic inefficiencies of earlier designs such as propeller effects in cruise and engine mounts drag. The potential benefits of this aircraft, such as increased range, endurance and payload capacity, make it an exciting prospect in the field of Urban Air Mobility.

Real-World Emission Characteristics of Diesel Pallet Trucks under Varying Loads: Using the Example of China

Diesel pallet trucks, a type of heavy-duty diesel trucks (HDDTs), have historically been a vital component in logistics and transport due to their high payload capacity. However, they also present significant challenges, particularly in terms of emissions which contribute substantially to urban air pollution. Traditional HDDTs emission measurement methods, such as engine bench tests and those used in laboratory settings, often fail to capture real-world emission behaviors accurately. This study specifically examines the real-world emission characteristics of diesel pallet trucks exceeding 30 t under varying loads (unloaded, half loaded, and fully loaded) and different road conditions (urban, suburban, and high-speed). Considering that data quality is the key to the accuracy of the scheme, this research utilized a portable emission measurement system (PEMS) to capture real-time emissions data of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOX), and total hydrocarbons (THC). Key findings demonstrate a direct correlation between vehicle load and emission factors, with the emission factors for CO2, CO, and NOX increasing by 39.5%, 105.4%, and 22.7%, respectively, from unloaded to fully loaded states under comprehensive operating conditions. Regression analyses further provide an emission factor prediction model for HDDPTs, underscoring the continuous relationship between speed, load, and emission rates. These findings provide a scientific basis for pollution control strategies for diesel trucks.

A novel approach for the enhancement of payload capacity in pixel value differencing image steganography schemes

A novel approach for the enhancement of payload capacity in pixel value differencing image steganography schemes