Autonomous Entities Research Articles

Proud to be not beautiful: navigating affects in the rebellious body project of Chinese TuoMeiYi feminism

ABSTRACT In recent years, TuoMeiYi (escaping beauty duty) has emerged in the Chinese digital space as a distinct feminist proposition. Advocating for women to break free from the constraints of beauty, TuoMeiYi feminists strive to redefine what a woman should look like, and actively practice their anti-beauty stance by shaving their hair into buzz cuts. This everyday feminist politics attempts to reclaim women’s autonomy over their bodies by transforming their feminist body into a rebellious project. Diverging from the prevalent media discursive approach in Chinese digital feminism studies, this article examines TuoMeiYi feminists’ explorative body project through the lens of affect grounded in corporeal and phenomenological feminist theories. Using digital ethnography to explore an online TuoMeiYi forum, this article recognizes that pride and shame have been discursively mobilized as pivotal tools to sustain the anti-beauty feminist ideal. Yet, the construction of the proud feminist subject also involves a highly self-autonomous logic that tries to eliminate feminist embodied feelings. In the end, this article argues that it is not ‘feeling good’ but the ‘strange feelings’ that demonstrate the feminist body is neither a docile nor consciously autonomous entity, but a rebellious affective being capable of feeling in unplanned alternative ways.

Affect in Literary Translations: What is at Stake for the Author and the Translator

This article explores the relationships between authors, translators, and readers within the context of literature and translation. Emphasising the reciprocal influence between texts, it delves into the desire of writers to control the interpretation of their works during translation. The examination extends to the hierarchy within literature and translation, questioning whether a translated text can be considered an autonomous entity and if translators can be acknowledged as authors considering the transformative nature of translation and the subjective, creative processes involved. The article also sheds light on the emotional and affective aspects involved in the translation process, highlighting the recurring theme of trust and the fear of translatorial non-compliance. Through examples, it demonstrates how authors can actively engage in the translation process to safeguard their narrative nuances. Case studies, including instances involving Umberto Eco, Guillermo Cabrera Infante, Carlos Fuentes, and Günter Grass, illustrate various levels of authorial control and collaboration. The discussion expands to the global literary landscape, emphasising the dominance of certain languages and the dynamics between the literary centre and periphery. Ultimately, it raises fundamental questions about authorship, control, and the transformative power of translation in shaping the “world republic of letters”. The article investigates the multifaceted dynamics between authors and translators, examining collaboration along a continuum from carte blanche to conflictual relationships. The extent of an author’s involvement in the translation process is explored, questioning the reasons behind some authors’ keen interest in ensuring accurate translations. The power imbalances within collaborations are scrutinised, raising questions about the translator’s agency. The article concludes with reflections on the challenges and potential pitfalls of authors participating in the translation of their own works, emphasising the inherent plurality of interpretations in the act of translation.

From Bench to Bedside With Large Language Models: AJR Expert Panel Narrative Review.

Large language models (LLMs) hold immense potential to revolutionize radiology. However, their integration into practice requires careful consideration. Artificial intelligence (AI) chatbots and general-purpose LLMs have potential pitfalls related to privacy, transparency, and accuracy, limiting their current clinical readiness. Thus, LLM-based tools must be optimized for radiology practice to overcome these limitations. Although research and validation for radiology applications remain in their infancy, commercial products incorporating LLMs are becoming available alongside promises of transforming practice. To help radiologists navigate this landscape, this AJR Expert Panel Narrative Review provides a multidimensional perspective on LLMs, encompassing considerations from bench (development and optimization) to bedside (use in practice). At present, LLMs are not autonomous entities that can replace expert decision-making, and radiologists remain responsible for the content of their reports. Patient-facing tools, particularly medical AI chatbots, require additional guardrails to ensure safety and prevent misuse. Still, if responsibly implemented, LLMs are well-positioned to transform efficiency and quality in radiology. Radiologists must be well-informed and proactively involved in guiding the implementation of LLMs in practice to mitigate risks and maximize benefits to patient care.

Developing an ensemble machine learning study: Insights from a multi-center proof-of-concept study.

To address the numerous unmeet clinical needs, in recent years several Machine Learning models applied to medical images and clinical data have been introduced and developed. Even when they achieve encouraging results, they lack evolutionary progression, thus perpetuating their status as autonomous entities. We postulated that different algorithms which have been proposed in the literature to address the same diagnostic task, can be aggregated to enhance classification performance. We suggested a proof of concept to define an ensemble approach useful for integrating different algorithms proposed to solve the same clinical task. The proposed approach was developed starting from a public database consisting of radiomic features extracted from CT images relating to 535 patients suffering from lung cancer. Seven algorithms were trained independently by participants in the AI4MP working group on Artificial Intelligence of the Italian Association of Physics in Medicine to discriminate metastatic from non-metastatic patients. The classification scores generated by these algorithms are used to train SVM classifier. The Explainable Artificial Intelligence approach is applied to the final model. The ensemble model was validated following an 80-20 hold-out and leave-one-out scheme on the training set. Compared to individual algorithms, a more accurate result was achieved. On the independent test the ensemble model achieved an accuracy of 0.78, a F1-score of 0.57 and a log-loss of 0.49. Shapley values representing the contribution of each algorithm to the final classification result of the ensemble model were calculated. This information represents an added value for the end user useful for evaluating the appropriateness of the classification result on a particular case. It also allows us to evaluate on a global level which methodological approaches of the individual algorithms are likely to have the most impact. Our proposal represents an innovative approach useful for integrating different algorithms that populate the literature and which lays the foundations for future evaluations in broader application scenarios.

A design solution for a self-guarding robot based on tube worm behavior

Tubeworms establish benthic habitats in the abyssal zones through the aggregation of extensive clusters of chitinous tubes, embodying sessile, tubicolous organisms that engage in filter feeding. The anterior extremity of these organisms is morphologically adapted into tentacle which are capable of retracting into the organisms body at a remarkable velocity when receiving external stimulation. This high speed relies on fan worms lubricant and strong vertical muscles. This adaptive behavior of tubeworms has served as an inspiration for the Long-term underwater detector robot. Despite the prevailing focus of extant research on the intrinsic characteristics of underwater sensors, such as precision and interactivity, there remains oversight regarding the preservation of high-value and inherently delicate sensors within subaquatic robotic carriers. In response to this lacuna, the paper proposes a novel device of an autonomous robotic entity designed to reflexively retract its sensory apparatus in reaction to environmental stimulation. The solutions presented are designed for long-term underwater robots which are subject to frequent external disturbances. The shell has been designed by means of a multilayer sheath structure of a fan worm and a retraction mechanism has been designed. Solidwork is used to model the robot and apdl is employed to simulate the strength stiffness of key structures. As a result of the modelling and simulation analyses, the possibility and practicality of this self-guarding robot have been determined. It is posited that the robotic apparatus harbors a potential for application in domains such as subaqueous surveillance, bathymetric resource exploration, and aquatic quality assessment. Prospective avenues for further scholarly inquiry encompass an augmentation of the investigation into the locomotive capabilities of the robot, alongside enhancements to its autogenic safeguarding mechanisms. These advancements may help to amplify the reliability of the device within severe and abyssopelagic conditions.

POLITICAL INTERNET MEMES: A LINGUISTIC PERSPECTIVE

The article is devoted to the analysis of the phenomenon of memes, which are a controversial aspect of modern communication, the subtleties of which have not yet been studied. The analysis of language material shows that the combination of verbal and non-verbal components of memes creates an autonomous information entity that is capable of self-reproduction of the representation of a linguistic personality at the phonetic, lexical, grammatical, cognitive and pragmatic levels in political discourse. In this realm, the concept of the “political internet meme” emerges, denoting a specialized form of political discourse that combines visual and verbal components to sway an audience into the realm of political communication. These memes combine traditional political terminology with colloquial vocabulary strategically designed to achieve persuasive goals. Generally, political internet memes are created through affixation and the use of simplified grammatical structures without articles, often intentionally including spelling and grammatical errors to increase their impact. In pursuit of a comedic effect, the creators of political Internet memes use a whole arsenal of stylistic and linguistic means. These include complex wordplay involving phonetic and morphological manipulations, various expressive techniques, and playful experiments with typography and punctuation. Thanks to such means, memes go beyond the simple transmission of information, turning into powerful tools of political expression and persuasion.

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.

Assessing the Role and Future of the Tax Court Post-MK Decision No. 26PUU-XXI2023

Taxation, as a fundamental component of the system of cooperation, serves as a financial resource to underpin governmental financing and expenditure while also acting as an instrument for the regulation of social and economic policies aimed at promoting equitable welfare. The process of tax collection occasionally engenders inequities for taxpayers; consequently, Law 14 of 2002 instituted the Tax Court as an autonomous judicial entity designated for the adjudication of tax-related disputes. Notwithstanding its establishment, the Tax Court encounters significant challenges, notably the dualism of authority wherein the Supreme Court provides technical guidance. At the same time, the Ministry of Finance oversees organizational, administrative, and financial directives. In the Constitutional Court's Decision (MK) Number 26/PUU-XXI/2023, the regulation pertaining to the oversight of the Tax Court was deemed inconsistent with Article 24, paragraphs (1) and (2) of the 1945 Constitution, prompting the Constitutional Court to impose a deadline of December 31, 2026, for the consolidation of the Tax Court's guidance authority under the auspices of the Supreme Court. Consequently, this research endeavours to scrutinize the role and prospective trajectory of the Tax Court alongside the measures necessary to effectuate the transfer of guidance authority in alignment with constitutional mandates. Hence, the author has entitled this study "Measuring the Role and Future of the Tax Court after the Constitutional Court Decision Number 26/PUU-XXI/2023." The questions posed for investigation are: What is the Role and Position of the Tax Court as delineated by the Tax Court Law, and what is the Role and Future of the Tax Court subsequent to the Constitutional Court Decision (Number 26/PUU-XXI/2023)? To address these inquiries, the author employs a qualitative writing methodology complemented by a normative legal perspective.

Tool-Augmented Human Creativity

Creativity is the hallmark of human intelligence. Roli et al. (Frontiers in Ecology and Evolution 9:806283, 2022) state that algorithms cannot achieve human creativity. This paper analyzes cooperation between humans and intelligent algorithmic tools to compensate for algorithms’ limited creativity. The intelligent tools have functionality from the neocortex, the brain’s center for learning, reasoning, planning, and language. The analysis provides four key insights about human-tool cooperation to solve challenging problems. First, no neocortex-based tool without feelings can achieve human creativity. Second, an interactive tool exploring users’ feeling-guided creativity enhances the ability to solve complex problems. Third, user-led abductive reasoning incorporating human creativity is essential to human-tool cooperative problem-solving. Fourth, although stakeholders must take moral responsibility for the adverse impact of tool answers, it is still essential to teach tools moral values to generate trustworthy answers. The analysis concludes that the scientific community should create neocortex-based tools to augment human creativity and enhance problem-solving rather than creating autonomous algorithmic entities with independent but less creative problem-solving.

Confluence of Random Walks, Interacting Particle Systems, and Distributed Machine Learning: Federated Learning through Crawling over Networks

In this work, we aim to unveil a new class of intermediate FL architectures between centralized and decentralized schemes called “FedCrawl.” FedCrawl takes advantage of benefits of D2D communications similar to decentralized schemes; however, it uses them in a nuanced way. FedCrawl is inspired by web crawlers, which effectively explore the websites to find updated/new content posted on the internet. The cornerstone of FedCrawl is its innovative conceptualization of neural networks (NNs) or other used ML models as autonomous entities, called random walkers, with the capability to move or jump across nodes in the network through peer-to-peer (P2P) or device-to-device (D2D) connections. We introduce five research aspects to study the nuanced intricacies governing random walker behavior in these environments. The first research aspect addresses the interplay between network topology and data distribution, emphasizing the importance of considering both factors for designing efficient random walks in FedCrawl. The second research aspect explores the applicability of node importance metrics in optimizing random walker paths for FedCrawl. We propose a dynamic perception-aware design, discussed in the third research aspect, where transition matrices adapt to the evolving state of random walkers, balancing exploration and exploitation. The fourth research aspect introduces innovative features like skipping, memory look-back, and caching/trailing to enhance random walker performance. Lastly, the fifth research aspect delves into the dynamics of multiple random walkers in networked environments, introducing the concept of multi-pole random walkers. Complementing these five research aspects, we present five conjectures, each introducing novel perspectives and methodologies in the domain of decentralized learning. These conjectures encompass areas such as temperature-based characterization of random walkers and network nodes, dynamic transition matrices, non-Markovian processes, and an evolutionary framework for random walker patterns.

“Use” as a Conscious Thought: Towards a Theory of “Use” in Autonomous Things

The way users perceive and use information systems artefacts has been mainly studied from the notion of behavioral beliefs, deliberate cognitive efforts, and physical actions performed by human actors to produce certain outcomes. The next generation of information systems, however, can sense, respond, and adapt to environments without necessitating similar cognitive efforts, physical contact, or explicit instructions to operate. Therefore, by leveraging theories of consciousness and technology use, this research aims to advance an alternative understanding of the "use" associated with the next generation of IS artefacts that do not require deliberate cognitive efforts, physical manipulation, or explicit instructions to yield outcomes. The theory and proposed model were refined and validated through the burst detection technique, IS expert involvement (n=10), a pilot study (n=130), and end-user surveys (n= 119). Structural equating modelling techniques were employed to test the theory. We show that unlike the manually operated IS artefacts, the “use” of a fully autonomous artefact is a conscious thought rather than a physical activity of operating a system to produce certain outcomes. We argue that, unlike the traditional notions of use associated with manually operated technologies, conscious use is not characterized solely by behavioral beliefs stemming from logical and reflective cognitive and physical efforts (e.g., effort expectancy). We propose the notion of conscious use within the context of fully autonomous entities and empirically validate its measure. Additionally, we offer recommendations for future research directions in this area. The conceptualization of this new theory for fully autonomous IS artefacts adds significant academic value to the literature given the convergence of AI-based machine learning systems and cognitive computing systems.

Therapy-Related Myeloid Neoplasm: Biology and Mechanistic Aspects of Malignant Progression.

Therapy-related myeloid neoplasms (t-MN) arise after a documented history of chemo/radiotherapy as treatment for an unrelated condition and account for 10-20% of myelodysplastic syndromes and acute myeloid leukemia. T-MN are characterized by a specific genetic signature, aggressive features and dismal prognosis. The nomenclature and the subsets of these conditions have changed frequently over time, and despite the fact that, in the last classification, they lost their autonomous entity status and became disease qualifiers, the recognition of this feature remains of major importance. Furthermore, in recent years, extensive studies focusing on clonal hematopoiesis and germline variants shed light on the mechanisms of positive pressure underpinning the rise of driver gene mutations in t-MN. In this manuscript, we aim to review the evolution of defining criteria and characteristics of t-MN from a clinical and biological perspective, the advances in mechanistic aspects of malignant progression and the challenges in prevention and management.

On the power of bounded asynchrony: convergence by autonomous robots with limited visibility

A distributed algorithm A\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {A}}$$\\end{document} solves the Point Convergence task if an arbitrarily large collection of entities, starting in an arbitrary configuration, move under the control of A\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {A}}$$\\end{document} to eventually form and thereafter maintain configurations in which the separation between all entities is arbitrarily small. This fundamental task in the standard OBLOT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {OBLOT}$$\\end{document} model of autonomous mobile entities has been previously studied in a variety of settings, including full visibility, exact measurements (including distances and angles), and synchronous activation of entities. Our study concerns the minimal assumptions under which entities, moving asynchronously with limited and unknown visibility range and subject to limited imprecision in measurements, can be guaranteed to converge in this way. We present an algorithm operating under these constraints that solves Point Convergence, for entities moving in two or three dimensional space, with any bounded degree of asynchrony. We also prove that under similar realistic constraints, but unbounded asynchrony, Point Convergence in the plane is not possible in general, contingent on the natural assumption that algorithms maintain the (visible) connectivity among entities present in the initial configuration. This variant, that we call Cohesive Convergence, serves to distinguish the power of bounded and unbounded asynchrony in the control of autonomous mobile entities, settling a long-standing question whether in the Euclidean plane synchronously scheduled entities are more powerful than asynchronously scheduled entities.

Advanced Data Science Applications in Vehicles: A Comprehensive Review

Purpose: This research paper aims to explore the transformative impact of data science applications within the automotive industry, with a focus on the evolution of vehicles into intelligent, connected, and autonomous entities. Through an extensive literature review and analysis of recent developments, the paper seeks to provide a comprehensive understanding of the current state and future prospects of data science in vehicles.
 Methodology: Advancements in sensor technologies, such as LiDAR, HD maps, radars, location tracking and cameras, are discussed, highlighting their role in data collection for applications like advanced driver assistance systems (ADAS) and autonomous driving. Relevant citations are provided. This subsection covers the collection and transmission of real-time data through telematics systems, showcasing their importance for predictive maintenance, fleet management, and personalized insurance programs. Citations support the presented information. The deployment of edge computing for real-time data processing in vehicles is discussed, emphasizing its significance for safety-critical applications like collision avoidance. Citations are provided to support the information. This section explores the application of machine learning algorithms to predict vehicle failures, optimize fuel efficiency, and analyze driver behavior. The importance of leveraging historical data to create accurate models is highlighted with supporting citations.
 Findings: The pivotal role of data science in enabling autonomous vehicles to navigate complex environments is discussed, emphasizing the use of machine learning models for real-time decision-making. Citations support the presented information. This subsection explores the integration of data science in traffic management systems, covering dynamic traffic signal control, congestion prediction, and route optimization. Citations support the findings related to traffic management applications. The paper discusses challenges associated with widespread implementation, including data privacy concerns, cybersecurity risks, and the need for standardized communication protocols. Additionally, potential future directions are outlined, such as the integration of blockchain for secure data sharing and the development of advanced human-machine interfaces.
 Unique Contribution to Theory, Practice and Policy: This research paper provides a well-rounded contribution by seamlessly integrating theoretical concepts, practical applications, and policy considerations in the realm of advanced data science applications in vehicles.

Person-Hood Issues Related To Artificial Intelligence

The abstract explores the intricate and ethically challenging subject of personhood issues in the realm of Artificial Intelligence (AI). As AI continues to advance, questions regarding the legal status, rights, and responsibilities of AI systems emerge, sparking a profound debate on whether AI entities should be granted personhood. The discussion begins by framing the current state of AI, acknowledging its increasing sophistication and integration into various aspects of human life. The focus then shifts to the core question: Should AI systems be endowed with legal personhood? This query becomes more pertinent as AI evolves towards achieving artificial general intelligence, comparable to human cognitive abilities. The abstract delves into the philosophical and ethical dimensions surrounding personhood, drawing parallels with historical debates on consciousness and humanity. The concept of personhood for AI is examined through the lens of ownership, accountability, representation, and management. The critical juncture is highlighted, where the evolution of AI, particularly towards artificial general intelligence, prompts a reassessment of the legal and ethical frameworks governing these entities. Notable considerations include the potential implications of personhood for AI, such as issues of ownership and accountability. The abstract raises thought-provoking scenarios, questioning the consequences of AI entities being granted legal status. The potential accumulation of wealth, rights, and influence by autonomous AI entities poses challenges to existing societal structures. Drawing on analogies from corporate law, the abstract explores the possibility of AI entities having a distinct legal status, separate from their human creators. However, it cautions against succumbing to the humanoid hype, emphasizing the need for a nuanced understanding of the implications of granting legal personhood to AI. In conclusion, the abstract underscores the urgency of addressing personhood issues related to AI. It navigates through the complex intersection of technology, ethics, and law, encouraging a thoughtful approach to the evolving nature of AI entities and their potential impact on societal structures. As AI progresses, defining the legal and ethical boundaries of personhood for these entities becomes a pivotal task to ensure responsible and equitable integration into human society.

An agent-based simulation model for the growth of the Sydney Trains network

Agent-based models are computational methods for simulating the actions and reactions of autonomous entities with the ability to capture their effects on a system through interaction rules. This study develops an agent-based simulation model (RANGE) to replicate the growth of Sydney Trains network by given exogenous historical evolution in land use. A set of locational rules has been defined to find a sequence of optimal stations from an initial seed. The model framework is an iterative process that includes five consecutive components including environment loading, measuring access, locating stations, connecting stations, and evaluating connections. In each iteration, following the locating/connecting process in each line of railways network, the accessibility will be calculated, and land use will be updated. Based on the compilation of network topology and properties, each iteration will be a year-on-year time step analysis. The network evolves based on a set of locational rules in regards to changes in the historic land use. Also, two coverage indices are defined to evaluate the fitness of the simulated lines in comparison to the Sydney tram and train network.

Clinical and Radiographic Characteristics in Segmental Colitis Associated With Diverticulosis, Diverticulitis, and Crohn’s Disease

Background and AimsSegmental colitis associated with diverticulosis (SCAD) is an underrecognized disease characterized by chronic segmental inflammation surrounding colonic diverticula. SCAD is recognized as an autonomous entity, although shares similar pathogenic and therapeutic aspects to inflammatory bowel disease (IBD) and may be considered a complication of diverticulitis. We aimed to characterize the clinical, endoscopic, and radiographic findings of SCAD and its potential overlap with diverticulitis and IBD. MethodsAll patients with suspected diagnosis of SCAD were identified using a bioinformatics search tool from January 1996 to October 2021 at our institution. Relevant demographic, clinical, endoscopic, and radiographic data were abstracted. Disease-related outcomes and radiographic characteristics were determined. ResultsSeventy-five patients with SCAD were included (48.0% female) with average age at diagnosis 62.5 years. Thirty-seven (49.3%) had a prior episode of diverticulitis. The most common presenting symptoms were abdominal pain (33.3%) and hematochezia (22.7%). Antibiotics (42.7%) and mesalamine (36.0%) were most used as first-line treatment options. Twenty (26.7%) required surgical intervention. The most common initial endoscopic finding was isolated sigmoid inflammation (86.7%). Fifty-one patients with confirmed SCAD, 72 with diverticulitis, and 12 with Crohn’s disease (CD) had imaging available for review. Penetrating disease was seen in 7 (13.7%) with SCAD compared to 7 (9.7%) and 2 (16.6%)with diverticulitis and CD, respectively (P = .14). Blinded radiologists diagnosed SCAD, CD, or diverticulitis correctly in 43.8%, 8.3%, and 27.1%, respectively. ConclusionSCAD should be considered when isolated sigmoid colon inflammation is seen on cross-sectional imaging. Penetrating disease is not a specific radiologic feature for either SCAD or diverticulitis. Further prospective studies are needed to correlate imaging characteristics with endoscopic findings to better describe radiographic features in SCAD.

МЕТОДИКА ОЦЕНКИ И УПРАВЛЕНИЕ РАЗВИТИЕМ СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ МЕЗОСИСТЕМ

The article is focused on the consideration of the concept of mesosism in the context of management by socio-economic development. It also provides a methodology for assessing and managing the development of socioeconomic mesosystems. The article proposes a number of methods that will allow assessing the level of development of socio-economic systems for further development of measures to improve their management efficiency. Systemic economics considers the concept of “mesoeconomics” mainly in the context of the economic sphere, focusing on the regional dimension [Kleiner 2006]. At the same time, it is advisable to expand the conceptual framework to include the following aspects in the field of mesoeconomics research: – Industry clusters and ecosystems – groups of interconnected enterprises and organizations united by a single industry specialization, common technologies and markets; – Local economic systems – autonomous territorial entities with their own resources, production base and infrastructure, but interacting with the external environment; – Global value chains – networks of interconnected enterprises and organizations engaged in joint activities for the production and distribution of goods and services on a global scale. The development of the theoretical foundations of mesoeconomics will allow not only to study, but also to manage those objects, contributing to an increase in the efficiency of the economic system as a whole. It will require the involvement of an interdisciplinary approach combining methods of systems analysis, economics, sociology and other sciences. Thus, mesoobjects take the modern economy beyond the neoclassical paradigm, opening up new horizons for research and practical application. The system economy, expanded on the basis of the proposed concepts, serves as a promising theoretical basis for building mesoeconomical models and developing effective management mechanisms.

Analysis and design research of digital electronic clocks

A digital electronic clock stands as a pinnacle of modern timing technology, built on digital circuits that offer precise hour, minute, and second tracking and display capabilities. The evolution of integrated circuits, combined with the ubiquitous application of quartz crystal oscillators, has propelled the digital electronic clock into myriad sectors including science, transportation, and finance. These clocks, appreciated for their precision, clarity, stability, and other attributes, vastly differ from their mechanical predecessors. Absent of mechanical transmission devices, they promise longevity and exact timekeeping. Such digitization serves as the foundational technological support for crafting large machinery and precision tools. Delving into the intricacies of digital electronic clocks and broadening their utilization holds substantial real-world relevance. This discourse employs a top-down hierarchical circuit design approach, segmenting the comprehensive circuit into distinct modules. This method not only streamlines its configuration, rendering it user-friendly and legible, but also ensures that each segmented circuit operates as an autonomous entity. This modularity facilitates smoother simulations and circuit modifications, enhancing adaptability and efficiency.

Categorization of organizational reputation and subordinate organizations' global funding outcome: A higher education perspective

Reputation is critical for building relationships with business customers in the global marketplace. However, in structurally connected organization configurations, the literature focuses mainly on one of the functional unit's reputations (either subordinate or superordinate organization), leaving out the interplay of reputation among various units in the organization. Drawing on identity and categorization theories, we develop a framework to examine the effects of brand reputation at both levels. Our study context is higher education, where business schools (subordinate) operate as autonomous entities globally yet are dependent on universities (superordinate) for policy decisions. We specify a random effects model on a 10-year panel dataset of 193 business schools to account for unobserved heterogeneity, potential selection bias, and endogeneity of reputation. Our findings suggest that brand reputation attributes at the subordinate and superordinate levels both individually and synergistically affect subordinate funding outcomes (i.e., business-school endowment). Furthermore, subordinate-level resource-utilization signals, such as diversification strategies and top executives' backgrounds, and superordinate-level policy signals, such as organization ownership and inclusivity, inform donor decisions and moderate the reputation–funding relationship. Our study suggests that administrators and managers should consider donor identity salience in marketing efforts.