Action Refinement Research Articles

Wet markets in Southeast Asia and access to healthy diets

Hunger and malnutrition in all forms continues to rise in Africa and Asia. Urban and rural communities’ diets in Southeast Asia (SEA) are increasingly unhealthy, with consumption influenced by affordability and convenience. The cost of a healthy diet is a major barrier to accessing healthy foods in SEA. Wet markets are key places in food environments where people buy and sell a variety of foods. They are especially important for food and nutrition insecure communities. This mini narrative review explores the role that wet markets, in SEA food environments, play in providing local communities with access to healthy foods. Fourteen peer-review papers, published in English between 2017 and 2022, were identified during screening and analysed according to six food environment domains. Findings highlight that convenient access to wet markets facilitates access to fruits and vegetables in peri urban and urban areas. Fresh foods, most notably fruits, were viewed as being more expensive than processed foods which in turn influenced purchasing behavior. Divergent findings were presented in the identified papers regarding affordability of food in wet markets. Concerns about food quality and the use of chemicals and pesticides were raised. This review was constrained by several factors including the lack of consistent and meaningful definitions and typologies of the varied forms of wet markets. Looking ahead, better defined interpretations of wet markets can enhance the development and refinement of appropriate policies and actions and comparison of wet markets, in respect of access to diverse, healthy foods, vendor practices and consumer food choices.

Enhancing team dynamics through digital coaching: the role of managerial and peer support

PurposeAlthough the literature on the effectiveness of team interventions is constantly expanding, there has been a strong focus on the process mechanisms that could explain their success, often overlooking the contextual aspects in which these interventions are carried out. Based on the Context-Mechanism-Outcome framework, this study aims to investigate the influence of contextual factors on the effectiveness of digital team coaching interventions that use social network visualisation to enhance team coordination and reduce interpersonal conflicts.Design/methodology/approachUsing a multi-wave, longitudinal design, this research analysed 38 work teams from three organisations over three-time points. Data collection focused on manager and peer support, the mechanisms of training transfer and action plan implementation and the outcomes of these interventions. Surveys were administered in three organisations, involving 317 respondents across different phases. The intervention spanned six to eight months, incorporating three to four structured online group sessions. Each session involved a multi-stage process, concluding with a result-oriented action plan about work-related goals. The intervention included social network visualisation, discussions, coaching and continuous refinement of action plans.FindingsThe analysis highlights how manager support significantly correlates with team coordination and performance, mainly when teams are less engaged in implementing action plans. Peer support did not show a mediating effect on training transfer or outcomes but had direct positive impacts on team coordination and performance.Practical implicationsTeams actively implementing action plans may require less immediate managerial support for effective coordination and high performance. The manager’s role becomes crucial, particularly in the early stages of the intervention or in those teams where online coordination alone may not be adequate for action plan implementation. Peer support for training transfer could enhance the effectiveness of the intervention in achieving desired team outcomes; therefore, cultivating a supportive peer environment is crucial for the success of such interventions. Monitoring and assessing team dynamics are vital to maximise the benefits of digital team coaching interventions.Originality/valueThis study stands out for its innovative exploration of the interplay between managerial and peer support in the context of digital team coaching, using social network visualisation as a novel approach to enhancing team dynamics.

Distributed Resource Scheduling for Large-Scale MEC Systems: A Multiagent Ensemble Deep Reinforcement Learning With Imitation Acceleration

In large-scale mobile edge computing (MEC) systems, the task latency, and energy consumption are important for massive resource-consuming and delay-sensitive Internet of Things Devices (IoTDs). Against this background, we propose a distributed intelligent resource scheduling (DIRS) framework to minimize the sum of task latency and energy consumption for all IoTDs, which can be formulated as a mixed-integer nonlinear programming. The DIRS framework includes centralized training relying on the global information and distributed decision making by each agent deployed in each MEC server. Specifically, we first introduce a novel multiagent ensemble-assisted distributed deep reinforcement learning (DRL) architecture, which can simplify the overall neural network structure of each agent by partitioning the state space and also improve the performance of a single agent by combining decisions of all the agents. Second, we apply action refinement to enhance the exploration ability of the proposed DIRS framework, where the near-optimal state-action pairs are obtained by a novel Levy flight search. Finally, an imitation acceleration scheme is presented to pretrain all the agents, which can significantly accelerate the learning process of the proposed framework through learning the professional experience from a small amount of demonstration data. The simulation results in three typical scenarios demonstrate that the proposed DIRS framework is efficient and outperforms the existing benchmark schemes.

A global view on fungal infections in humans and animals: infections caused by dimorphic fungi and dermatophytoses.

Fungal infections are still underappreciated and their prevalence is underestimated, which renders them a serious public health problem. Realistic discussions about their distribution, symptoms, and control can improve management and diagnosis and contribute to refinement of preventive actions using currently available tools. This article represents an overview of dermatophytes and endemic fungi that cause infections in humans and animals. In addition, the impact of climate change on the fungal spread is discussed. The endemic fungal infections characterized in this article include coccidioidomycosis, histoplasmosis, blastomycosis, lobomycosis, emergomycosis and sporotrichosis. Moreover the geographic distribution of these fungi, which are known to be climate sensitive and/or limited to endemic tropical and subtropical areas, is highlighted. In turn, dermatophytes cause superficial fungal infections of skin, hairs and nails, which are the most prevalent mycoses worldwide with a high economic burden. Therefore, the possibility of causing zoonoses and reverse zoonoses by dermatophytes is highly important. In conclusion, the article illustrates the current issues of the epidemiology and distribution of fungal diseases, emphasizing the lack of public programmes for prevention and control of these types of infection.

DRAG: Deep Reinforcement Learning Based Base Station Activation in Heterogeneous Networks

Heterogeneous Network (HetNet), where Small cell Base Stations (SBSs) are densely deployed to offload traffic from macro Base Stations (BSs), is identified as a key solution to meet the unprecedented mobile traffic demand. The high density of SBSs are designed for peak traffic hours and consume an unnecessarily large amount of energy during off-peak time. In this paper, we propose a deep reinforcement-learning based SBS activation strategy that activates the optimal subset of SBSs to significantly lower the energy consumption without compromising the quality of service. In particular, we formulate the SBS on/off switching problem into a Markov Decision Process that can be solved by Actor Critic (AC) reinforcement learning methods. To avoid prohibitively high computational and storage costs of conventional tabular-based approaches, we propose to use deep neural networks to approximate the policy and value functions in the AC approach. Moreover, to expedite the training process, we adopt a Deep Deterministic Policy Gradient (DDPG) approach together with a novel action refinement scheme. Through extensive numerical simulations, we show that the proposed scheme greatly outperforms the existing methods in terms of both energy efficiency and computational efficiency. We also show that the proposed scheme can scale to large system with polynomial complexities in both storage and computation.

Religious Development Management in Forming the Character of Criminers

Management of religious guidance in shaping the character of prisoners is a renewal, refinement or effort of action or activity carried out in an integrated, efficient and effective manner to obtain better results. If this guidance activity is carried out on prisoners, then religious guidance will give meaning to the prisoner to be faithful, knowledgeable and have a noble character in life and life. The process of forming good characters must be in accordance with the basis for the formation of good characters itself, namely the Al-Qur'an and the life and life examples of the Prophet Muhammad SAW. Al-Qur'an is the Word of Allah SWT in which it provides guidance for humans in various aspects, one of which is about guidelines for behavior so that humans can distinguish between good and bad.

Coupled similarity: the first 32 years

Coupled similarity is an equivalence on (labeled) transition systems; its distinguishing power lies between (weak) bisimilarity and (may) testing equivalence. Its main feature, compared to weak bisimilarity, is an additional $$\tau $$-law that abstracts from the atomicity of internal choices among several possible branches, thus allowing for gradual commitments. The need for this $$\tau $$-law in applications was motivated by van Glabbeek and Vaandrager in 1988. Parrow and Sjodin coined the term coupled simulation in 1992 as a coinductive proof technique for the comparison of distributed (not “just” concurrent) systems, heavily exploiting gradual commitments. Over the years, coupled similarity also gained significance for the definition and analysis of the correctness of encodings, of action refinement and contraction, and of branching-time semantics for various process calculi. In this paper, we compare variants and formalizations of coupled similarity and highlight its relevance.

A Bridge to Leadership Communication Success:: Impact of Leader-Member Exchange on Nursing Administrative Relationships

Nurse managers are the cornerstones of nursing administration, and leadership theory can help them achieve administrative success. Our interdisciplinary research team formed a collaboration with a clinical setting to study the nuances of nursing administration communication. The investigation examined the impact of leader-member exchange, a leadership theory that focuses on relationships, in 206 nurses in a 600-bed hospital and found significant correlations with job satisfaction and organizational commitment, but not with organizational citizenship behavior. Nursing implications for retention of nursing workforce and refinement of leadership actions are presented.

Feldenkrais's Touch, Ephram's Laughter, Gould's Sensorium: Listening and Musical Practice between Thinking and Doing

AbstractThis study addresses listening as a hinge between therapeutic and musical contexts. In the first two sections I examine the productive confluence of Jean-Luc Nancy's thought and Moshe Feldenkrais's somatic practice. I show that the ‘subject’ is configured as both embodied and enactivist. Drawing on Nancy's work, Jacques Lacan, Sigmund Freud and educational and developmental child psychology, I position the listening subject on a fulcrum of balance and imbalance essential to learning and musical practice. In the third part of this study, I concretize Feldenkrais's ideals of correct action and listening in musical practice. Using Glenn Gould and empirical work on musical practice, I explore the significance of listening between acts of playing. Listening is proposed not merely as a phenomenological form of making sense (Nancy), but as a form of self-negotiation and an enactivist and imaginative space that leads to new possibilities of thought and refinement of action.

Active Zone Proteins RIM1αβ Are Required for Normal Corticostriatal Transmission and Action Control.

Dynamic regulation of synaptic transmission at cortical inputs to the dorsal striatum is considered critical for flexible and efficient action learning and control. Presynaptic mechanisms governing the properties and plasticity of glutamate release from these inputs are not fully understood, and the corticostriatal synaptic processes that support normal action learning and control remain unclear. Here we show in male and female mice that conditional deletion of presynaptic proteins RIM1αβ (RIM1) from excitatory cortical neurons impairs corticostriatal synaptic transmission in the dorsolateral striatum. Key forms of presynaptic G-protein-coupled receptor-mediated short- and long-term striatal plasticity are spared following RIM1 deletion. Conditional RIM1 KO mice show heightened novelty-induced locomotion and impaired motor learning on the accelerating rotarod. They further show heightened self-paced instrumental responding for food and impaired learning of a habitual instrumental response strategy. Together, these findings reveal a selective role for presynaptic RIM1 in neurotransmitter release at prominent basal ganglia synapses, and provide evidence that RIM1-dependent processes help to promote the refinement of skilled actions, constrain goal-directed behaviors, and support the learning and use of habits.SIGNIFICANCE STATEMENT Our daily functioning hinges on the ability to flexibly and efficiently learn and control our actions. How the brain encodes these capacities is unclear. Here we identified a selective role for presynaptic proteins RIM1αβ in controlling glutamate release from cortical inputs to the dorsolateral striatum, a brain structure critical for action learning and control. Behavioral analysis of mice with restricted genetic deletion of RIM1αβ further revealed roles for RIM1αβ-dependent processes in the learning and refinement of motor skills and the balanced expression of goal-directed and habitual actions.

Developing a climate adaptation strategy for vulnerable seabirds based on prioritisation of intervention options

Conservation of marine species typically focuses on monitoring and mitigating demonstrated stressors where possible. Evidence is accumulating that some species will be negatively affected in the future by climate change and that reduction of existing stressors may not be sufficient to offset these impacts. Recent work suggests the shy albatross (Thalassarche cauta) will be adversely affected by projected changes in environmental conditions under plausible climate change scenarios. Furthermore, modelling shows that elimination of the principal present-day threat to albatrosses, fisheries bycatch, an achievable and critical priority, may not be sufficient to reverse projected population declines due to climate impacts, which cannot be directly eliminated. Here, a case study is presented in which a range of intervention options, in preparation for predicted climate change impacts, are identified and evaluated. A suite of 24 plausible climate adaptation options is first assessed using a semi-quantitative cost–benefit–risk tool, leading to a relative ranking of actions. Of these options, increasing chick survival via reduction of disease prevalence through control of vectors, was selected for field trials. Avian insecticide was applied to chicks’ mid-way through their development and the effect on subsequent survival was evaluated. Survival of treated chicks after six weeks was significantly higher (92.7%) than those in control areas (82.1%). This approach shows that options to enhance albatross populations exist and we argue that testing interventions prior to serious impacts can formalise institutional processes and allow refinement of actions that offer some chance of mitigating the impacts of climate change on iconic marine species.

Formal development of multi-agent systems using MAZE

MAZE is an extension of the Object-Z specification language supporting the specification and development of multi-agent systems (MAS). Following recommendations from the agent-oriented software engineering community, it supports three distinct levels of abstraction: (i) the macro level which focusses on the system's overall, global behaviour, independently of how the agents of the system operate and interact, (ii) the meso level which focusses on agent interactions, and (iii) the micro level which focusses on the operation of individual agents. Object-Z's high-level support for component-based specification, which is well suited to modelling MAS, is complemented in MAZE with support for action refinement to facilitate the top-down development process from the macro to micro level, and with a number of syntactic conventions aimed at abstractly specifying the low-level mechanisms required for dealing with asynchronous communication and timing constraints at the micro level. The latter are shorthands for existing Object-Z notation and so require no redefinition of Object-Z's semantics. In this paper, we provide an overview of MAZE and illustrate its use on a non-trivial case study: a swarm robotic algorithm for self-assembly.

Declarative event based models of concurrency and refinement in psi-calculi

Psi-calculi constitute a parametric framework for nominal process calculi, where constraint based process calculi and process calculi for mobility can be defined as instances. We apply here the framework of psi-calculi to provide a foundation for the exploration of declarative event-based process calculi with support for run-time refinement. We first provide a representation of the model of finite prime event structures as an instance of psi-calculi and prove that the representation respects the semantics up to concurrency diamonds and action refinement. We then proceed to give a psi-calculi representation of Dynamic Condition Response Graphs, which conservatively extends prime event structures to allow finite representations of (omega) regular finite (and infinite) behaviours and have been shown to support run-time adaptation and refinement. We end by outlining the final aim of this research, which is to explore nominal calculi for declarative, run-time adaptable mobile processes with shared resources.

Open Fuzzy Synchronized Petri Net

Designing Multi agent systems needs a high-level specification model which supports abstraction, dynamicity, openness and enables fuzziness. Since the model of Synchronized Petri Nets supports dynamicity and abstraction, we extend it by fuzziness, openness and interaction with environment. The proposed model called Open Fuzzy Synchronized Petri Nets (OFSyPN for short) associates action name with transitions and enables openness feature and interaction with environment. Each action has an uncertainty degree and places are typed. The authors give an operational semantics for OFSyPN in terms of Fuzzy Labeled Transition System (FLTS for short). FLTS is a semantics model, which allows a concise action refinement representation and deals with incomplete information through its fuzziness representation. Furthermore the structure can be used to produce a tree of potential concurrent design trajectories, named fuzzy labeled transition refinement tree (FLTRT for short). We exemplify the OFSyPN model thought a case study.

ST-structures

The present paper defines ST-structures (and an extension of these, called STC-structures). The main purpose is to provide concrete relationships between highly expressive concurrency models coming from two different schools of thought: the higher dimensional automata, a state-based approach of Pratt and van Glabbeek; and the configuration structures and unrestricted event structures, an event-based approach of van Glabbeek and Plotkin. In this respect we make comparative studies of the expressive power of ST-structures relative to the above models. Moreover, standard notions from other concurrency models are defined for ST-structures, like steps and paths, bisimilarities, and action refinement, and related results are given. These investigations of ST-structures are intended to provide a better understanding of the state-event duality described by Pratt, and also of the (a)cyclic structures of higher dimensional automata.

Fuzzy Labeled Transition Refinement Tree

This paper aims to provide a formal framework that supports an incremental development of dynamic systems such as multi agents systems (MAS). We propose a fuzzy labeled transition system model (FLTS for short). FLTS allows a concise action refinement representation and deals with incomplete information through its fuzziness representation. Afterward, based on FLTS model, we propose a refinement model called fuzzy labeled transition refinement tree (FLTRT for short). The FLTRT structure serves as a tree of potential concurrent design trajectories of the system. Also, we introduce bisimulation relations for both models in order to identify equivalent design trajectories, which could be assessed with respect to relevant design parameters.

Barriers and bridges to the adoption of environmentally-sustainable offerings

This research identifies the factors that inhibit the incorporation of environmentally-sustainable offerings into firms' operations, while outlining strategies that environmentally-sustainable suppliers can use to overcome such adoption barriers. A discovery-oriented approach analyzes twenty in-depth interviews with mid- and senior-level managers whose firms were faced with, and yet overcame, adoption barriers. Results indicate that supplier related barriers, such as associated costs, ease of use, suppliers' credibility, and their offerings' creativity and execution, and intraorganizational barriers, such as organizational structure and culture, inhibit adoption. The refinement and alignment of suppliers' actions, communications, and offerings were suggested to aid in overcoming the barriers. This research yields insights for both research and practice, as it provides a series of testable research propositions, supports several theories, and furnishes supplier firms with strategies to better position their firms and offerings.

Introducing extra operations in refinement

Abstract This paper reconsiders refinements which introduce actions on the concrete level which were not present at the abstract level. It considers a range of different basic refinement relations, covering the standard ones for formalisms like Event-B, Z, action systems, and CSP. It also describes a number of ways in which new operations may be introduced: extended interfaces, internal actions, stuttering steps, and action refinement. The main contribution of this paper is in exploring the interaction between those two dimensions. In particular, it shows how the “refining skip” method is incompatible with failures-based refinement relations, and consequently some decisions in designing Event-B refinement are more entangled than previously highlighted.

Perspicuity and Granularity in Refinement

This paper reconsiders refinements which introduce actions on the concrete level which were not present at the abstract level. It draws a distinction between concrete actions which are "perspicuous" at the abstract level, and changes of granularity of actions between different levels of abstraction. The main contribution of this paper is in exploring the relation between these different methods of "action refinement", and the basic refinement relation that is used. In particular, it shows how the "refining skip" method is incompatible with failures-based refinement relations, and consequently some decisions in designing Event-B refinement are entangled.

Incurred Sample Reanalysis: Different Evaluation Approaches on Data Obtained for Spironolactone and its Active Metabolite Canrenone

The inherent reproducibility of a bioanalytical approach is usually sustained through incurred sample reanalysis (ISR). Questions relating to the number of ISRs, the right moment for performing reanalysis, the way of performing an appropriate statistical refinement of experimental data and actions to be taken in the case of failure are frequently raised. Data resulting from ISR following a bioequivalence study for spironolactone formulations are discussed. Reanalysis of samples was carried out twice: immediately after the end of the study and after a period that overcame the long-term stability study achieved during method validation. The Bland-Altman approach was used to assess experimental results. ISR was successful over the short reanalysis period for both compounds. Data produced through reanalysis after the long-term period indicated a systematic positive bias for the metabolite canrenone (although results supported reproducibility). The results obtained for spironolactone were affected by a strong negative systematic bias and failed to support reproducibility. The explanation deals with the continuous conversion of spironolactone to canrenone in plasma samples. However, reproducibility of the method may be sustained by comparing original and repeated differences between concentration values in samples by means of a paired t-test, Wilcoxon sign rank-sum test and linear regression. Different statistical approaches for making data comparisons are discussed and may be successfully applied during reanalysis of samples from a bioequivalence study. Results of the evaluations may differ in accordance with the statistical procedure being applied, thus a definitive conclusion requires consideration of all specific experimental circumstances arising during production of the processed data.