Independent Operator Research Articles

Integration of biofuel-induced electricity generators (BEGs) with wearable biosensing devices

This review article explores the potential revolutionary uses of biofuel-induced electricity generators (BEGs) integrated into portable biosensing devices. It describes the workings, and benefits of BEGs-based biosensors while highlighting the complementary nature of energy production and biosensing. The article delves into the ways BEGs transform biosensing capabilities in wearable technology, highlighting their ability to sustain themselves, compatibility with living organisms, and ongoing power production. BEGs eliminate the need for external power sources by enabling independent and uninterrupted operation through the metabolic activity of microorganisms. Their compatibility with the human body guarantees a secure and pleasant on-body experience. Wearables that incorporate BEGs allow for the continuous tracking of ambient variables, physiological data, and biomarkers. The review highlights the exciting possibilities of BEGs based-biosensors in healthcare, environmental monitoring, and other fields, paving the way for autonomous, continuous monitoring in the future to enhance health management and raise environmental consciousness.

Basis for non-factorizable superamplitudes in N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 1 supersymmetry

In this paper we develop a semi-standard Young tableau (SSYT) approach to construct a basis of non-factorizable superamplitudes in N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 1 massless supersymmetry. This amplitude basis can be directly translated to a basis for higher dimensional supersymmetric operators, yielding both the number of independent operators and their form. We deal with distinguishable (massless) chiral/vector superfields at first, then generalize the result to the indistinguishable case. Finally, we discuss the advantages and disadvantages of this method compared to the previously studied Hilbert series approach.

Independent operations of appetitive and aversive conditioning systems lead to simultaneous production of conflicting memories in an insect.

Pavlovian conditioning is a ubiquitous form of associative learning that enables animals to remember appetitive and aversive experiences. Animals possess appetitive and aversive conditioning systems that memorize and retrieve appetitive and aversive experiences. Here, we addressed a question of whether integration of competing appetitive and aversive information takes place during the encoding of the experience or during memory retrieval. We developed novel experimental procedures to address this question using crickets (Gryllus bimaculatus), which allowed selective blockade of the expression of appetitive and aversive memories by injecting octopamine and dopamine receptor antagonists. We conditioned an odour (conditioned stimulus 1, CS1) with water and then with sodium chloride solution. At 24 h after conditioning, crickets retained both appetitive and aversive memories, and the memories were integrated to produce a conditioned response (CR). Importantly, when a visual pattern (CS2) was conditioned with CS1, appetitive and aversive memories formed simultaneously. This indicates that appetitive and aversive second-order conditionings are achieved at the same time. The memories were integrated for producing a conditioned response. We conclude that appetitive and aversive conditioning systems operate independently to form parallel appetitive and aversive memories, which compete to produce learned behaviour in crickets.

Asymmetric Nash bargaining model for operation optimization of multi-integrated energy systems considering peer-to-peer energy trading

Energy interactions across integrated energy systems constitute crucial means to enhance energy efficiency and match supply and demand. However, the cooperative operation and benefit distribution among multiple integrated energy systems still need in-depth exploration. To fill this gap, this paper presents an asymmetric Nash bargaining optimization model for multiple integrated energy systems considering peer-to-peer trading. First, a scheduling model for multi-integrated energy systems is formulated considering carbon trading. Then, the model is incorporated into Nash bargaining framework and transformed into the alliance cost minimization subproblem and peer-to-peer trading payment bargaining subproblem. The bargaining power factor is introduced to measure the contribution of participants in energy sharing. The alternating direction multiplier method is utilized to handle the proposed model. Finally, a case study is carried out to validate the validity of the proposed strategy. The results show that compared with the independent operation mode, the performances of three integrated energy systems in collaborative operation mode are enhanced by 11.7 %, 9.0 %, and 4.8 % respectively. The distributed algorithm can reduce the computation time by 30 % and obtain highly efficient solutions while protecting private information of each participant. This research provides support and practical tools for conducting peer-to-peer transactions of multiple integrated energy systems.

Making Switches: Key Strategic Decisions When Moving From a Local, Independent Operator to a Wholly Owned Subsidiary

ABSTRACTEntering a foreign market entails making the important mode decision of how to operate there. But the initial mode choice is not always forever and may be reassessed as business circumstances change. The mode shifting process—that is, how switches from one mode to another unfold—has scarcely been described, so we lack a systematic outline of this process. In this article, we take a first step toward such an outline. Adopting the established distinction between the formation and implementation phases of strategy making and execution, we describe the critical strategic decisions managers need to make about how to carry out a mode switch. Regarding the formation phases, we discuss the identification and consideration of entry mode switches as viable options, and whether companies plan or not for such shifts. Regarding the implementation phases, we differentiate between the integrating and collaborating decisions that define the type of switches made by companies.

Dimension-eight operator basis for universal standard model effective field theory

We present the basis of dimension-eight operators associated with universal theories. We first derive a complete list of independent dimension-eight operators formed with the Standard Model bosonic fields characteristic of such universal new physics scenarios. Without imposing C or P symmetries the basis contains 175 operators—that is, the assumption of universality reduces the number of independent Standard Model effective field theory (SMEFT) coefficients at dimension eight from 44807 to 175. 89 of the 175 universal operators are included in the general dimension-eight operator basis in the literature. The 86 additional operators involve higher derivatives of the Standard Model bosonic fields and can be rotated in favor of operators involving fermions using the Standard Model equations of motion for the bosonic fields. By doing so we obtain the allowed fermionic operators generated in this class of models which we map into the corresponding 86 independent combinations of operators in the dimension-eight basis of [C. W. Murphy, Dimension-8 operators in the standard model effective field theory, .]. Published by the American Physical Society 2024

Integrated scheme analysis and thermodynamic performance study of advanced nuclear-driven hydrogen-electricity co-production systems with iodine-sulfur cycle and combined cycle

A promising method for massive clean hydrogen production is the Very High Temperature Reactor (VHTR)-driven Nuclear Hydrogen Production (NHP) system using the Iodine–Sulfur (IS) cycle. Research on integrated scheme and thermodynamic performance of the VHTR-driven NHP system using the IS cycle has, however, received little attention up to this point, particularly when the combined cycle is employed as the power generation cycle. In order to bridge this research gap, this work proposed and studied two distinct VHTR-driven hydrogen-electricity co-production systems with the IS cycle and combined cycle: the independent operating system and the coupled operating system. Thermodynamics was used to model these two systems, and system thermodynamic performance was examined under the baseline operating conditions. A parametric study was further conducted on how two important operating parameters affected system thermodynamic performance. The primary findings indicated that the coupled operating system outperformed the independent operating system in terms of thermodynamic performance. Additionally, both the independent and coupled operating systems could produce hydrogen at the same rate of 289.8 mol/s, with net electrical power outputs of 61.07 MW and 102.7 MW, respectively, under the baseline operating conditions. Furthermore, it was discovered that a rise in the mass flow ratio for both operating systems would result in a notable reduction in system efficiency.

The Influence of The Use of Audio-Visual Media on The Ability of Fraction Calculation Operations of Grade IV Students of SD Negeri 4 Amparita Sidrap

This study examines the effect of the use of audio-visual media on the ability of fraction calculation operations of fourth grade students of SD Negeri 4 Amparita. The main problem studied is whether there is a positive influence of audio-visual media on the ability of fraction calculation operations of fourth grade students of SD Negeri 4 Amparita. This study is an experimental research that aims to determine whether there is a positive effect of audiovisual media on the ability of fraction calculation operations of fourth grade students of SD Negeri 4 Amparita Sidrap on the material of addition and subtraction of fractions. This research uses a quantitative approach. This study consists of two variables, namely audiovisual media and conventional models as independent variables and students' fraction calculation operation skills as the dependent variable, using the Randomized Subject Pretest-Posttest Control Group Design research design. The population in this study were all 4th grade students of SD Negeri 4 Amparita consisting of 1 class with a total sample of 42 people. The research sample of class IVA as an experimental class with 21 students and Class IVB with 21 students who were selected by Random Class. The data obtained were analyzed with descriptive statistics and inferential statistics. The results of descriptive analysis showed that the average value of fraction calculation ability of experimental class students was 75.71 and the average value of fraction calculation ability of control class students was 60.48. The learning completeness of experimental class students was 85.95% while the learning completeness of control class students was 47.61%. Inferential statistical analysis to test the hypothesis through Independent Sample T-tests obtained the value of -t count < - t table (-3.678 < -2.021) or t count > t table (3.678 > 2.021) thus H0 is rejected and H1 is accepted. In this case, audio-visual media has a positive effect on the ability of fraction calculation operations of fourth grade students of SD Negeri 4 Amparita Sidrap.

A coordinated operation method of wind-PV-hydrogen- storage multi-agent energy system

Wind-photovoltaic (PV)-hydrogen-storage multi-agent energy systems are expected to play an important role in promoting renewable power utilization and decarbonization. In this study, a coordinated operation method was proposed for a wind-PV- hydrogen-storage multi-agent energy system. First, a coordinated operation model was formulated for each agent considering peer-to-peer power trading. Second, a coordinated operation interactive framework for a multi-agent energy system was proposed based on the theory of the alternating direction method of multipliers. Third, a distributed interactive algorithm was proposed to protect the privacy of each agent and solve coordinated operation strategies. Finally, the effectiveness of the proposed coordinated operation method was tested on multi-agent energy systems with different structures, and the operational revenues of the wind power, PV, hydrogen, and energy storage agents of the proposed coordinated operation model were improved by approximately 59.19%, 233.28%, 16.75%, and 145.56%, respectively, compared with the independent operation model.

The Path of the Reformed Church in Elizabeth

The Hungarian Reformed Church in Elizabeth, New Jersey operated for about sixty years. The congregation was established by Hungarian immigrants to the United States of America in the late 19th and early 20th centuries. On 21 May 1914, the church became member of the Presbyterian Church in the United States of America. The close-knit community had an active religious and social life and became an important meeting place for local Hungarians. The congregation, which had become financially independent, organized a number of charity events to finance their own expenses, missionary goals, and fundraising activities. It was also important for the congregation to cultivate its Hungarian roots. In the 1970s, it had to cease independent operation partly due to the assimilation of the second and third generations and partly because of urban planning due to the change in the social composition of the town. Rev. Bertalan Szathmáry, a pastor who had previously served in the Elizabeth congregation for several years, gathered the leaderless Newark congregants and founded a new congregation in Union. Keywords: Hungarian Reformed Church, Elizabeth (New Jersey, USA), Presbyterian Church

Improved Message Mechanism-Based Cross-Domain Security Control Model in Mobile Terminals

Dual-domain terminal with two built-in independent operating systems - Life Domain and Work Domain, provides convenience for daily use and mobile office. However, the security isolation between the two domains also causes that message reminders cannot be delivered and viewed across domains, which restricts the improvement of work efficiency and the expansion of mobile services. This paper conducts an in-depth study on this pain point and proposes the concept and implementation method of a cross-domain instant messaging reminder service system for mobile office, focusing on solving the problems of: cross-domain isolated boundary exchange of message reminders, timeliness and delivery rate guarantee of message reminders, and security check filtering of message contents. Technically, on the side of mobile office platform, based on AMQP technical framework and protocol, the cross-domain isolated border message queue push and synchronization services are built, which are real-time, reliable and high-throughput.

HEROIC: a platform for remote collection of electroencephalographic data using consumer-grade brain wearables

The growing number of portable consumer-grade electroencephalography (EEG) wearables offers potential to track brain activity and neurological disease in real-world environments. However, accompanying open software tools to standardize custom recordings and help guide independent operation by users is lacking. To address this gap, we developed HEROIC, an open-source software that allows participants to remotely collect advanced EEG data without the aid of an expert technician. The aim of HEROIC is to provide an open software platform that can be coupled with consumer grade wearables to record EEG data during customized neurocognitive tasks outside of traditional research environments. This article contains a description of HEROIC’s implementation, how it can be used by researchers and a proof-of-concept demonstration highlighting the potential for HEROIC to be used as a scalable and low-cost EEG data collection tool. Specifically, we used HEROIC to guide healthy participants through standardized neurocognitive tasks and captured complex brain data including event-related potentials (ERPs) and powerband changes in participants’ homes. Our results demonstrate HEROIC’s capability to generate data precisely synchronized to presented stimuli, using a low-cost, remote protocol without reliance on an expert operator to administer sessions. Together, our software and its capabilities provide the first democratized and scalable platform for large-scale remote and longitudinal analysis of brain health and disease.

Multifunctional Intelligent Metamaterial Computing System: Independent Parallel Analog Signal Processing

Analog computing based on miniaturized surfaces has gained attention for its high‐speed and low‐power mathematical operations. Building on recent advances, an anisotropic space‐time digital metasurface for parallel and programmable wave‐based mathematical operations is proposed. Using frequency conversions, our metasurface performs 1st‐order and 2nd‐order spatial differentiations, integrodifferential equations, and sharp edge detection in spatially encoded images. The anisotropic nature of the meta‐particle enables independent and simultaneous operations for two orthogonal polarizations. Reconfigurability is achieved through tunable gate biasing of an indium tin oxide layer. Illustrative examples demonstrate that the metasurface's output signals and transfer functions closely match ideal transfer functions, confirming its versatility and effectiveness. Unlike other wave‐based signal processors, the design handles wide spatial frequency bandwidths, even with high spatial frequency inputs.

Compact In Situ Electrochemical NMR with Wireless and Anti-interference Strategy in Multiscenario Applications.

The integration of electrochemistry with nuclear magnetic resonance (NMR) spectroscopy recently offers a powerful approach to understanding oxidative metabolism, detecting reactive intermediates, and predicting biological activities. This combination is particularly effective as electrochemical methods provide excellent mimics of metabolic processes, while NMR spectroscopy offers precise chemical analysis. NMR is already widely utilized in the quality control of pharmaceuticals, foods, and additives and in metabolomic studies. However, the introduction of additional and external connections into the magnet has posed challenges, leading to signal deterioration and limitations in routine measurements. Herein, we report an anti-interference compact in situ electrochemical NMR system (AICISENS). Through a wireless strategy, the compact design allows for the independent and stable operation of electrochemical NMR components with effective interference isolation. Thus, it opens an avenue toward easy integration into in situ platforms, applicable not only to laboratory settings but also to fieldwork. The operability, reliability, and versatility were validated with a series of biomimetic assessments, including measurements of microbial electrochemical systems, functional foods, and simulated drug metabolisms. The robust performance of AICISENS demonstrates its high potential as a powerful analytical tool across diverse applications.

Multiplexed All‐Optical Permutation Operations Using a Reconfigurable Diffractive Optical Network

AbstractLarge‐scale and high‐dimensional permutation operations are important for various applications in, for example, telecommunications and encryption. Here, all‐optical diffractive computing is used to execute a set of high‐dimensional permutation operations between an input and output field‐of‐view through layer rotations in a diffractive optical network. In this reconfigurable multiplexed design , every diffractive layer has four orientations: , , , and . Each unique combination of these layers represents a distinct rotation state, tailored for a specific permutation operation. Therefore, a K‐layer rotatable diffractive design can all‐optically perform up to independent permutation operations. The original input information can be decrypted by applying the specific inverse permutation matrix to output patterns. The feasibility of this reconfigurable multiplexed diffractive design is demonstrated by approximating 256 randomly selected permutation matrices using = 4 rotatable diffractive layers. To further enhance its multiplexing capability, input polarization diversity is also utilized. Additionally, this reconfigurable diffractive design is experimentally validated using terahertz radiation and 3D‐printed diffractive layers, providing a decent match to numerical results. The presented rotation‐multiplexed diffractive processor is particularly useful due to its mechanical reconfigurability, offering multifunctional representation through a single fabrication process.

P-206 Unveiling the elasticity of zona pellucida: shifting focus to a neglected embryonic feature

Abstract Study question Is it feasible to quantitatively assess the elasticity of the zona pellucida, and how does this measurement correlate with blastocyst features? Summary answer The elasticity of the zona pellucida can be quantitatively evaluated, demonstrating a correlation with distinct developmental stages and morphological features of blastocysts. What is known already Embryologists have primarily focused on assessing morphokinetic and morphological features of embryos to enhance success rates in assisted reproduction technology cycles. However, the zona pellucida (ZP) has often been overlooked as a potential marker of embryonic quality. Previous studies have established a correlation between the thickness of the ZP and implantation rates in cleavage-stage embryos. Yet, the comprehensive attributes of the ZP in blastocysts remain under-explored, with critical aspects such as its elasticity receiving scant attention. Study design, size, duration A retrospective analysis was conducted on 254 blastocysts from 103 patients. For each blastocyst, two images were captured: one prior to and another following lased-induced artificial shrinkage. This study focused on assessing ZP elasticity by comparing its thickness during blastocele pressure-induced distension and subsequent to blastocyst collapse. Variations in thickness were interpreted as reflections of pressure release. To ensure the reliability and accuracy of data, measurements were performed by two independent operators. Participants/materials, setting, methods Measurements were performed using ImageJ software. Operators executed twelve radial assessments of ZP thickness at 30-degree intervals and three additional measurements of the area within the ZP. These measurements were averaged for analysis. The ZP re-expansion percentage post-laser collapse was determined by comparing the change in thickness relative to the initial thickness. Linear regression and Spearman’s correlation were employed to examine the relationships among ZP re-expansion, thickness, enclosed area, patient age, and blastocyst features. Main results and the role of chance The average ZP thickness prior to freezing (Pre-ZPT) was 5.1 ± 2.0 micrometers, increasing to 8.6 ± 2.0 micrometers following collapse. The mean blastocyst diameter at the time of freezing was 192 ± 17 micrometers, with ZP re-expansion averaging 82.1%. A strong correlation was observed between Pre-ZPT and post-collapse thickness, with a coefficient of 0.75 (P = 4.8 × 10−47). Pre-ZPT showed a significant inverse and non-linear relationship with pre-collapse blastocyst diameter (Pre-BD), as assessed by Spearman’s correlation (P value: 2.9 × 10−³¹). Additionally, a linear correlation was observed between Pre-BD and the percentage of ZP re-expansion post-collapse (P value: 3.8 × 10−²¹). Given the strong interdependence of these parameters, reflecting expected behavior from a semi-elastic sheath undergoing stretching, linear correlation between Pre-BD and re-expansion percentage was used to define ZP elasticity. Deviations from average behavior were normalized into percentiles and analyzed against patient age and blastocyst characteristics. Multivariate regression, adjusted for variables including Pre-ZPT, revealed a strong inverse association between blastocyst elasticity and freezing day, with a decrease of 16.8 percentiles on average (P value: 4.9 × 10−6). Conversely, a positive association was identified with poor-quality blastocysts, which showed an average increase of 12.4 percentiles in elasticity (P value: 1.5 × 10−³). No significant correlation emerged between ZP elasticity and patient age Limitations, reasons for caution This preliminary study was limited to the evaluation of the morphological and developmental characteristics of blastocysts, without delving into clinical outcomes. It is critical to note that blastocyst quality assessment is influenced by operator interpretation, which introduces a degree of variability into the morphological evaluation process. Wider implications of the findings Evaluating the elasticity of the ZP, a relatively unexplored aspect, might provide insights into its predictive value of blastocyst competence and subsequent successful clinical outcomes following embryo transfer. Such an analysis could significantly enrich our understanding of embryonic reproductive competence. Trial registration number not applicable

Exploring the Practical Applications of Artificial Intelligence, Deep Learning, and Machine Learning in Maxillofacial Surgery: A Comprehensive Analysis of Published Works.

Artificial intelligence (AI), deep learning (DL), and machine learning (ML) are computer, machine, and engineering systems that mimic human intelligence to devise procedures. These technologies also provide opportunities to advance diagnostics and planning in human medicine and dentistry. The purpose of this literature review was to ascertain the applicability and significance of AI and to highlight its uses in maxillofacial surgery. Our primary inclusion criterion was an original paper written in English focusing on the use of AI, DL, or ML in maxillofacial surgery. The sources were PubMed, Scopus, and Web of Science, and the queries were made on the 31 December 2023. The search strings used were "artificial intelligence maxillofacial surgery", "machine learning maxillofacial surgery", and "deep learning maxillofacial surgery". Following the removal of duplicates, the remaining search results were screened by three independent operators to minimize the risk of bias. A total of 324 publications from 1992 to 2023 were finally selected. These were calculated according to the year of publication with a continuous increase (excluding 2012 and 2013) and R2 = 0.9295. Generally, in orthognathic dentistry and maxillofacial surgery, AI and ML have gained popularity over the past few decades. When we included the keywords "planning in maxillofacial surgery" and "planning in orthognathic surgery", the number significantly increased to 7535 publications. The first publication appeared in 1965, with an increasing trend (excluding 2014-2018), with an R2 value of 0.8642. These technologies have been found to be useful in diagnosis and treatment planning in head and neck surgical oncology, cosmetic and aesthetic surgery, and oral pathology. In orthognathic surgery, they have been utilized for diagnosis, treatment planning, assessment of treatment needs, and cephalometric analyses, among other applications. This review confirms that the current use of AI and ML in maxillofacial surgery is focused mainly on evaluating digital diagnostic methods, especially radiology, treatment plans, and postoperative results. However, as these technologies become integrated into maxillofacial surgery and robotic surgery in the head and neck region, it is expected that they will be gradually utilized to plan and comprehensively evaluate the success of maxillofacial surgeries.

Implementasi Prinsip – Prinsip Good Corporate Governance (GCG) pada Bank Syariah Indonesia KCP.Panyabungan Mandailing Natal

This study aims to evaluate the application of the principles of Good Corporate Governance (GCG) at Bank Syariah Indonesia Kcp. Panyabungan Mandailing Natal. The implementation of GCG is very important for Islamic banks to ensure transparent, accountable, responsible, independent, and fair operations, in accordance with sharia principles. The research method used is a qualitative approach with a descriptive method, involving interviews with bank staff and direct observation at the research location. The results showed that Bank Syariah Indonesia Kcp. Panyabungan has implemented GCG principles well. Transparency is evident from the disclosure of accurate and timely information. Accountability is realized through the supervision and accountability of the board of commissioners and directors. The bank complies with laws and regulations and sharia principles as part of its responsibility. Independence is achieved through decision-making that is free from external pressure, while fairness is reflected in fair treatment to all stakeholders. Although the results show good GCG implementation, there is a need to continue strengthening GCG implementation to maintain the integrity and sustainability of the bank in the long run.

Exploring the essential features influencing the synthesis of methylenedianiline to support industrial processes

The most important intermediate of methylene diphenyl diisocyanate (MDI), the most widely and quantitatively produced isocyanate in the world, is methylenedianiline (MDA). MDA is industrially produced from the reaction of aniline and formaldehyde catalysed by inorganic acids, most commonly HCl. The reaction parameters used during the synthesis of MDA have a fundamental impact on the quality parameters of the resulting MDA product mixture, and thus on the properties of the final MDI product mixture as well. Although MDA is an important industrial intermediate, currently its synthesis at the industrial level is based on empirical rules, knowledge and rule of thumbs, the effects of production parameters and their magnitude on product properties are not known and not published in the literature. In this study, the correlations between the independent operating parameters and dependent product quality parameters characterizing the MDA mixture were explored by developing different regression models with the use of experimental laboratory synthesis data in order to support the industrial synthesis process with easily deployable models with satisfactorily high accuracy. After investigating the laboratory experiment data from a total of 46 individual laboratory experiments, it was found that with machine learning models almost all of the independent parameters can be described with satisfactory accuracy. The models presented in this work demonstrate that it is possible to develop models that can be used to adjust the ring distribution, isomer ratios and selectivity of the reaction with minimising by-product quantities according to market demands or to different objective functions by fine-tuning the production parameters., thus achieving an optimal product portfolio and operating cost for the industrial process as well.

Smart Cities towards Artificial Intelligence

The creation of smart cities has come a long way in recent years, especially in domains that use AI, such IoT-based components, security systems, smart living options, and environmental monitoring. These advancements seek to build surroundings that meet human requirements by utilizing cutting edge technologies such as automated parking, smart healthcare, and seismic monitoring systems. Even with these encouraging advancements, the current generation of smart cities is still unable to attain genuine autonomy, particularly when it comes to component-level autonomous situation management and decision-making. The transformational perspective proposed in this work views the constituent components of smart environments as self-governing agents with the ability to make decisions. The purpose of these autonomous agents is to improve security and smart living by being able to self-manage and react automatically to different situations. Such autonomous agents can be integrated to accomplish the goal of artificially intelligent smart cities. In smart cities, autonomous agents may behave pro-actively without human involvement by continually monitoring and analyzing data, anticipating possible problems, and taking proactive actions. In the context of smart healthcare, these agents may, for example, track a patient's vitals in real time, anticipate possible health emergencies, notify medical personnel, or even start emergency procedures. Autonomous agents may dynamically assign parking spots in the context of smart car parking based on real-time data, maximizing space use and minimizing traffic congestion. Agents that can autonomously manage emergency actions, such as directing people to safety and managing infrastructure to minimize damage, might be beneficial for earthquake detecting systems. As autonomous entities endowed with decision-making skills are included, we are moving closer to truly intelligent cities. Because of these agents' capacity for independent operation and quick response to changing circumstances, smart cities are able to offer a better quality of security and service while accommodating the changing demands of its residents. As a result, smart cities that have these intelligent agents installed will be more responsive, efficient, and resilient—ultimately capturing the spirit of artificial intelligence in urban planning.