Small Payloads Research Articles

A trade-off methodology for micro-launchers

The trend of cost-effective access to space and satellite technologies’ evolution is increasing the small satellite market. However, small payloads usually ride as piggyback, being a secondary passenger of a space vector, with very low flexibility in target orbit and launch schedule. The micro-launchers are designed to answer the needs of the small satellite missions, with a payload capacity up to 350 kg to Low Earth Orbit, aiming to low turn-over time and competitive prices. This paper explains the work performed by Politecnico di Torino in support of the ESA–ESTEC activities on micro-launchers. The aim is to provide preliminary guidelines for choosing and evaluating new innovative micro-launcher flight vehicle engineering processes. A trade-off methodology is proposed and defined based on the Analytically Hierarchical Process (AHP). This methodology considers, among other features, the flight profile, maximum payload, and physical characteristics. To support the trade-off analysis, a software tool is built for the automatic generation of the aerodynamics and propulsion parameters needed for the completion of the preliminary designs, enabling the performance estimation. The launcher’s performance models, with an analysis of the take-off sites and target orbits, are also produced. This allows the definition of performance maps where the maximum payload is graphed as a function of the orbit altitude and inclination. A set of innovative micro-launchers exploiting different technologies is also assessed as a case study.

Design Optimization and Parameter Analysis of a Hybrid Rocket Motor-Powered Small LEO Launch Vehicle

In this paper, the effects of different grain shapes of a hybrid rocket motor (HRM) and different payload mass/orbit heights on the design of small launch vehicles (SLVs) are systematically discussed. An integrated overall design model for the hybrid rocket motor-powered small launch vehicle (HPSLV) is established, and two groups of three-stage SLVs capable of sending small payloads to the low earth orbit (LEO) are designed and optimized. In the first group, the SLVs with different grain shapes and different numbers of chambers in HRMs at the 1st and the 2nd stages are optimized and analyzed. In the second group, the SLVs capable of sending different payload mass to different orbit heights are optimized and analyzed. Pareto graphs of the design results show that the design of HRM at the 1st stage has the greatest impact on the take-off mass, total velocity increment, and maximum axial overload of the SLV. Self-organizing maps show that the take-off mass, maximum diameter, overall length, and velocity increment of the SLVs have the same variation tendency. For the 1-chamber HRM at the 1st stage, the wheel-shaped grain is better than circle-shaped and star-shaped grains in terms of reducing the total mass and length of the SLV, and the 4-chamber parallel HRM has more advantages over all 1-chamber designs for the same reason. The theoretical velocity increments are calculated by the Tsiolkovsky formula, and the actual velocity increments are obtained based on the trajectory simulation data. The results indicate that the HPSLV has a regular distribution in terms of the ratio of theoretical (actual) velocity increments at three different stages, and the estimated distribution ratio is around 1 : 1.55 : 1.69 (1 : 1.9 : 2.39), which can provide some reference for future development of HPSLV.

Robust observer-based anti-swing control of 2D-crane systems with load hoisting-lowering

A new model-free robust control scheme for payload swing angle attenuation of two-dimensional crane systems with varying rope length is introduced in this work. The proposed controller consists of a proportional derivative controller, a disturbance observer, and a compensation term that includes a coupling function. A proper design of the coupling function allows attenuating the magnitude of the swing angle, while the disturbance observer permits reducing the effect of internal and external disturbances. Then, a rigorous stability analysis demonstrates that the proposed controller allows the system to follow a desired translational motion and hoisting/lowering the load with small payload oscillations despite the adverse effects caused by internal and external disturbances. In the proposed scheme, a stage devoted to the design of the reference signal is also encompassed. The new methodology is compared to a robust controller and an adaptive scheme. Exhaustive numerical simulations demonstrate that the new controller’s performance outperforms the other control techniques, despite the presence of endogenous and exogenous disturbances.

Equity Is Key to Build Back Better after COVID-19: Prioritize Noncommunicable Diseases and Kidney Health.

<h3>ABSTRACT</h3> Among the major classes of RNAs in the cell, tRNAs remain the most difficult to characterize via deep sequencing approaches, as tRNA secondary structure and nucleotide modifications can both interfere with cDNA synthesis by commonly-used reverse transcriptases (RTs). Here, we benchmark a recently-developed RNA cloning protocol, termed Ordered Two-Template Relay (OTTR), to characterize intact tRNAs and tRNA fragments in budding yeast and in mouse tissues. We find that OTTR robustly captures full-length tRNAs in budding yeast and in mouse testis, with relatively low levels of premature termination at known barriers – 1-methylguanine, N2,N2-dimethylguanine, and 1-methyladenine – to typical reverse transcriptases. Moreover, these and several other nucleotide modifications leave misincorporation signatures in OTTR datasets which enables their detection without any additional protocol steps. Turning to analysis of small RNAs such as tRNA cleavage products, we compare OTTR with several standard small RNA-Seq protocols, finding that OTTR provides the most accurate picture of tRNA fragment levels by comparison to “ground truth” Northern blots. Applying this protocol to mature mouse spermatozoa, our data dramatically alter our understanding of the small RNA cargo of mature mammalian sperm, revealing a far more complex population of tRFs – including both 5’ and 3’ tRNA halves derived from the majority of tRNAs – than previously appreciated. Taken together, our data confirm the superior performance of OTTR to commercial protocols in analysis of tRNA fragments, and force a reappraisal of potential epigenetic functions of the sperm small RNA payload.

Metal-organic frameworks for simultaneous gene and small molecule delivery in vitro and in vivo

Nanoparticles based on metal–organic frameworks (nMOF) became one of the most promising class of drug delivery vehicles due to their ability to transport a great range of payloads, high capacity, tunable release, and the potential to simultaneously transport several different payloads to achieve synergistic therapeutic effect. However, despite the significant progress with small molecule payloads (including siRNA), delivery of functional genes has been greatly limited. Here, we show the first nanoscale modified MOFs (modMOF) that allow: i) co-delivery of a transgene and a drug-like molecule; ii) in vivo gene delivery and expression. The multimodal modMOFs are fabricated via growing of the metal–organic framework shell on top of the magnetic core and then surface-modified with multiple polymers that do not inhibit incorporation of the small-molecule payload inside the particle and allow further binding of the plasmid DNA. Such structure allows efficient transfection by the plasmid DNA of virtually any size while fully retaining the superior small-molecule transport capacity of the MOF shell. The magnetic core offers additional functionality to the agent including capability for the highly accurate tracking in vivo. Performance of the agents is demonstrated in vitro for different cell lines and in vivo upon intravenous injection of the agents in mice. Expression of the target protein in lungs supplemented with the slow diffuse release of the small molecule payload suggests that the developed modMOF synthesis strategy may offer novel routes for lung disease treatment based on co-targeting of multiple signaling pathways.

Brain penetrating peptides and peptide-drug conjugates to overcome the blood-brain barrier and target CNS diseases.

Nearly one in six people worldwide suffer from disorders of the central nervous system (CNS). There is an urgent need for effective strategies to improve the success rates in CNS drug discovery and development. The lack of effective technologies for delivering drugs and genes to the brain due to the blood-brain barrier (BBB), a structural barrier that effectively blocks most neurotherapeutic agents from reaching the brain, has posed a formidable hurdle for CNS drug development. Brain-homing and brain-penetrating molecular transport vectors, such as brain permeable peptides or BBB shuttle peptides, have shown promise in overcoming the BBB and ferrying the drug molecules to the brain. The BBB shuttle peptides are discovered by phage display technology or derived from natural neurotropic proteins or certain viruses and harness the receptor-mediated transcytosis molecular machinery for crossing the BBB. Brain permeable peptide-drug conjugates (PDCs), composed of BBB shuttle peptides, linkers, and drug molecules, have emerged as a promising CNS drug delivery system by taking advantage of the endogenous transcytosis mechanism and tricking the brain into allowing these bioactive molecules to pass the BBB. Here, we examine the latest development of brain-penetrating peptide shuttles and brain-permeable PDCs as molecular vectors to deliver small molecule drug payloads across the BBB to reach brain parenchyma. Emerging knowledge of the contribution of the peptides and their specific receptors expressed on the brain endothelial cells, choice of drug payloads, the design of PDCs, brain entry mechanisms, and delivery efficiency to the brain are highlighted. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease.

Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware

Windows malware detectors based on machine learning are vulnerable to adversarial examples, even if the attacker is only given black-box query access to the model. The main drawback of these attacks is that: (i) they are query-inefficient, as they rely on iteratively applying random transformations to the input malware; and (ii) they may also require executing the adversarial malware in a sandbox at each iteration of the optimization process, to ensure that its intrusive functionality is preserved. In this paper, we overcome these issues by presenting a novel family of black-box attacks that are both query-efficient and functionality-preserving, as they rely on the injection of benign content - which will never be executed - either at the end of the malicious file, or within some newly-created sections. Our attacks are formalized as a constrained minimization problem which also enables optimizing the trade-off between the probability of evading detection and the size of the injected payload. We empirically investigate this trade-off on two popular static Windows malware detectors, and show that our black-box attacks can bypass them with only few queries and small payloads, even when they only return the predicted labels. We also evaluate whether our attacks transfer to other commercial antivirus solutions, and surprisingly find that they can evade, on average, more than 12 commercial antivirus engines. We conclude by discussing the limitations of our approach, and its possible future extensions to target malware classifiers based on dynamic analysis.

Applicability of Iodine as a propellant for hall Effect thrusters: Performance parameters prediction

In deep space missions with smaller payloads, electric propulsion is one of the most preferred propulsion techniques. Electric propulsion possesses the advantages of prolonged mission span and a very high specific impulse (Isp). However, the complexity lies in determining the suitable propellant for the electric propulsion-based systems viz., Hall effect thrusters (HET). The present paper reports the approach suitable for 6U CubeSat to utilize Iodine as a potential alternate fuel. The study focuses on computational simulation using the commercial package ANSYS FLUENT 18. A Hall effect thruster simulation is carried out using MHD module in fluent, wherein effect of power supplies were studied by varying the voltage supply of 200 V and 300 V. It is observed that Iodine propellant with the HET configuration delivers Isp of 2650 s and thrust ∼ 37.5 (mN) in the STP at 600 W, and Isp of 4565 s followed by thrust ∼ 27.5 (mN) in STP at 400 W. The simulation is carried out by assuming the plasma fluid model and serves as the base for the earlier stage development of experimental techniques.

Research Flights on Blue Origin's New Shepard

Abstract Blue Origin's New Shepard launch vehicle made its first flight above the Kármán Line, returning safely to Earth in November 2015. At the time when this paper is being written (February 2021), the system has conducted 14 flights, including 10 with research and education payloads aboard. More than 100 payloads have exercised a wide range of capabilities and interfaces, from small cubesat-form factor student payloads to large custom payloads of nearly 100 kg. Investigations have spanned a wide range of high-altitude and microgravity research objectives, as well as raising technology readiness level (TRL) on diverse hardware. This paper summarizes New Shepard's payload missions to date, and presents standardized and custom accommodations, both in the shirtsleeve cabin and directly exposed to the space environment.

Steganalysis of low stego-payload color images using software complex

In the paper, a new software package is presented as a tool that allows to conduct steganalysis of color images and reveal embedded messages such as LSB inserts or Koha-Zhao inserts. The complex combines two algorithms previously developed by the authors and is highly effective even for small stegocontainer payload (10–30 %). The computer experiment results and a comparison of the software package and some other models performance are presented and discussed.”.

Co-administered antibody improves penetration of antibody\u2013dye conjugate into human cancers with implications for antibody\u2013drug conjugates

Poor tissue penetration remains a major challenge for antibody-based therapeutics of solid tumors, but proper dosing can improve the tissue penetration and thus therapeutic efficacy of these biologics. Due to dose-limiting toxicity of the small molecule payload, antibody-drug conjugates (ADCs) are administered at a much lower dose than their parent antibodies, which further reduces tissue penetration. We conducted an early-phase clinical trial (NCT02415881) and previously reported the safety of an antibody-dye conjugate (panitumumab-IRDye800CW) as primary outcome. Here, we report a retrospective exploratory analysis of the trial to evaluate whether co-administration of an unconjugated antibody could improve the intratumoral distribution of the antibody-dye conjugate in patients. By measuring the multiscale distribution of the antibody-dye conjugate, this study demonstrates improved microscopic antibody distribution without increasing uptake (toxicity) in healthy tissue when co-administered with the parent antibody, supporting further clinical investigation of the co-administration dosing strategy to improve the tumor penetration of ADCs.

Role of Unmanned Aerial Systems for Natural Resource Management

Natural resources management (NRM) is an important application of satellite remote sensing. The need for cost-effective, accurate, demand-based high-resolution data for natural resources management is growing in developing countries. However, the higher cost of satellite data, limitations of temporal and spatial resolution are the biggest hurdle for continuous monitoring of the dynamics of natural resources, i.e. agriculture, forest, water and land resources. Due to these limitations, unmanned aerial system (UAS)-based remote sensing studies for natural resource management are rapidly growing, as it offers several advantages, i.e. flexibility, efficiency, easy operation, higher spatial resolution, multispectral resolution and cost-effectiveness over high-resolution satellite data. The role of UAS is optimal in remote areas for mapping and monitoring. The constantly improving technology of UAS has led to several advantages over satellite data, however; some challenges remain the same as the main focus of UAS developers is to reduce the cost and payload weight. The challenges include poor radiometric and geometric performance, small payload, large dataset, data processing, regulation and restrictions. The application of UAS is still in its initial phase; however, its ability to produce application-specific data at relatively lower cost has proved that UAS has a great potential for natural resources management. Based on the existing literature, this study is an attempt to evaluate the current status of the use of UAS for NRM along with its major strength, opportunity, weakness, threats and future perspective.

Massive connectivity with machine learning for the Internet of Things

Driven by the need to ensure the connectivity of an unprecedentedly huge number of IoT devices with no human intervention the issues of massive connectivity have recently become one of the main research areas in IoT studies. Conventional wireless communication technologies are designed for Human-to-Human (H2H) communication which leads to major problems in primary access, channel utilization and spectrum efficiency when massive numbers of devices require connectivity. Current random access procedures are based on a four-step handshaking with control messages which contradicts the requirements of IoT applications in terms of small data payloads and low complexity. Targeted channel utilization and spectrum efficiency cannot be achieved using traditional orthogonal approaches. Thus the goal of our work is to review the most recent developments and critically evaluate the existing work related to the evolution of network access methods in the new communication era. The paper covers three major aspects: first the primary random access procedures, proposed for IoT communications are discussed. The second aspect focuses on the approaches for integration of existing random multiple access schemes with non-orthogonal multiple access methods (NOMA). This integration of random access procedures with NOMA opens a new research trend in the field of massive connectivity. Operating on space domains additional to the physical domain such as code and power domains, NOMA integration targets increased channel utilization and spectrum efficiency to complement the flexibility of random access. On the other hand, the design of efficient algorithms for massive connectivity in IoT is also challenged by the highly application and environmentally dependent traffic model. A new angle of tackling this problem has emerged thanks to the extensive developments in machine learning and the possibilities of their incorporation in communication networks. Thus, the final aspect this review paper addresses are the newly emerging research directions of incorporating machine learning (ML) methods for providing efficient IoT connectivity. Breakthrough ML techniques allow wireless networking devices to perform transmissions by learning and building knowledge about the communication and networking environment. A critical evaluation of the large body of work accumulated in this area in the most recent years and outlining of some major open research issues concludes the paper.

On the Multiplexing of Data and Metadata for Ultra-Reliable Low-Latency Communications in 5G

This paper addresses the problem of downlink radio resource management for ultra-reliable low-latency communications (URLLC) in fifth generation (5G) systems. To support low-latency communications, we study performance of two multiplexing schemes namely in-resource control signalling and joint encoding of data and metadata . In the former, the metadata and data are separately encoded and the metadata is sent at the beginning of transmission time prior to the data. Thus, it benefits from a low-complexity receiver structure to decode the data block. The latter takes advantages of transmitting a larger blocklength to enhance the reliability and improve spectrum efficiency by jointly encoding data and metadata as a single codeword. Dealing with small URLLC payloads, the overhead and error of sending metadata are not negligible and have a significant impact on the system performance in terms of resource usage the reliability of transmission. For each scheme, we derive expressions for the outage probability and resource usage by taking into account impacts of the finite blocklength payloads, overhead and error of sending metadata, and probability of error in uplink feedback channel. We propose a novel framework for joint data and metadata link adaptation to minimize the average number of allocated resources, while ensuring the stringent URLLC quality of service requirements. An optimization problem is formulated for each scheme that is mixed-integer non-convex problem, difficult to solve in polynomial time. Solutions based on successive convex optimization are proposed. Numerical evaluations show that the proposed algorithms perform close to the optimal solution and demonstrate remarkable gains of up to $\mathbf {27\%}$ improvement in resource usage. Finally, we present sensitivity analysis of the results for various network parameters.

Revolving Codes: Overhead and Computational Complexity Analysis

Revolving codes (ReC) are a new family of network codes that reduce signaling overhead and maintain high decoding probability, which is key in applications with small payloads, e.g., IoT, Industry 4.0. However, they have only been studied using simulations. We present i) the first exact mathematical model for the total overhead and decoding probability of a set of ReCs, and ii) efficient encoders and decoders. Our analysis shows that ReC decoders' number of multiplications scales as O(g) where g is the number of data packets being combined. In practice, this translates in several orders of magnitude fewer multiplications, half the number of additions, and lower transmission overheads compared to RLNC.

Sortase-Mediated Site-Specific Modification of Interleukin-2 for the Generation of a Tumor-Targeting Acetazolamide-Cytokine Conjugate.

Small ligands specific to tumor-associated antigens can be used as alternatives to antibodies for the delivery of small payloads such as radionuclides, cytotoxic drugs, and fluorophores. Their use as a delivery moiety of bioactive proteins such as cytokines remains largely unexplored. Here, we describe the preparation and in vivo characterization of the first small molecule–cytokine conjugate targeting carbonic anhydrase IX (CAIX), a marker of renal cell carcinoma and hypoxia. Site-specific conjugation between interleukin-2 and acetazolamide was obtained by sortase A-mediated transpeptidation. Binding of the conjugate to the cognate CAIX antigen was confirmed by surface plasmon resonance. The in vivo targeting of structures expressing carbonic anhydrase IX was assessed by biodistribution experiments in tumor-bearing mice. Optimization of manufacturability and tumor-targeting performance of acetazolamide–cytokine products will be required in order to enable industrial applications.

A High-Assay Low-Enriched Uranium Fuel Transportation Concept

The uranium 235U enrichment commonly used in fuel production for U.S. light water nuclear reactors typically does not exceed 5 wt%. In contrast, many of the currently investigated advanced reactor concepts demand fuel with higher enrichments. This includes high-assay low-enriched uranium (HALEU), characterized by a 235U enrichment of 5 to 20 wt%. The necessity of HALEU transportation in the fuel production cycle leads to new challenges caused by various technical and regulatory hurdles. Current U.S. Nuclear Regulatory Commission–approved transportation package designs for UF6 with enrichments above 5 wt% provide relatively small payloads [≤116 kg (250 lb)]. Furthermore, in accordance with 10 CFR 71.55, package design activities for fissile material enriched above 5 wt% need to consider water infiltration in the containment as part of the criticality safety evaluations. This study presents a transportation package concept for HALEU advanced nuclear reactor fuel with a significantly higher payload of up to 376 kg (830 lb) of fissile material per package and up to 1881 kg (4149 lb) of HALEU per legal weight truck. The anticipated chemical form of the transported material is UO2 downblended from available highly enriched uranium. The concept utilizes a combination of existing transportation packaging, 18 inner canisters, and a novel basket design that includes a borated aluminum flux trap. Criticality and shielding evaluations; fundamental structural, confinement, and thermal assessments; and studies on package operations are presented. The results of this study build significant confidence in the technical feasibility of a high-capacity HALEU transportation package concept while demonstrating the concept’s potential to meet U.S. regulatory requirements.

PS-PC: An Effective Method to Improve VoIP Technology Bandwidth Utilization over ITTP Protocol

Abstract Voice over IP (VoIP) wastes a valuable amount of bandwidth because of its large packet header size compared to its small packet payload. The main objective of this paper is to reduce the amount of this wasted bandwidth, by proposing a new packets coalescence method, called Payload Shrinking and Packets Coalesce (PS-PC). The proposed PS-PC method reduces the amount of the wasted bandwidth by i) coalesces a group of VoIP packets in one header instead of a separate header to each packet and ii) shrinks the VoIP packet payload to a smaller one based on a certain algorithm. The proposed PS-PC method is deployed at the sender side VoIP gateway that represents an exit point to a myriad number of simultaneous VoIP calls. The performance evaluation showed better bandwidth usage when deploying the proposed PS-PC method with ITTP protocol in comparison to the traditional ITTP protocol without the PS-PC method.

Abstract 4537: SBT6050, a HER2-directed TLR8 ImmunoTAC™therapeutic, is a potent human myeloid cell agonist that provides opportunity for single agent clinical activity

Abstract SBT6050, a novel therapeutic comprised of a potent toll-like receptor (TLR) 8 agonist conjugated to a HER2-directed monoclonal antibody that binds an epitope distinct from trastuzumab, is designed for systemic delivery and tumor-localized activation of human myeloid cells in the presence of moderate and high HER2-expressing tumor cells. Many solid tumors, including those expressing HER2, are refractory to immunotherapy due to immune-suppressive mechanisms, loss of HLA, low neoantigen availability, and/or minimal T cell infiltrates. These tumors frequently contain abundant populations of tumor-associated myeloid cells. Activation of these cells through TLR agonism has emerged as a promising approach in overcoming resistance mechanisms to current cancer immunotherapies. Unlike other endosomal TLRs such as TLR7 and TLR9, TLR8 is highly expressed in human myeloid cells known to be prevalent in human tumors such as conventional DCs and macrophages. TLR8's restricted myeloid cell expression removes the risk of inducing T cell death or tumor cell proliferation as described for other innate immune activators such as STING. Agonism of TLR8 in human myeloid cells activates a broad spectrum of anti-tumor immune mechanisms, including proinflammatory cytokine production, repolarization of suppressive myeloid cells and the priming of CTL responses. These functions cannot be replicated by a potent TLR7 agonist or with clinical agents such as resiquimod that agonize TLR7 and only weakly engage TLR8. Here we present data demonstrating the superiority of SBT6050 at activating human myeloid cells compared to HER2 antibody conjugates that use either a selective TLR7 agonist or resiquimod. In vitro studies with human immune cells show that SBT6050 potently induces multiple anti-tumor immune activities, including proinflammatory cytokine and chemokine production, inflammasome activation, direct activation of DCs and indirect T and NK cell cytolytic activity. Our data indicate the favorable profile of SBT6050 is likely due to efficient engagement of TLR8 in conjugate form and TLR8's unique expression profile, and not due to differences in the potency of the small molecule payloads. Using an SBT6050 mouse surrogate we show in vivo evidence for intratumoral TLR agonist activation of several myeloid driven anti-tumor pathways leading to curative single agent efficacy in both a T cell-excluded syngeneic tumor model and a xenograft model lacking T, B and NK cells. Collectively, these data demonstrate that SBT6050 displays an attractive functional profile unachievable with agonist-based antibody conjugates directed against other innate immune receptors. These data also highlight the potential for SBT6050 to be clinically active as a monotherapy. SBT6050 is projected to enter the clinic in 2020 for patients with moderate or high HER2-expressing tumors. Citation Format: Michael R. Comeau, Ty Brender, Monica Childs, Jamie Brevik, Damion Winship, Heather Metz, Jenny Chang, Jeffrey Adamo, Ben Setter, Hengyu Xu, Li-Qun Fan, Brenda Stevens, Sean W. Smith, Phil Tan, Robert DuBose, Yvette Latchman, Peter Baum, Valerie Odegard. SBT6050, a HER2-directed TLR8 ImmunoTAC™therapeutic, is a potent human myeloid cell agonist that provides opportunity for single agent clinical activity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4537.

Efficient Scheduling for the Massive Random Access Gaussian Channel

This paper investigates the massive random access Gaussian channel with a focus on small payloads. For this problem, grant-based schemes have been regarded as inefficient due to the necessity of large feedbacks and the use of inefficient scheduling request methods. This papers attempts to answer whether grant-based schemes can be competitive against state-ot-art grantless schemes and worthy of further investigation. In order to compare these schemes fairly, a novel model is proposed, and, under this model, a novel grant-based scheme is proposed. The scheme uses Ordentlich and Polyanskiy's grantless method to transmit small coordination indices in order to perform the scheduling request, which allows both the request from the users to be efficient and the feedback to be small. We also present improvements to the Ordentlich and Polyanskiy's scheme, allowing it to transmit information through the choice of sub-block, as well as to handle collisions of the same message, significantly improving the method for very small messages. Simulation results show that, if a small feedback is allowed, the proposed scheme performs closely to the state-of-art while using simpler coding schemes, suggesting that novel grant-based schemes should not be dismissed as a potential solution to the massive random access problem.