Autonomic Loop Research Articles

The use of face masks and the impact on heart rate variability during baseline ECG

We compared electrocardiograms (ECGs) findings with one year difference between each other with and without use of face mask at the moment to be tested. The first ECG was done one year before without face mask, and the second ECG with a mask one year later after 3 months of mandatory use for epidemiological COVID-19 pandemic justifications in healthy youth elite athletes. Regarding heart rate variability (HRV), an increase in RMSSD was recorded when the test was performed with a mask (M): 108.5 ± 90 ms vs. No mask (NM): 72.9 ± 54.2 ms (p <0.002). And also an increase in SDNN, when the test was done with a M: 86.2 ± 47.2 ms vs. NM: 65.9 ± 43.5 ms (p <0.036). The results on ECG are consistent with the increasing predominance of parasympathetic regulation, which is responsible for regulation of the autonomic loop when the subject is using face mask.

NORA: An Approach for Transforming Network Management Policies into Automated Planning Problems.

Realizing autonomic management control loops is pivotal for achieving self-driving networks. Some studies have recently evidence the feasibility of using Automated Planning (AP) to carry out these loops. However, in practice, the use of AP is complicated since network administrators, who are non-experts in Artificial Intelligence, need to define network management policies as AP-goals and combine them with the network status and network management tasks to obtain AP-problems. AP planners use these problems to build up autonomic solutions formed by primitive tasks that modify the initial network state to achieve management goals. Although recent approaches have investigated transforming network management policies expressed in specific languages into low-level configuration rules, transforming these policies expressed in natural language into AP-goals and, subsequently, build up AP-based autonomic management loops remains unexplored. This paper introduces a novel approach, called NORA, to automatically generate AP-problems by translating Goal Policies expressed in natural language into AP-goals and combining them with both the network status and the network management tasks. NORA uses Natural Language Processing as the translation technique and templates as the combination technique to avoid network administrators to learn policy languages or AP-notations. We used a dataset containing Goal Policies to evaluate the NORA’s prototype. The results show that NORA achieves high precision and spends a short-time on generating AP-problems, which evinces NORA aids to overcome barriers to using AP in autonomic network management scenarios.

Adaptive DTN Routing: A Neuromorphic Networking Perspective

Routing is one of the main drivers of the end-to-end performance of bundle transmissions over a disruption tolerant network given the potentially large impact of the temporary but long-term partitioning that can occur at different sections of the network. A neuromorphic networking approach that defines an adaptive bundle routing for disruption-tolerant networks (DTN) is proposed where spiking neuronal networks (SNN) are used to determine the routing decisions of autonomous agents. The event-driven information encoding of spiking neurons involves very low energy consumption, which makes this approach attractive for challenging DTN applications with limited access to energy sources. The SNNs are continually updated within an autonomic loop, which produces synapse strength updates that are proportional to the expected communication costs of the routing decisions. A reward shaping procedure and a delay-tolerant mechanism for finding the local link-state is proposed, which allows determining instantaneous learning rewards for the agents. The method was tested on an emulated space communications network with scheduled disruptions. The results show that the proposed cognitive routing approach offers improved bundle delivery performance under network congestion compared to the standard Contact Graph Routing.

Progress and prospects for accelerating materials science with automated and autonomous workflows.

Accelerating materials research by integrating automation with artificial intelligence is increasingly recognized as a grand scientific challenge to discover and develop materials for emerging and future technologies. While the solid state materials science community has demonstrated a broad range of high throughput methods and effectively leveraged computational techniques to accelerate individual research tasks, revolutionary acceleration of materials discovery has yet to be fully realized. This perspective review presents a framework and ontology to outline a materials experiment lifecycle and visualize materials discovery workflows, providing a context for mapping the realized levels of automation and the next generation of autonomous loops in terms of scientific and automation complexity. Expanding autonomous loops to encompass larger portions of complex workflows will require integration of a range of experimental techniques as well as automation of expert decisions, including subtle reasoning about data quality, responses to unexpected data, and model design. Recent demonstrations of workflows that integrate multiple techniques and include autonomous loops, combined with emerging advancements in artificial intelligence and high throughput experimentation, signal the imminence of a revolution in materials discovery.

A Design Guideline for Adaptation Decisions in the Autonomic Loop

Autonomic computing has received great attention as a solution for the increasing complexity of today’s self-adaptive systems. In this kind of systems, the decision to ensure the most suitable autonomic application’s adaptation according to context is very important. In the literature, several research activities propose decision approaches and frameworks within the MAPE-K autonomic loop for adaptation. However, there is a lack of guidelines to design adaptation decisions. Such guidelines are required to assist the designers of autonomic applications and unify existing decision approaches. In this work, we propose a design guideline for adaptation decisions and an instantiation of this guideline in the case study Smart Building.

Distributed Execution of Modular Discrete Controllers for Data Center Management

Complex computing systems are increasingly designed so that they are self-adaptive, and adopt the autonomic computing approach for their administration. Real systems require the co-existence of multiple such autonomic management loops. Their uncoordinated execution can lead to problematic interferences and jeopardize performance as well as consistency. This is a typical example of the general need for methodological support for the design of well- coordinated managers, without breaking their natural modularity. We address the problem with a method stressing modularity, and focusing on the discrete control of the interactions of managers. This paper focusses on proposals for the distributed execution of modular controllers, first in synchronized way, and then relaxing this synchronization. We apply and validate our method on a multiple-loop multi-tier system in a data-center.

The Aesop Approach for Semantic-Based End-User Service Optimization

The need to autonomically optimize end-user service experience in near real time has been identified in the literature in recent years. Management systems that monitor end-user service session context exist but approaches that estimate end-user service experience from session context do not analyze the compliance of that experience with user expectations. Approaches that optimize end-user service delivery are not applicable to arbitrary services; they either optimize specific service types or use general mechanisms that do not consider service experience. The lack of a holistic model for end-user service management is a barrier to autonomic end-user service optimization. This paper presents Aesop, an approach addressing autonomic optimization of end-user service delivery using semantic-based techniques. Its knowledge base uses the End-User Service Analysis and Optimization ontology, which models the end-user service management domain and partitions knowledge that varies over time for efficient access. The Aesop Engine executes an autonomic loop in near real time, which runs semantic algorithms to monitor sessions, analyze their compliance with expectations, and plan and execute optimizations on service delivery networks. The algorithms are efficient because they operate on small partitioned subsets of the Knowledge Base held as separate self-contained models at run time. An Aesop implementation was evaluated on a home area network test bed where compliance of service sessions with expectations when optimization was active was compared with compliance of an identical set of sessions when optimization was inactive. Significant improvements were observed on compliance levels of high priority sessions in all experimental scenarios, with compliance levels more than doubled in some cases.

An Increased Endothelial‐Independent Vasodilation Is the Hallmark of the Neurally Mediated Syncope

The neurally mediated syncope (NMS) is sustained by complex cardiac and vascular reflexes, acting on and amplified by central autonomic loops, resulting in bradycardia and hypotension. Our aim was to assess whether the pathophysiology of NMS is also related to an abnormal peripheral vasoreactivity. We evaluated by ultrasound the flow-mediated vasodilation (FMD) and the nitrate-mediated dilation (NMD) in 17 patients with NMS, induced by drug-free tilt test in 6 subjects and by nitrate-potentiated tilt test in the other 11 cases; the syncope was classified as vasodepressive (VD) in 8 cases, cardioinhibitory (CI) in 7, and mixed in 2. The FMD was not different from controls (10.2 ± 4.5 vs 11.4 ± 3.9, P = ns), with normal recovery times; the NMD was greater in fainting subjects than in controls (26.7 ± 7.3 vs 19.0 ± 3.6, P < 0.05), with higher values in VD than in CI syncope (31.1 ± 7.0 vs 23.1 ± 5.0, P = ns); compared to controls, subjects with NMS showed normal recovery times after FMD but longer recovery times after nitrate administration (13.0 ± 5.6 vs 6.3 ± 0.7 minutes, P < 0.05). The evaluation of endothelial function supports evidence that NMS is characterized by a marked and sustained endothelial-independent vasodilation, in the presence of a normal FMD; vascular hyperreactivity in response to nitrate administration is particularly overt in vasodepressive syncope and can explain the high rate of responses to nitrate administration during tilt test.

Heart Rate Variability in Outbred White Rats upon Periodical α-Tocopherol Administration

Effect of alpha-tocopherol (vitamin E) periodical administration on heart rhythm regulation was investigated in outbred white rats. alpha-Tocopherol administration to males was followed by reduction of sympathetic neural influence on heart rhythm and also by the increase of the number of individuals with high activity of autonomic regulation loop. In female rats alpha-tocopherol administration modulates the activity of humoral control circuit and promotes heart rate reduction, however upon that the percent of females with high centralization of heart rate regulation was increased.

Autonomic heart rate control and regional vascular reactions

Rheovasographic parameters (the thigh region) were recorded in groups of subjects with high and low heart rate variability (HRV). Correlation between the rheovasographic parameters and the sympathetic-parasympathetic balance value (LF/HF) was found. It was established that vagosympathetic balance in the first group was interrelated with the parameters of the ascending portion of the rheological wave; in the second group, with the parameters characterizing the blood flow in the microcirculatory bed. Thus, predominance of the autonomic loop of regulation mainly ensures an optimal regional arterial blood flow; the predominance of the central loop of regulation of cardiac activity, an optimal blood flow in microvessels.

A novel neurological mechanism to explain the adverse effect of depression on coronary artery disease

The strong antecedent effect of depression as a risk factor in the development of coronary artery disease (CAD) has been demonstrated in many robust epidemiological studies. However, the underlying causative mechanisms are incompletely understood: this hypothesis proposes one possibility. A variety of histological and radiological techniques have been used to demonstrate structural and functional abnormalities in the prefrontal cortex (PFC) of depressed subjects. In addition, this limbic region has been inextricably implicated in the modulation of autonomic tone. Cardio-specifically, stimulation of PFC has arrhythmogenic effects. Reciprocally, cardiac stress tests produce activation of this cortical region. These observations place PFC at the top of a hierarchical autonomic loop involved in sensing and modulating cardiac variables. Finally, the reduced heart rate variability, higher heart rates and elevated cerebrospinal fluid catecholamine levels in depressed patients, compared to non-depressed matched controls, suggest sympathetic overdrive in these patients. These observations lead the author to propose that a primary defect in the PFC of depressed subjects destabilises the autonomic neurocardiac axis, accounting for the proven adverse effect of depression on CAD. This novel neurological mechanism can help to develop other current theories and to design and trial future therapies to reduce the adverse effect of depression on coronary artery disease.

Random Characteristics of the Type II Phase-Locked Loop

The results of a study of the characteristics of the second-order Type II phase-locked loop with a Gaussian noise input, and obtained by digital computer simulation, are presented. The digital simulation is described and the random state variables are defined such that their characteristics can be interpreted in terms of existing phase portraits of autonomous phase-locked loops. The statistics associated with the state variables, which are phase error and a measure of frequency error, and those associated with the number of cycles skipped and the mean time to unlock, are given.