Feedback Synthesis Research Articles

Feedbacks: a new synthesis of causal loops across ecology

Feedbacks are the basic linkages of living systems. In organisms, they regulate the processes of growth and homeostasis, as well as their interactions with their world. Feedback, which Judson (1980) called ‘one of the chief themes of scientific understanding,' is equally important in ecological systems. The ecological literature is rich in papers dealing with the role of feedback in various phenomena. However, we know of no comprehensive synthesis of feedbacks in ecology. Pichon et al. (2024) accomplish this, and for the first time show that ecological feedbacks can be categorized in terms of a small number of fundamental attributes. The paper brings the array of different types of feedbacks into a manageable order, providing not only the relevant theoretical framework but also guidance on methods for applying understanding to practical issues.

Policy Optimization Over Submanifolds for Linearly Constrained Feedback Synthesis

Policy Optimization Over Submanifolds for Linearly Constrained Feedback Synthesis

On the Feedback Synthesis for an Autonomous Linear System with Perturbations

On the Feedback Synthesis for an Autonomous Linear System with Perturbations

Consolidated guidance for behavioral intervention pilot and feasibility studies

BackgroundIn the behavioral sciences, conducting pilot and/or feasibility studies (PFS) is a key step that provides essential information used to inform the design, conduct, and implementation of a larger-scale trial. There are more than 160 published guidelines, reporting checklists, frameworks, and recommendations related to PFS. All of these publications offer some form of guidance on PFS, but many focus on one or a few topics. This makes it difficult for researchers wanting to gain a broader understanding of all the relevant and important aspects of PFS and requires them to seek out multiple sources of information, which increases the risk of missing key considerations to incorporate into their PFS. The purpose of this study was to develop a consolidated set of considerations for the design, conduct, implementation, and reporting of PFS for interventions conducted in the behavioral sciences.MethodsTo develop this consolidation, we undertook a review of the published guidance on PFS in combination with expert consensus (via a Delphi study) from the authors who wrote such guidance to inform the identified considerations. A total of 161 PFS-related guidelines, checklists, frameworks, and recommendations were identified via a review of recently published behavioral intervention PFS and backward/forward citation tracking of a well-known PFS literature (e.g., CONSORT Ext. for PFS). Authors of all 161 PFS publications were invited to complete a three-round Delphi survey, which was used to guide the creation of a consolidated list of considerations to guide the design, conduct, and reporting of PFS conducted by researchers in the behavioral sciences.ResultsA total of 496 authors were invited to take part in the three-round Delphi survey (round 1, N = 46; round 2, N = 24; round 3, N = 22). A set of twenty considerations, broadly categorized into six themes (intervention design, study design, conduct of trial, implementation of intervention, statistical analysis, and reporting) were generated from a review of the 161 PFS-related publications as well as a synthesis of feedback from the three-round Delphi process. These 20 considerations are presented alongside a supporting narrative for each consideration as well as a crosswalk of all 161 publications aligned with each consideration for further reading.ConclusionWe leveraged expert opinion from researchers who have published PFS-related guidelines, checklists, frameworks, and recommendations on a wide range of topics and distilled this knowledge into a valuable and universal resource for researchers conducting PFS. Researchers may use these considerations alongside the previously published literature to guide decisions about all aspects of PFS, with the hope of creating and disseminating interventions with broad public health impact.

Global synthesis of effects and feedbacks from artificial reefs on socioecological systems in recreational fisheries

AbstractArtificial reefs have been widely deployed with the intention of increasing fish habitat, enhancing recreational fishery opportunities and providing socio‐economic benefits to surrounding communities. Substantial work has been done to understand the ecology of artificial reefs but the efficacy of artificial reefs as a management tool hinges on socioecological feedbacks that are not well understood. Socioecological feedbacks are difficult to discern because they depend on multiple and complex interactions between fish, fishers, managers and habitats. To better understand the net effects of artificial reefs on recreational fisheries, we conducted a literature review to catalogue effects and feedbacks of artificial reefs. Our global synthesis revealed that artificial reefs may result in a net negative effect on fish populations, at least in the short‐term, as catch‐driven effects bolstering socio‐economic objectives occur more often or at greater intensities than positive biological effects. We have highlighted important effects of artificial reefs and feedbacks that need to be accounted for when considering their deployment in fishery management. There may be unintended consequences if biological benefits from habitat‐to‐fish and fish‐to‐fish feedbacks are outweighed by population losses due to greater socio‐economic benefits from fish‐to‐fisher feedbacks. Taken in concert with their semi‐permanent nature and apparent popularity with stakeholders, a view emerges of artificial reefs possibly functioning as a ‘social‐ecological trap’. This work emphasizes the need for robust assessments of the effects of artificial reefs, as well as more formal decision science approaches for implementing of these structures.

Affective Feedback Synthesis Towards Multimodal Text and Image Data

In this article, we have defined a novel task of affective feedback synthesis that generates feedback for input text and corresponding images in a way similar to humans responding to multimodal data. A feedback synthesis system has been proposed and trained using ground-truth human comments along with image–text input. We have also constructed a large-scale dataset consisting of images, text, Twitter user comments, and the number of likes for the comments by crawling news articles through Twitter feeds. The proposed system extracts textual features using a transformer-based textual encoder. The visual features have been extracted using a Faster region-based convolutional neural networks model. The textual and visual features have been concatenated to construct multimodal features that the decoder uses to synthesize the feedback. We have compared the results of the proposed system with baseline models using quantitative and qualitative measures. The synthesized feedbacks have been analyzed using automatic and human evaluation. They have been found to be semantically similar to the ground-truth comments and relevant to the given text–image input.

Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies

Gradient-based methods have been widely used for system design and optimization in diverse application domains. Recently, there has been a renewed interest in studying theoretical properties of these methods in the context of control and reinforcement learning. This article surveys some of the recent developments on policy optimization, a gradient-based iterative approach for feedback control synthesis that has been popularized by successes of reinforcement learning. We take an interdisciplinary perspective in our exposition that connects control theory, reinforcement learning, and large-scale optimization. We review a number of recently developed theoretical results on the optimization landscape, global convergence, and sample complexityof gradient-based methods for various continuous control problems, such as the linear quadratic regulator (LQR), [Formula: see text] control, risk-sensitive control, linear quadratic Gaussian (LQG) control, and output feedback synthesis. In conjunction with these optimization results, we also discuss how direct policy optimization handles stability and robustness concerns in learning-based control, two main desiderata in control engineering. We conclude the survey by pointing out several challenges and opportunities at the intersection of learning and control.

Nonlinear feedback synthesis and control of periodic, quasiperiodic, chaotic and hyper-chaotic oscillations in mechanical systems

Nonlinear feedback synthesis and control of periodic, quasiperiodic, chaotic and hyper-chaotic oscillations in mechanical systems

An illustration of a quasi-interpolation driven technique for feedback synthesis

This article illustrates an offline approximate feedback synthesis algorithm on one of the simplest unconstrained optimal control problems — the continuous-time linear quadratic regulator (LQR). The driving engine behind the approximation algorithm is a special kind of quasi-interpolation technique based on the theory of approximate approximations. The explicit feedback control is approximated via the quasi-interpolation scheme on a uniform-cardinal grid over the phase-space. This method provides theoretical guarantees for the uniform i.e. L∞ convergence of the approximated feedback law to the actual optimal feedback, up to some saturation error, which can be reduced to an arbitrary number. Although the analytical expression for the LQ feedback is available, we present the technique in this simple case to serve as an illustrative test bed for the algorithm. We provide a couple of numerical examples to illustrate our results. The algorithm has the potential to be employed for tight uniform approximation of optimal feedback maps under constraints and will be reported subsequently.

A non-iterative approach to Linear Quadratic Static Output Feedback

This paper considers the problem of static output feedback (SOF) synthesis for linear time-invariant (LTI) systems. Static output feedback, and more generally structured controller synthesis, is of special interest to any industrial application where a reduced-order controller is desired, e.g., high-order systems, or a specific structure is to be imposed, i.e., distributed/decentralised control. A simple two-step process is proposed, solving one Riccati equation and one optimisation problem with linear matrix inequality (LMI) constraints, enabled via a dilation using the distance to the full-state feedback optimum gain. Numerical analysis shows considerable computational savings, with negligible differences in the performance, when compared to current iterative methods.

A Structure Exploiting SDP Solver for Robust Controller Synthesis

In this paper, we revisit structure exploiting SDP solvers dedicated to the solution of Kalman-Yakubovic-Popov semi-definite programs (KYP-SDPs). These SDPs inherit their name from the KYP lemma and they play a crucial role in e.g. robustness analysis, robust state feedback synthesis, and robust estimator synthesis for uncertain dynamical systems. Off-the-shelve SDP solvers require O(n6) arithmetic operations per Newton step to solve this class of problems, where n is the state dimension of the dynamical system under consideration. Specialized solvers reduce this complexity to O(n3). However, existing specialized solvers do not include semi-definite constraints on the Lyapunov matrix, which is necessary for controller synthesis. In this paper, we show how to include such constraints in structure exploiting KYP-SDP solvers.

Синтез субоптимальных обратных связей в линейных задачах оптимального управления методом опорных векторов

Optimal feedback synthesis for two linear optimal control problems is studied: The terminal problem and the problem of minimizing the total impulse of the control. The main contribution of the paper is a method for constructing suboptimal feedbacks in the problems under consideration, based on a linear binary data classification for datasets obtained during the simulation process or real-time control of the system.

The Dandarah App: An mHealth Platform to Tackle Violence and Discrimination of Sexual and Gender Minority Persons Living in Brazil.

Discrimination and violence are widely experienced by sexual and gender minority (SGM) persons worldwide. More than one SGM person is murdered every day in Brazil because of their sexuality or gender identity, which is the highest reported homicide rate in the world. Alt-hough discrimination and violence against SGM persons in Brazil are considered to be hate crimes, reporting is still suboptimal due to fear of police SGM phobia and victim blaming. Accessible and easily disseminated interventions are urgently needed. Herein, we describe the develop-ment of an mHealth solution to help address violence against SGM persons, namely the Rainbow Resistance: Dandarah App, with a synthesis of key results and feedback from the SGM community after 24 months of using the app. Twenty-two focus group discussions (FGDs) were conducted with SGM persons living in six Brazilian states: Bahia, Federal District, São Paulo, Rio de Janeiro, Minas Gerais, Sergipe, and Pará. A total of 300 SGM persons participated in the FGDs. A thematic analysis was performed to interpret the qualitative data. Content themes related to aesthetics, us-ability, barriers to resources, and likes/dislikes about the intervention arose from the FGDs. Participants found the intervention to be user-friendly, endorsed more likes than dislikes, and suggested a few changes to the app. The findings suggest that the intervention is usable and fit for future ef-fectiveness testing, and that it could fill an important gap in the well-being of SGM persons living in a country with high levels of discrimination and violence towards this community, i.e., Brazil.

Robust Static Output Feedback with Dynamic Disturbance Feed-forward for Lateral Control of Long-combination Vehicles At High Speeds

Abstract A control strategy is proposed to improve the high-speed lateral performance of an A-double (tractor-semitrailer-dolly-semitrailer) combination vehicle using active steering of the front axle of the dolly. The strategy is realized as a H∞-type static output feedback combined with dynamic feed-forward. The static output feedback synthesis is based on a previous work from the literature, while novel linear matrix inequality (LMI) conditions have been derived for dynamic feed-forward synthesis that can also be used for uncertain systems. The proposed controller has a simple structure and is easy to implement from a practical point of view since it requires only the driver steering angle (for feed-forward) and just one articulation angle measurement (for feedback). Obtained using a high-fidelity vehicle model, the synthesis results confirm a significant reduction in the rearward amplifications of the yaw rate and the lateral acceleration as well as the high-speed transient off-tracking during sudden lane change maneuvers.

Structured controller synthesis through block-diagonal factorization and parameter space optimization

Constraints on the feedback structure arise in many control systems due to implementing cost, hardware limitations and operational reliability. The parameter space method aims to solve the robust structured controller design problems based on a convex reformulation technique. Despite its attractiveness, the structural constraints are limited to be either decentralized or linear dependence among entries within the same row or column in the current literature. And the global optimal solution is yet to be guaranteed, since a non-convex constraint is introduced in the parameter space after reformulating it as the output feedback synthesis problem. In this paper, we extend the parameter space method to a more generalized structured optimal control problem, such that the linear dependence can occur among its arbitrary entries. A bilinear factorization to the feedback gain matrix is proposed by a special Kronecker product decomposition. Subsequently, an equivalent transformation is proposed to convert this structured control design problem to a controller synthesis problem under decentralized full-state feedback. Thereby, the prior non-convex constraint in the parameter space is removed and the globally optimal structured controller is synthesized by convex programming. Examples such as integrated design and formation control demonstrate its practical appeals.

Erratum to: Observer-Aided Output Feedback Synthesis as an Optimization Problem

Erratum to: Observer-Aided Output Feedback Synthesis as an Optimization Problem

O52 - Review of accreditation standards: A snapshot of the Midwife Accreditation Standards 2021

The purpose of this presentation is to highlight key aspects of the newly published Australian Nursing and Midwifery Accreditation Council’s Midwife Accreditation Standards 2021. The Australian Nursing and Midwifery Accreditation Council (ANMAC) uses the Midwife Accreditation Standards to accredit and assess entry to practice midwifery programs and the education providers who offer them. In developing the Midwife Accreditation Standards 2021, wide-ranging consultation was undertaken with key stakeholders in midwifery education. ANMAC received more than 250 submissions across three separate consultation periods. Stakeholders contributed feedback by way of online surveys, written submissions, and face-to-face consultation. Synthesis of stakeholder feedback is available on the ANMAC website. The consultation process identified several key areas for consideration including, governance arrangements, intraprofessional learning, digital literacy and midwife prescribing and diagnostics. These will be the focus of this presentation. Significant changes to the Midwifery Accreditation Standards 2021 include clarifying the requirements of the head of discipline role, as well as content related to intraprofessional learning and digital literacy. When developing these standards ANMAC consulted widely on the inclusion of prescribing in entry to practice midwifery programs though this was not ultimately included in the standards. Hence the inclusion of prescribing and diagnostic skills in future accreditation standards for undergraduate midwifery programs will also be explored. Additionally, some practical changes have been implemented by replacing the previous nine standards with five, and the inclusion of an Essential Evidence document to support the development of accreditation submissions

How does nursing-sensitive indicator feedback with nursing or interprofessional teams work and shape nursing performance improvement systems? A rapid realist review

BackgroundCare quality varies between organizations and even units within an organization. Inadequate care can have harmful financial and social consequences, e.g. nosocomial infection, lengthened hospital stays or death. Experts recommend the implementation of nursing performance improvement systems to assess team performance and monitor patient outcomes as well as service efficiency. In practice, these systems provide nursing or interprofessional teams with nursing-sensitive indicator feedback. Feedback is essential since it commits teams to improve their practice, although it appears somewhat haphazard and, at times, overlooked. Research findings suggest that contextual dynamics, initial system performance and feedback modes interact in unknown ways. This rapid review aims to produce a theorization to explain what works in which contexts, and how feedback to nursing or interprofessional teams shape nursing performance improvement systems.MethodsBased on theory-driven realist methodology, with reference to an innovative combination of Actor-Network Theory and Critical Realist philosophy principles, this realist rapid review entailed an iterative procedure: 8766 documents in French and English, published between 2010 and 2018, were identified via 5 databases, and 23 were selected and analysed. Two expert panels (scientific and clinical) were consulted to improve the synthesis and systemic modelling of an original feedback theorization.ResultsWe identified three hypotheses, subdivided into twelve generative configurations to explain how feedback mobilizes nursing or interprofessional teams. Empirically founded and actionable, these propositions are supported by expert panels. Each configuration specifies contextualized mechanisms that explain feedback and team outcomes. Socially mediated mechanisms are particularly generative of action and agency.ConclusionsThis rapid realist review provides an informative theoretical proposition to embrace the complexity of nursing-sensitive indicator feedback with nursing or interdisciplinary teams. Building on general explanations previously observed, this review provides insight into a deep explanation of feedback mechanisms.Systematic review registrationProspero CRD42018110128.

Suppression of Chaotic Oscillations in Small Energy Systems

The paper considers the suppression of chaotic oscillations in small energy systems that occur in emergency modes and lead to the phenomenon of voltage collapse, which corresponds to the process of voltage drop in the network, which can be accompanied by a complete shutdown of the affected area. The paper also presents a method that has been developed and that allows changing the spectrum of Lyapunov’s characteristic indicators and converting chaotic oscillations in a small power system to regular dynamic modes. The method of synthesis of control actions is based on the theorem of topological equivalence of hyperbolic nonlinear systems and their linearized models as well as on and the use of numerical integration of nonlinear differential equations describing the behavior of power systems in order to construct a phase portrait and calculate Lyapunov’s characteristic exponents. The results of the work consist in the synthesis of feedback, which ensures the formation of a spectrum of Lyapunov’s characteristic indicators with negative values. The suppression of chaotic regimes occurs by forming a spectrum of negative Lyapunov’s characteristic indicators in a closed system. The parameters of the regulator in the feedback circuit are determined using the modal control method based on the solution of the matrix algebraic Sylvester equation. The solution of the problem of transition from a chaotic regime to a regular movement in a small power system is considered. To test the operability of the proposed method of chaos suppression, the spectrum of Lyapunov’s characteristic indicators is calculated and trajectories in the phase space of the initial nonlinear system and the system with control action are constructed. For energy systems with chaotic dynamics, synthesized feedback makes it possible to suppress chaotic fluctuations and switch to regular modes, thereby preventing the occurrence of emergency modes.

Synthesis and implementation of lambda-approach of slide control in heat-consumption system

The paper proposes an essentially new approach to synthesis and implementation of dynamic objects with three-position relay control. The approach consists in organization of differentiation procedure on the relay element involved into feedback. We considered synthesis of the relay element feedback in tasks of robust and time optimal control of heat-consumption systems. To demonstrate the effectiveness of the proposed approach, a comparative assessment of the results of modeling heat consumption systems with three-position relay control and a traditional linear–quadratic regulator is presented. We attached transient processes plots of active heat-consumption systems which confirm the effectiveness of the synthesized relay control.