Agent System Research Articles

Oil-in-water nanoemulsion adhesive system: Preparation by ultrasonic homogenization and its application in 3D direct writing composite energetic materials

Stable and low-particle size nanoemulsions were prepared using ultrasound homogenization. The conditions for preparing low-viscosity nanoemulsions were optimized using Response Surface Methodology (RSM) experimental design. The results showed that the addition of composite surfactants at 1%, an ultrasound amplitude of 35%, an ultrasound time of 4 min, and an ultrasound temperature of 20 °C yielded nanoemulsions with the best particle size and stability. The particle distribution was uniform, and the cold and heat stability were good. Compared with traditional emulsions, the low-viscosity nanoemulsion had better environmental stability, storage stability, and exhibited a phenomenon of self-reducing particle size at 40–55 °C, indicating that the emulsion had good performance under complex environmental conditions. The performance test of composite energetic materials using two types of emulsions as bonding systems showed that the low-viscosity nanoemulsion composite energetic material effectively reduced friction sensitivity, increased detonation velocity, and had better thermal stability and smaller propagation size. The results confirmed that the low-viscosity nanoemulsion perfectly met the requirements of bonding agents for composite energetic materials. This study provides a new approach for bonding agent systems of composite energetic materials and can serve as a new method to meet the special requirements of composite energetic materials.

Activity and recyclability enhancement of pH-dependent Fe0@BC-mediated heterogeneous sodium percarbonate (SPC)-reducing agents (RA) system

Dyes pose great threats to the aquatic environment and human health. Fe0-based Fenton-like systems have been widely employed for the degradation of organic dyes. However, the regulation of degradability and recyclability was still unclear. In this study, Rhodamine B (RhB) was served as the model pollutant, hydroxylamine hydrochloride was selected as the RA, the natural photocatalysis system demonstrated stable operation. RA, as performance enhancement agent, was firstly reported in micro/nano-Zero-Valent Iron@Biochar (m/nZVI@BC) based SPC-RA system. Carrier size-fractionated m/nZVI@BC was fabricated by one-step carbothermal method. As a result, RA synergistically interacted with SPC, and the reaction time reduced from 15 min to 4 min. In the 0.010 g m/nZVI@BC-mediated SPC-RA system, over 95% of RhB (100 mg·L−1, 1041.667 mg·g−1) was successfully degraded. The maximum degradation ability could still exceed 1g·g−1 via 5 times repeated applications. Meanwhile, the loss of degradability, caused by halving SPC concentration could be compensated by RA dosage measurement. The entire degradation process was predominantly dominated by free radicals (•OH> 1O2> •O2−> •CO3−). Reactive oxidizing species (ROSs) were primarily excited by α-Fe0, Fe3C and N sites of biochar (BC). Light and BC carrier dedicated slight influence. These discoveries shed a light on the activity and recyclability regulation of catalytic material, aligning with the principles of green chemistry and cleaner production. This study demonstrates a novel approach to efficient management of solid waste disposal, reuse of waste biomass, advanced treatment of dye-containing wastewater, pollution control in aquatic environments.

Leveraging active queries in collaborative robotic mission planning

This paper focuses on the high-level specification and generation of 3D models for operational environments using the idea of active queries as a basis for specifying and generating multi-agent plans for acquiring such models. Assuming an underlying multi-agent system, an operator can specify a request for a particular type of model from a specific region by specifying an active query. This declarative query is then interpreted and executed by collecting already existing data/information in agent systems or, in the active case, by automatically generating high-level mission plans for agents to retrieve and generate parts of the model that do not already exist. The purpose of an active query is to hide the complexity of multi-agent mission plan generation, data transformations, and distributed collection of data/information in underlying multi-agent systems. A description of an active query system, its integration with an existing multi-agent system and validation of the active query system in field robotics experimentation using Unmanned Aerial Vehicles and simulations are provided.

Chitosan in cancer therapy: a dual role as a therapeutic agent and drug delivery system.

Although chemotherapy is still the most preferred treatment for cancer, most chemotherapeutic agents target both cancer cells and healthy cells and cause serious sideeffects due to high toxicity. Improved drug delivery systems (DDSs), which enhance the efficacy of current chemotherapeutic drugs while reducing their toxicity, offer potential solutions to these challenges. Chitosan (CS) and its derivatives are biopolymers with biodegradable, biocompatible, and low-toxicity properties, and their structure allows for convenient chemical and mechanical modifications. In its role as a therapeutic agent, CS can impede the proliferation of tumor cells through the inhibition of angiogenesis and metastasis, as well as by triggering apoptosis. CS and its derivatives are also frequently preferred as DDSs due to their properties such as high drug-carrying capacity, polycationic structure, long-term circulation, and direct targeting of cancer cells. Various therapeutic agents linked to CS and its derivatives demonstrate potent anticancer effects with advantages such as reduced side effects compared to the original drugs, owing to factors like targeted distribution within cancer tissues and sustained release. This review emphasizes the utilization of CS and its derivatives, both as therapeutic agents and as carriers for established chemotherapeutic drugs.

Usability and Acceptability of a Conversational Agent Health Education App (Nthabi) for Young Women in Lesotho: Quantitative Study.

Young women in Lesotho face myriad sexual and reproductive health problems. There is little time to provide health education to women in low-resource settings with critical shortages of human resources for health. This study aims to determine the acceptability and usability of a conversational agent system, the Nthabi health promotion app, which was culturally adapted for use in Lesotho. We conducted a descriptive quantitative study, using a 22-item Likert scale survey to assess the perceptions of the usability and acceptability of 172 young women aged 18-28 years in rural districts of Lesotho, who used the system on either smartphones or tablets for up to 6 weeks. Descriptive statistics were used to calculate the averages and frequencies of the variables. χ2 tests were used to determine any associations among variables. A total of 138 participants were enrolled and completed the survey. The mean age was 22 years, most were unmarried, 56 (40.6%) participants had completed high school, 39 (28.3%) participants were unemployed, and 88 (63.8%) participants were students. Respondents believed the app was helpful, with 134 (97.1%) participants strongly agreeing or agreeing that the app was "effective in helping them make decisions" and "could quickly improve health education and counselling." In addition, 136 (98.5%) participants strongly agreed or agreed that the app was "simple to use," 130 (94.2 %) participants reported that Nthabi could "easily repeat words that were not well understood," and 128 (92.7%) participants reported that the app "could quickly load the information on the screen." Respondents were generally satisfied with the app, with 132 (95.6%) participants strongly agreeing or agreeing that the health education content delivered by the app was "well organised and delivered in a timely way," while 133 (96.4%) participants "enjoyed using the interface." They were satisfied with the cultural adaptation, with 133 (96.4%) participants strongly agreeing or agreeing that the app was "culturally appropriate and that it could be easily shared with a family or community members." They also reported that Nthabi was worthwhile, with 127 (92%) participants reporting that they strongly agreed or agreed that they were "satisfied with the application and intended to continue using it," while 135 (97.8%) participants would "encourage others to use it." Participants aged 18-24 years (vs those aged 25-28 years) agreed that the "Nthabi app was simple to use" (106/106, 100% vs 30/32, 98.8%; P=.01), and agreed that "the educational content was well organised and delivered in a timely way" (104/106, 98.1% vs 28/32, 87.5%; P=.01). These results support further study of conversational agent systems as alternatives to traditional face-to-face provision of health education services in Lesotho, where there are critical shortages of human resources for health. ClinicalTrials.gov NCT04354168; https://www.clinicaltrials.gov/study/NCT04354168.

A possible thermodynamic definition and equation of state for a model of political election cycles.

This work demonstrates how a simulation of political discourse can be formulated using variables of the agents' behaviors in a simulation, as thermodynamic variables. With these relations the methodology provides an approach to create a correspondence between the variables of an agent based social system and those of a thermodynamic system. Extended from this observation, diagrams akin to a P-V diagram for gases can be created for this social system. The basic thermodynamic variables of temperature, pressure and volume are defined from a system of agents with political and non-political actions engaged in simulated political discourse. An equation of state is defined for the simulated political phenomenon. Through this equation of state the full thermodynamic map of the system is presented under a P-V diagram with isothermal and isentropic lines, which is able to represent the political situation of the system at each point of time. The classic election cycle that takes place can be represented on this thermodynamic map (corresponding to an Otto cycle). This provides a possibility for researching macroscopic social cycles as a thermodynamic/informational cycle as the traces on the thermodynamic map show similarities to an Otto cycle. Such a formulation reinforces the endeavours of social physics to view social phenomena with physical principles.

Development of Paclitaxel Proliposomal Dry Powder Inhaler (PTX-PLM-DPI) by Freeze-Drying Method for Lung Cancer

Despite various efforts, a successful selective delivery system for chemotherapeutic agents for lung cancer is still lacking. Dry powder inhaler (DPI) systems based on proliposomes (PLMs) could be a potential system for the efficient delivery of paclitaxel to lungs. PLM-based DPI prepared with a freeze-drying method can therefore be an alternative. Paclitaxel-loaded PLM-based DPI (PTX-PLM-DPI) powders were prepared using the method of thin film deposition on a carrier followed by freeze drying. These were prepared using soya phosphatidylcholine (SPC) and cholesterol as the lipids and mannitol as the carrier. The reconstituted liposomes were evaluated in terms of size, morphology, drug entrapment, release and cytotoxicity. The DPI powders were evaluated for their flow property, surface topography, dose uniformity and in vitro lung deposition. Stable and free-flowing PTX-PLM-DPI powder was obtained that could be reconstituted into homogenous liposomal vesicles < 200 nm as confirmed by TEM and SEM studies. The liposomes showed drug entrapment of 92.64 ± 1.4% and diffusion-controlled release of up to 28% in 24 h. These liposomes showed better dose-dependent cytotoxicity in A549 cells in comparison to paclitaxel suspension with IC50 values of 46 ± 0.87 ng/mL and 154.9 ± 3.64 ng/mL, respectively. In vitro lung deposition studies of the PTX-PLM-DPI showed sufficient deposition with the fine particle fraction (FPF) of 50.86 ± 2.8% of particles with an aerodynamic diameter less than 5 µ. Hence, it canbe concluded that PLM-based DPI prepared by freeze drying can be a promising, stable, safe and free-flowing system for the enhanced lung delivery of paclitaxel.

Research on the optimization of the temperature field distribution of a multi-source microwave agent system based on event-triggered

Aiming at the problem of optimizing temperature distribution and heating efficiency in a multi-source microwave agent system, a collaborative tracking strategy using an event-triggering approach is explored. Firstly, setting the control object as a switch to optimize the system control process, a new cooperative switching strategy of event-triggered is designed to intensify the process of energy distribution by changing the time–frequency distribution of power. Secondly, exploring multi-agent architecture with an event-triggered multi-microwave source system to minimize communication frequency and energy consumption for faster agreement. Then, The material grouping strategy divides all materials into four categories based on their characteristics. Two materials, potato (group (a)) and SiC (group (c)) are selected for experimentation. Finally, a simple and easy-to-implement multi-source microwave numerical heating model was constructed using finite element analysis. The heating law described in this article was tested through experiments. The results showed that using this method increased the utilization rate of microwave energy in SiC by a maximum of 9.67% compared to traditional heating methods. Furthermore, it improved the temperature uniformity while maintaining excellent quality. Additionally, the energy utilization efficiency of potatoes was maximized by 8.76%, and the temperature uniformity was improved mostly by 12.04%.

Application of AI conversation agent in new frameworks and fields and improvement in sensory aspects

Taking a big step with the development of AI, the functions of conversation agents are becoming increasingly mature, and people's lives are becoming increasingly dependent on the conversation agent system. Its assistance to people is reflected in many fields. This has sparked people's exploration of some emerging fields, it is necessary to organize and summarize the new technologies, functions, data, and methods for training new data required for studying emerging fields. More and more deep learning technology have been applied to conversation agents that improve the quality of the service significantly. It is still in the initial stage, and needs improvement both at modeling methods and datasets gathering.

Gellan-Based Hydrogel as a Drug Delivery System for Caffeic Acid Phenethyl Ester in the Treatment of Oral Candida albicans Infections.

Candida albicans can cause various types of oral infections, mainly associated with denture stomatitis. Conventional therapy has been linked to high recurrence, toxicity, and fungal resistance, necessitating the search for new drugs and delivery systems. In this study, caffeic acid phenethyl ester (CAPE) and gellan gum (GG) were studied as an antifungal agent and carrier system, respectively. First, we observed that different GG formulations (0.6 to 1.0% wt/vol) were able to incorporate and release CAPE, reaching a controlled and prolonged release over 180 min at 1.0% of GG. CAPE-GG formulations exhibited antifungal activity at CAPE concentrations ranging from 128 to >512 µg/mL. Furthermore, CAPE-GG formulations significantly decreased the fungal viability of C. albicans biofilms at short times (12 h), mainly at 1.0% of GG (p < 0.001). C. albicans protease activity was also reduced after 12 h of treatment with CAPE-GG formulations (p < 0.001). Importantly, CAPE was not cytotoxic to human keratinocytes, and CAPE-GG formulations at 1.0% decreased the fungal burden (p = 0.0087) and suppressed inflammation in a rat model of denture stomatitis. Altogether, these results indicate that GG is a promising delivery system for CAPE, showing effective activity against C. albicans and potential to be used in the treatment of denture stomatitis.

Using brewing waste diatomite activated by ball milling to simple and sustainable synthesis of nano-H-ZSM-5 aggregates

Brewing waste diatomite (BSDT) from the beer industry is a highly productive silica-aluminate solid waste and realizing the resource utilization of BSDT is the key to achieving the circular economy. Synthesis of zeolites from BSDT is a high value-added utilization method, but using BSDT to synthesize zeolites via “silica-alumina homologation” is difficult because of its high SiO2/Al2O3 ratio and low chemical activity. Further, using BSDT to synthesize high-quality nano-zeolites on a large scale through a simple and green method is a huge challenge. In this study, we propose a facile and scalable strategy to utilize BSDT as the only Si-Al source to prepare high-quality nano-H-ZSM-5 aggregates with hierarchical structures in a single templating agent system by solid-like transformations. The activation of BSDT was achieved by mechanical ball milling. Crystallite size and hierarchical structures are controlled by decoupling the crystal nucleation and growth processes. Due to the “silica-alumina homologation” system, aluminum species enter the zeolite framework along with the dynamic crystallization process and provide uniform acidic sites. In the methanol conversion reaction, the obtained catalysts showed longer lifetime (172.5 h) and higher light olefin selectivity (62.5%) compared to commercial catalysts. This strategy is simple, economical, and scalable, and can be extended to the synthesis of other framework-type zeolites with high SiO2/Al2O3 ratios.

A Review of the Literature on Multi Agent Based Power Distribution System Restoration

One of the most popular research areas is multi agent systems (MAS), which consists of multiple agents interacting with one another to accomplish a shared goal. MAS has been created with a variety of power system applications in mind. One major use for such is power system restoration. A number of architectures for fault isolation, problem identification, and power system restoration are presented by researchers. The available architectures for power distribution restoration and upcoming developments in MAS-based power system restoration are thoroughly reviewed in this research.

Hyaluronan/B12-chitosan polyelectrolyte complex for oral colistin administration

Polyelectrolyte complexes (PECs) based on polysaccharides, including hyaluronic acid (HA) and chitosan (CS), are promising delivery systems for antimicrobial agents, including oral administration of the peptide antibiotic colistin (CT). Modification of CS with different targeting ligands to improve intestinal permeability is a suitable way to improve the oral bioavailability of polyelectrolyte particles. This study describes the procedure for obtaining CT-containing PECs based on HA and CS modified with cyanocobalamin (vitamin B12). In this case, vitamin B12 is used as a targeting ligand because it is absorbed in the ileum via specific transporter proteins. The resulting PECs had a hydrodynamic size of about 284 nm and a positive ζ-potential of about 26 mV; the encapsulation efficiency was 88.2 % and the CT content was 42.2 μg/mg. The developed systems provided a two-phase drug release: about 50 % of the CT was released in 0.5–1 h, and about 60 % of the antibiotic was cumulatively released in 5 h. The antimicrobial activity of encapsulated CT was maintained at the same level as the pure drug for at least 24 h (minimum inhibitory concentration against Pseudomonas aeruginosa was 2 μg/mL for both). In addition, the apparent permeability coefficient of CT in the PEC formulation was 2.4 × 10−6 cm/s. Thus, the incorporation of CT into HA- and vitamin B12-modified CS-based PECs can be considered as a simple and convenient method to improve the oral delivery of CT.

Significantly Tunable Foaming Behavior of Blowing Agent for the Polyethylene Foam Resin with a Unique Designed Blowing Agent System.

The chemical blowing agent plays a crucial role in enhancing the performance of the polyethylene (PE) foaming resin during the rotational foaming process. Previously, the conventional blowing agent of the PE resin commonly used pure azodicarbonamide (AZ). It had the unavoidable drawbacks of releasing NH3 and exhibiting strong reactions during the rotational foaming process. Meantime, pure AZ had a relatively high decomposition temperature, resulting in a sharp foaming process. To address the above issues, this work developed a uniquely designed blowing agent system. In this study, a novel blowing agent for the PE resin was successfully synthesized by a one-pot method. This blowing agent consisted of an activator and AZ, which exhibited a lower decomposition temperature and a milder decomposition rate than AZ. The activator was constituted of small-sized ammonium dihydrogen phosphate on the AZ surface, which could be decomposed properly and deliver phosphoric acid and H2O during the foaming process. Then, AZ reacted with H2O under phosphoric acid catalysis. Also, this reaction generated CO2 emission while reducing the emission of NH3 through recombination with phosphoric acid. Moreover, phosphoric acid catalysis caused a decrease in the AZ decomposition temperature. Meantime, the thermal coupling appeared during the foaming process, which could further reduce the decomposition rate. Consequently, the small activator played a key role in regulating cell formation and diffusion. Compared to AZ, the novel blowing agent system significantly reduced the cell diameter of the PE foam resin and enhanced its flexural modulus by 50%. Furthermore, the novel blowing agent facilitated better demolding performance and improved the surface morphology of the PE foam product. This research provides significant foaming behavior regulation for the PE resin during industrial applications.

Development of a prototype of a theranostic system based on silica nanoparticles with immobilized fluorescent dyes and VEGF targeting ligand.

Background. Administration of certain drugs causes undesirable effects associated with the systemic effect of the active substance on the entire body. Selective targeting of the drug to the affected tissue promotes a selective increase in the concentration of the substance in the area of interest, thereby reducing the systemic effect and enhancing the local therapeutic effect.Objective. Development of a targeted delivery system for theranostic agents using recombinant human vascular endothelial growth factor type A (rhVEGF-A121) as a targeting ligand.Design and method. To create the theranostic complex, commercially available reagents were used: the recombinant protein rhVEGF-A121 (cat.#: PSG140-10, LLC CyStorLab, Skolkovo, Russia) and fumed silica Aerosil (A-200, Degussa AG, Germany). The tosyl spacer that interconnects both components was synthesized in the laboratory. Protein conjugation with fluorophores was also carried out in-house. Indocyanine green (ICG; Sigma-Aldrich, USA) and rhodamine B (JSC Lenreaktiv, St. Petersburg, Russia) were taken for immobilization.Results. In the course of the work, functionalization of silica nanoparticles (SiNPs) with a tosyl spacer was carried out, conjugates of SiNPs with rhVEGF-A121 were synthesized, and theranostic constructs based on SiNPs were obtained, including rhVEGF-A121 as a targeting ligand, and ICG/Rhodamine B as a visualizing label.Conclusion. In the presented study, a prototype of a complex for targeted delivery of a theranostic agent to tissues with an active angiogenesis process, for example, to tumor and ischemic tissues, was developed. To solve the problem, we immobilized on the surface of SiNP a recombinant protein of human vascular endothelial growth factor (rhVEGF) to use as a guide ligand. Such a synthetic construct will help to deliver diagnostic and/ or medicinal substances packed in SiNP directly to cells that overexpress extracellular specific receptors of the VEGFR family. In subsequent in vivo experiments, delivery efficiency will be assessed by tissue accumulation of the fluorophores ICG and rhodamine B, which have been conjugated to the targeting ligand protein. The physicochemical characteristics of the obtained samples were studied by the methods of spectrophotometry and dynamic light scattering.

Skill Development through Artificial Cognitive Systems and Social Robotics Applied at Tech-Education

The focus of this research is to demonstrate how a platform composed of systems of artificial cognitive agents and social robotics can interact, teach and learn with students and teachers, through a pedagogical practice and methodological integration of the psychological concepts of the Theory of Multiple Intelligences, the educational foundations of the Dialectic methodology and the relationship explored in the Man-Machine Symbiosis. The objective of this article is to present the cognitive methodological concept of the project developed, grounding it from the theoretical principles, to the selection criteria for the models presented in the current discussions, taking as lines of thought that seek to define the strategy for creating personalized learning storytelling, the techniques for building social robotics in education and the interactivity between visual feedback in the challenging context of technological education.

A security framework for mobile agent systems

A security framework for mobile agent systems

Functional structure of reflexive-active systems of artificial heterogeneous intelligent agents

The paper is aimed at developing distributed artificial intelligence systems for relevant simulation of collective solving of practical problems by modeling reflection. The paper presents the basic design principles and typical functional structure of reflexive-active systems of artificial heterogeneous intelligent agents. Agents of such systems mutually model each other’s reflexive positions; dynamically develop tactics and strategies for their behavior that are relevant to the models of their counterparties; if it is necessary during problem solving, attract new agents from the pool of available agents built by various developers and exclude existing ones, rebuilding “on the fly” the composition of agents and the structure of connections between them.

Inverse Value Iteration and Q -Learning: Algorithms, Stability, and Robustness.

This article proposes a data-driven model-free inverse Q -learning algorithm for continuous-time linear quadratic regulators (LQRs). Using an agent's trajectories of states and optimal control inputs, the algorithm reconstructs its cost function that captures the same trajectories. This article first poses a model-based inverse value iteration scheme using the agent's system dynamics. Then, an online model-free inverse Q -learning algorithm is developed to recover the agent's cost function only using the demonstrated trajectories. It is more efficient than the existing inverse reinforcement learning (RL) algorithms as it avoids the repetitive RL in inner loops. The proposed algorithms do not need initial stabilizing control policies and solve for unbiased solutions. The proposed algorithm's asymptotic stability, convergence, and robustness are guaranteed. Theoretical analysis and simulation examples show the effectiveness and advantages of the proposed algorithms.

Data-driven Agent-based Modeling: Experimenting with the Schelling’s Model

Agent-based modeling and simulation is a practical computational technique for studying complex systems of autonomous agents in various disciplines. Agent-based models facilitate the study of emergent phenomena by simulating heterogeneous agents and their flexible behaviors and interactions. However, developing an agent-based model of a complex system is often time-consuming and vulnerable to the modeler’s biases. Addressing this challenge requires a paradigm shift from knowledge-driven modeling to data-driven modeling. In this research, we initiate and experiment with automating the process of composing agent-based models by developing data-driven model extraction. To achieve this objective, we conduct experiments employing different variations of Schelling’s segregation model, a well-known agent-based model, each featuring different parameter sets and complexity levels.