Mobile Agents Research Articles

True Crime Podcasting as Participatory Journalism: A Digital Ethnography of Collaborative Case Solving

True crime podcasts invite their listeners to crowdsource investigations online, solving cases that have fallen through the cracks of the criminal justice system. Through a cultural criminologist lens, this digital ethnography examines The Vanished podcast as a case study of how true crime listeners engage with solving cases in digital community spaces. Previous studies have dismissed true crime fans as pseudo police acting as digital vigilantes. Podcasting communities provide an important public service, working as participatory journalists to investigate the story and report the truth. Rather than depending on law enforcement permission to organize, online crime-investigation communities leverage the Internet’s function as an organizing agent for mobilization beyond the parameters of conventional social structures and formal government agencies. Findings reveal a six-step process of case collaboration between podcast producers, active listeners, and family and friends of missing persons. Other communities can apply this unique system to successfully investigate crime, suggesting implications for individuals within marginalized groups less likely to find justice through the formal legal system.

Autonomous Cooperative Hunting with Rule-Based and Self-Learning Control for Multiagent Systems

This paper considers the problem of autonomous cooperative hunting in an unknown dynamic environment, where a group of mobile agents collaborate to capture a moving target. Due to the decentralized decision-making nature of multi-agent systems and the presence of real-world constraints, it is a challenging task. To solve this problem, an artificial rule based hunting algorithm (AR-HA) is firstly developed based on the principles of attraction and repulsion with heading adjustment, and each agent is controlled by the designed rules. Then, to further enhance the stability of cooperative hunting, a self-learning algorithm based on Twin Delayed Deep Deterministic policy gradient (SL-TD3) is proposed. Each agent is governed by its own SL-TD3 controller and learns independently from its interaction with the environment, taking advantage of the reward function designed based on the control rules of AR-HA. Besides, in order to improve training efficiency, imitation learning is employed to initialize the actor network. Experiments on both virtual and real robots demonstrate the effectiveness of the proposed algorithms for autonomous cooperative hunting.

An integrated decision-execution framework of cooperative control for multi-agent systems via reinforcement learning

Cooperative control is both a crucial and hot research topic for multi-agent systems (MASs). However, most existing cooperative control strategies guarantee tracking stability under various non-ideal conditions, while the path decision capability is often ignored. In this paper, the integrated decision-execution (IDE) framework is newly presented for cooperative control of multi-agent systems (MASs) to accomplish the integrated task of path decision and cooperative execution. This framework includes a decision layer and a control layer. The decision layer generates a continuous trajectory for the virtual leader to reach the target from its initial position in an unknown environment. To achieve the goal of this layer, (1) the Step-based Adaptive Search Q-learning (SASQ-learning) algorithm is proposed based on reinforcement learning to efficiently find the discrete path, (2) an Axis-based Trajectory Fitting (ATF) method is developed to convert the discrete path into a continuous trajectory for mobile agents. In the control layer, this trajectory is used to regulate the following MASs to achieve cooperative tracking control with the presence of input saturation. Simulation experiments are presented to demonstrate the effectiveness of this framework.

Advanced spatial query processing in IoT through mobile agent integration

In IoT environments, various applications and protocols rely on spatial query processing to obtain, analyze, and interpret information from sensor nodes based on their location within a specific area. It enables the efficient monitoring and management of spatial data, which is crucial for applications such as environmental monitoring, smart cities, and disaster response. By querying the location and status of sensor nodes, spatial query processing facilitates real-time decision-making, optimizes resource allocation, and enhances the overall performance of the IoT system.This paper focuses on Window queries, a key spatial query type that retrieves data from sensors within a defined two-dimensional zone. The research aims to improve spatial query processing in IoT environments by proposing a Window query processing method that balances various performance factors such as energy efficiency, latency, accuracy, and query success rate. We introduce a novel approach using mobile agents to enhance spatial query processing by addressing the constraints of sensor networks. Simulation results from the NS-2 simulator demonstrate the effectiveness of our method across different parameters and environments.

Microfinance, Financial Inclusion and Economic Welfare in Africa: A Panel Investigation

This study explores the relationship between microfinance, financial inclusion, and economic welfare in a sample of 23 African countries for the period of 2004 to 2023 using annual time series data. We measured microfinance with the number of Branches of Microfinance banks, Microfinance Borrowers, Microfinance outstanding deposits, Microfinance outstanding loans; financial inclusion number of registered mobile money accounts per 1,000 adults; the number of mobile money agent outlets par 1,000 adults; and digital card ownership; governance and institutional quality with Rule of law, regulatory quality, and government effectiveness; and economic welfare with household consumption; while we controlled for the inflation rate, interest rate and exchange rate. These variables were estimated using Panel Least Squares, Fully Modified OLS (FMOLS), Dynamic OLS (DOLS), and Panel Autoregressive Distributed Lag (ARDL) estimation techniques. The result of the cointegration revealed that cointegration exists between the variables of the model. Findings from the aforesaid estimation techniques show that there is the existence of long-run relationships between microfinance, financial inclusion, and economic welfare since the coefficients of the microfinance and financial inclusion variables are statistically significant. The coefficients of the error correction terms which measure the effects of the short-run dynamics of the model suggest that the speeds of adjustment from the long run to the short run in the models would be 76%, 61%, 83%, 67%, 68%, 34%, and 80% respectively for all the specified models. Following the findings of the study, conclusions were drawn and the study suggests that microfinance institutions should adapt to the digitization of their products and services for wider coverage on one hand; the government should provide digital financial amenities to create a fertile ground for micro-financial institutions to rely on to maximize the welfare of the economy.

Locating a black hole in a dynamic ring

In networked environments supporting mobile agents, a pressing problem is the presence of network sites harmful for the agents. In this paper we consider the danger posed by a node that destroys any incoming agent without leaving any trace. Such a dangerous node is known in the literature as a black hole (Bh). The problem of a team of system agents determining its location, known as black hole search (Bhs ), has been extensively studied in the literature under a variety of assumptions, both in synchronous and asynchronous settings. The main complexity parameter of Bhsis the number of system agents (called size) needed to solve the problem; other parameters are the number of moves (called cost) performed by the agents, and the time until termination.In the existing literature, with only a couple of exceptions, all results are based on a common assumption that the network is static, i.e. its topology does not change in time. We consider instead the Bhswhen the network is dynamic: the link structure of the graph changes over time. While time-varying graphs have been the focus of intense research in the last two decades, very little is known on the problem of locating the Bh in such networks.In this paper, we contribute to fill this research gap by studying Bhsin dynamic ring networks, focusing on the 1-interval connectivity adversarial dynamics. Feasibility and complexity of the problem depend on many factors, specifically on the size n of the ring, whether or not n is known, and the type of inter-agent communication (whiteboards, tokens, face-to-face, visual). In this paper, we provide a complete feasibility characterization presenting size optimal algorithms. Furthermore, we establish lower bounds on the cost and time of size-optimal solutions and show that our algorithms achieve those bounds.

Repeated CXCR4 Blockade by Plerixafor Attenuates Transplant Vasculopathy in Murine Aortic Allografts.

Plerixafor, a hematopoietic stem cell mobilization agent, increases the peripheral blood content of effector and regulatory T cells and may have beneficial effects on cardiac allograft vasculopathy. The aim of the current study was to evaluate its effects in a murine aortic allograft model using different application procedures. Allogeneic donor aorta grafts (n = 8/group) from C57BL/6 mice(H2b) were abdominally transplanted into CBA mice (H2k). Plerixafor application was performed either continuously for 14 d using abdominally implanted osmotic pumps (1 mg/kg/d) or i.p. with a single dose (1 and 5 mg/kg) on day 0 or pulsed injections of 1 mg/kg on days 0, 7, 14, and 21. Cell distribution was monitored by FACS. Aortic grafts were evaluated for neointima development by Elastica-van-Gieson on day 30. Immunofluorescence and intragraft gene expression analysis were performed. On day 14, significantly fewer hematopoietic stem cells were found in the bone marrow of all plerixafor-treated mice. In the pulsed application group, significantly more hematopoietic stem cells were found in the peripheral blood on day 14 (0.045 ± 0.002%; p < 0.01 [pulsed]; versus 0.0068 ± 0.002% [control]) and also more regulatory T cells. PCR revealed lower inflammatory cytokines. The luminal occlusion was significantly reduced in the pulsed treated group (33.65 ± 8.84 versus 53.13 ± 12.41) going along with decreased neointimal CD4+ T cell and plasmacytoid dendritic cell infiltration, as well as less smooth muscle cell proliferation. The application of plerixafor attenuates chronic rejection in aortic allografts via immunomodulatory effects. Injection of repeated low-dose plerixafor is the most effective application form in the aortic transplant model.

Comparison of the efficacy of a generic plerixafor versus Mozobil as adjunct peripheral blood stem cell mobilization agents in multiple myeloma patients.

Plerixafor is an adjunct peripheral blood stem cell (PBSC) mobilization agent with well-demonstrated safety and efficacy. The routine use of the originator brand drug (Mozobil) has been limited by cost. This retrospective study was conducted to compare the mobilization efficacy of a lower-cost generic plerixafor and Mozobil in multiple myeloma (MM) patients. The study included two near-concurrent cohorts of MM patients mobilized with brand (n = 64) or generic (n = 61) plerixafor in addition to filgrastim. Collection and early engraftment outcomes were compared. The two cohorts had comparable distributions of sex, age, and weight. Previous treatment histories and proportions of upfront versus just-in-time plerixafor use were similar. There was no significant difference in their median overall cumulative total yield (106 CD34+ cells/kg) (brand, 5.91; generic, 5.80; p = .51). However, the generic cohort had a significantly higher median yield after the first dose (4.79 vs. 3.78, p = .03), and consequently lower median numbers of plerixafor doses (p = .001) and collection days (p = .002). Only 31.1% of patients in the generic arm required more than one dose versus 59.4% of patients in the brand arm (p = .006). All transplanted patients in the brand and generic arms (90.6% and 85.2% respectively, p = .42) achieved engraftment. There was no significant difference in their median times to platelet and neutrophil engraftment, nor their transfusion requirements during the first 30 days post-transplant. The generic plerixafor produced comparable cumulative collection yields and early engraftment outcomes as Mozobil, but fewer doses and collection days were needed to reach collection goal.

LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras With Negative Imaging Plane on Mobile Agents

LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras With Negative Imaging Plane on Mobile Agents

Modelling and forecasting mobile money customer transaction volumes in rural and semi-urban Malawi: An autoregressive integrated moving average spatial decomposition

Mobile money technologies in Malawi have revolutionised banking and monetary transactions across geographical barriers. Prospects of profit have drawn mobile money agents to invest in the business but find it is more profitable when substantial customers subscribe to the cash-in and cash-out facilities of mobile money. Despite the initial success, several challenges have emerged, including regulatory hurdles, network reliability issues, and the need for increased financial literacy among users. The volumes of transactions in the rural areas are observably lower compared to urban areas. This study uses Bvumbwe township in Malawi to model and forecast the discrepancy of mobile money transactions in rural and semi-urban Malawi. The study uses ARIMA modelling to understand the temporal manifestation of mobile money subscription in these localities. Using ARMA (1,1) models decomposed for the semi-urban and rural area, the study finds that the semi-urban area has a disproportionately higher and lasting volume of mobile money transactions compared to the rural area. The study also finds that mobile money transactions are more susceptible to long-lasting effects of external shocks in the rural area compared to the urban area. Intuitively, the day-to-day relationship in the transactions is also stronger in the rural area. These findings highlight the need for tailored policy interventions to enhance mobile money adoption and utilization in different geographical contexts.

2-AG-loaded and bone marrow-targeted PCL nanoparticles as nanoplatforms for hematopoietic cell line mobilization

BackgroundThe use of mobilizing agents for hematopoietic stem cell (HSC) transplantation is insufficient for an increasing number of patients. We previously reported lipid made endocannabinoid (eCB) ligands act on the human bone marrow (hBM) HSC migration in vitro, lacking long term stability to be therapeutic candidate. In this study, we hypothesized if a novel 2-AG-loaded polycaprolactone (PCL)-based nanoparticle delivery system that actively targets BM via phosphatidylserine (Ps) can be generated and validated.MethodsPCL nanoparticles were prepared by using the emulsion evaporation method and characterized by Zetasizer and scanning electron microscopy (SEM). The encapsulation efficiency and release profile of 2-AG were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The presence of cannabinoid receptors (CBRs) in HSCs and monocytes was detected by flow cytometry. Cell morphology and viability were assessed using transmission electron microscopy (TEM), SEM, and the WST-1 viability assay. The migration efficacy of the 2-AG and 2-AG-loaded nanoparticle delivery system on HSCs and HPSCs (TF-1a and TF-1) and monocytes (THP-1) was evaluated using a transwell migration assay.ResultsThe 140–225 nm PCL nanoparticles exhibited an increasing polydispersity index (PDI) after the addition of Ps and 2-AG, with a surface charge ranging from − 25 to -50 mV. The nanoparticles released up to 36% of 2-AG within the first 8 h. The 2-AG-Ps-PCL did not affect cellular viability compared to control on days 5 and 10. The HSCs and monocytes expressed CB1R and CB2R and revealed increased migration to media containing 1 µM 2-AG-Ps-PCL compared to control. The migration rate of the HSCs toward monocytes incubated with 1 µM 2-AG-Ps-PCL was higher than that of the monocytes of control. The 2-AG-Ps-PCL formulation provided a real time mobilization efficacy at 1 µM dose and 8 h time window via a specific CBR agonism.ConclusionThe newly generated and validated 2-AG-loaded PCL nanoparticle delivery system can serve as a stable, long lasting, targeted mobilization agent for HSCs and as a candidate therapeutic to be included in HSC transplantation (HSCT) protocols following scale-up in vivo preclinical and subsequent clinical trials.Graphical

Comparative analysis of selected optimization algorithms for mobile agents’ migration pattern

Comparative analysis of selected optimization algorithms for mobile agents’ migration pattern

Principal–agent trust and adoption of digital financial services: Evidence from India

AbstractThe high reliance on cash is a lifestyle for many people, and their low proficiency with smartphone usage acts as an inertial barrier to using digital financial services (DFS). Given low financial or digital literacy, online banking transactions have to be promoted and mediated by DFS agents. This study examines the role of digital platforms, intermediaries such as banks, mobile money agents, payment banks, post offices, and the government's increasing use of digital technologies. This usage of digital platforms is based on the trust relationship between the principals, who are owners of their bank accounts, and agents of DFS, who are intermediaries. A linear probabilistic model is employed to determine the determinants behind the low adoption of DFS between the necessity and nonnecessity groups. We observe that demand‐side factors like education level, identity proof (documentation), and level of smartphone use proficiency increase the probability of a principal's involvement in a digital mode of payment. At the same time, supply‐side factors like digital infrastructure and trust deficit due to unviable commission incentives to DFS agents decrease the principal's likelihood of using digital platforms.

Enabling Mobile AI Agent in 6G Era: Architecture and Key Technologies

Enabling Mobile AI Agent in 6G Era: Architecture and Key Technologies

Self configuring mobile agent-based intrusion detection using hybrid optimized with Deep LSTM

Sensor nodes can be deployed in harsh or hostile environments in many applications, making these nodes more prone to failure. The illegal movement monitoring within the sensor networks is a most challenging problem. The mobile malicious nodes are preferred by the attacker to maximize his impact. For a dynamic environment, a promising technology of sensor networks is expected to Intrusion detection. Multi-mobile agents utilize many approaches, after verification that collects data from sensor nodes. However, these approaches are inefficient to verify all the sensor nodes (SNs) of the network, due to its high delay, energy consumption, and mobility. The proposed Dunnock Ibis optimization LSTM model (DIO opt LSTM) solves this problem. Here, the sensor nodes are grouped into clusters; hence, mobile agent performs verification only the cluster heads instead of verifying all the SNs. The proposed DIO optimization combines the unique behavior of Egret Swam and Ibis optimization algorithm which efficiently tunes the LSTM classifier, resulting in the model providing better convergence. The simulation results show the proposed system shows a better result than the existing system by utilizing the database IDS 2018 Intrusion CSVs, the analysis is done based on performance metrics such as End-end-delay (ED), normalized energy (NE), and throughput. At 200 nodes and 1500 rounds, the DIO opt LSTM method has efficiently performed 146 numbers of alive nodes, 0.46 ms of delay, 0.15 J of normalized energy, and 0.89 bps of throughput.

Development of VLA4 and CXCR4 Antagonists for the Mobilization of Hematopoietic Stem and Progenitor Cells.

The treatment of patients diagnosed with hematologic malignancies typically includes hematopoietic stem cell transplantation (HSCT) as part of a therapeutic standard of care. The primary graft source of hematopoietic stem and progenitor cells (HSPCs) for HSCT is mobilized from the bone marrow into the peripheral blood of allogeneic donors or patients. More recently, these mobilized HSPCs have also been the source for gene editing strategies to treat diseases such as sickle-cell anemia. For a HSCT to be successful, it requires the infusion of a sufficient number of HSPCs that are capable of adequate homing to the bone marrow niche and the subsequent regeneration of stable trilineage hematopoiesis in a timely manner. Granulocyte-colony-stimulating factor (G-CSF) is currently the most frequently used agent for HSPC mobilization. However, it requires five or more daily infusions to produce an adequate number of HSPCs and the use of G-CSF alone often results in suboptimal stem cell yields in a significant number of patients. Furthermore, there are several undesirable side effects associated with G-CSF, and it is contraindicated for use in sickle-cell anemia patients, where it has been linked to serious vaso-occlusive and thrombotic events. The chemokine receptor CXCR4 and the cell surface integrin α4β1 (very late antigen 4 (VLA4)) are both involved in the homing and retention of HSPCs within the bone marrow microenvironment. Preclinical and/or clinical studies have shown that targeted disruption of the interaction of the CXCR4 or VLA4 receptors with their endogenous ligands within the bone marrow niche results in the rapid and reversible mobilization of HSPCs into the peripheral circulation and is synergistic when combined with G-CSF. In this review, we discuss the roles CXCR4 and VLA4 play in bone marrow homing and retention and will summarize more recent development of small-molecule CXCR4 and VLA4 inhibitors that, when combined, can synergistically improve the magnitude, quality and convenience of HSPC mobilization for stem cell transplantation and ex vivo gene therapy after the administration of just a single dose. This optimized regimen has the potential to afford a superior alternative to G-CSF for HSPC mobilization.

Complex Laplacian approach for formation tracking without velocity measurements

This paper is focused on formation tracking control of multi-agent systems in a leader–follower setting. The objective is to introduce control algorithms to steer a team of mobile agents into a desired, moving geometrical pattern while the agents are unaware of their own and other agents' velocity information during the entire process. We introduce a formation control law under which the agents asymptotically shape a desired geometrical pattern and track a constant reference velocity. Another control law is then introduced to address the case where the reference velocity is time-varying. Both control laws are based on the complex Laplacian approach and do not require agents' velocity information. The convergence of these algorithms are proved and their performance are examined via numerical examples. Simulation results verify the outperformance of the proposed control laws compared to the rival control schemes in the literature.

Overcoming probabilistic faults in disoriented linear search

We consider search by mobile agents for a hidden, idle target, placed on the infinite line. Feasible solutions are agent trajectories in which all agents reach the target sooner or later. A special feature of our problem is that the agents are p-faulty, meaning that every attempt to change direction is an independent Bernoulli trial with known probability p, where p is the probability that a turn fails. We are looking for agent trajectories that minimize the worst-case expected termination time, relative to the distance of the hidden target to the origin (competitive analysis). Hence, searching with one 0-faulty agent is the celebrated linear search (cow-path) problem that admits optimal 9 and 4.59112 competitive ratios, with deterministic and randomized algorithms, respectively.First, we study linear search with one deterministic p-faulty agent, i.e., with no access to random oracles, p∈(0,1/2). For this problem, we provide trajectories that leverage the probabilistic faults into an algorithmic advantage. Our strongest result pertains to a search algorithm (deterministic, aside from the adversarial probabilistic faults) which, as p→0, has optimal performance 4.59112+ϵ, up to the additive term ϵ that can be arbitrarily small. Additionally, it has performance less than 9 for p≤0.390388. When p→1/2, our algorithm has performance Θ(1/(1−2p)), which we also show is optimal up to a constant factor.Second, we consider linear search with two p-faulty agents, p∈(0,1/2), for which we provide three algorithms of different advantages, all with a bounded competitive ratio even as p→1/2. Indeed, for this problem, we show how the agents can simulate the trajectory of any 0-faulty agent (deterministic or randomized), independently of the underlying communication model. As a result, searching with two agents allows for a solution with a competitive ratio of 9+ϵ (which we show can be achieved with arbitrarily high concentration) or a competitive ratio of 4.59112+ϵ. Our final contribution is a novel algorithm for searching with two p-faulty agents that achieves a competitive ratio 3+4p(1−p), in expectation and with arbitrarily high concentration.

On a dynamic and decentralized energy-aware technique for multi-robot task allocation

In the real world, multi-robot systems need to deal with on-the-fly (runtime) arrivals of new sets of tasks. This entails repeated adjustments of their current task allocations to include the newer ones while also ensuring that the overall performance does not degrade. This paper proposes a decentralized and distributed dynamic task allocation algorithm to handle this issue in a multi-robot scenario. The proposed work provides a conflict-free allocation of a set of tasks constituting a job to robots and minimizes the total execution time. These jobs can comprise multiple independent and/or dependent tasks or a combination thereof, which are injected on-the-fly into a network of robots. The dependent tasks of a job are related by precedence constraints that specify the ordering or dependencies between pairs of tasks. The work also describes a decentralized adaptive energy threshold mechanism for determining whether or not a robot needs to visit a battery stockpile after the execution of a task. Conflicting task selections among the robots in this decentralized set-up are resolved using mobile agents during runtime. Apart from allocating tasks to the robots, these mobile agents exploit the benefits of centralized and decentralized systems and provide an advantage over auction-based task allocation algorithms. The proposed algorithm takes into consideration the energy requirements, both during the task allocation process and actual execution. The proposed algorithm also caters to strategies to deal with delays caused by obstacles and congestion during the actual execution of the tasks. Experiments conducted using Webots, an open-source robot simulator, and Tartarus, a multi-agent platform, authenticate the efficacy of the proposed algorithm compared to other prominent task allocation algorithms in terms of minimization of average waiting time, total task allocation time, total job allocation time, and total execution time of an experiment.

Dimensi Pembentuk Ketertarikan Investor Memilih Produk Cilem BSI Kencong

Islamic investment has become an attractive choice for Indonesian society looking to grow their funds while adhering to Islamic law. BSI Kencong, part of Bank Syariah Indonesia (BSI), offers the Cilem investment product designed to meet these needs. This research aims to identify the factors influencing public interest in investing in Cilem at BSI Kencong. The research method employed is qualitative, utilizing literature review and customer testimonial analysis. Data was gathered from various sources, including official BSI publications, Islamic investment literature, and customer reviews. The findings reveal several key factors driving public interest in Cilem investments. Firstly, the competitive profit potential is a major attraction, supported by expertise in investment management and diversification across safe Sharia-compliant instruments. Secondly, the security and trust provided by BSI Kencong, overseen by the Financial Services Authority and the National Sharia Board of MUI, instill confidence in customers. Thirdly, adherence to Islamic principles is crucial, evidenced by Sharia certification from the National Sharia Board of MUI. Additionally, ease of access and transactions play a significant role. BSI Kencong offers various channels including branches, the BSI Mobile app, website, and agents, enhancing customer convenience. Friendly and professional service from BSI Kencong staff adds to customer comfort and satisfaction. Active promotion and education efforts by BSI Kencong increase public awareness and understanding of Cilem products. Positive testimonials from investors demonstrate real benefits, encouraging prospective customers to participate. Lastly, the desire to support the growth of Islamic economy in Indonesia further strengthens public interest in Cilem investments. In conclusion, the combination of factors such as profit potential, security and trust, Sharia compliance, ease of access, professional service, promotion and education, positive testimonials, and support for Islamic economy collectively create a compelling attraction for the public to invest in Cilem products through BSI Kencong.