Higher-level Phenomena Research Articles

Mechanisms that enhance Internet of Things engagement

Purpose By drawing on previous research on mechanism-based explanations and business-to-business engagement, the purpose of this study is to identify and define mechanisms that enhance Internet of Things (IoT) engagement. Design/methodology/approach By positioning the study within the paradigm of critical realism (CR), this paper used multiple case study research. This paper applied 12 in-depth, semi-structured interviews, an observation and firm documents as data-gathering tools. Findings This paper argues that the higher-level phenomenon (Institutional logic of the IoT ecosystem) leads to a higher-level outcome (IoT engagement). As lower-level situational mechanisms, this paper found IoT readiness and transparency in the ecosystem. Action-formation mechanisms were acknowledged as communication, availability of an IoT interface, and support. Commitment, trust, satisfaction and software maintenance and updates were recognized as transformational mechanisms. Practical implications The findings will help managers to understand which mechanisms to focus on when forming engagement strategies for onboarding new actors and strengthening relationships with existing actors. Furthermore, this paper suggests considering the IoT readiness of new actors more critically, as this mechanism was found to be the most crucial one for an early stage of engagement in an IoT ecosystem. Originality/value This study helps understand the causal structures behind engagement and enhances the theoretical and practical domain of IoT engagement. In addition, this study demonstrates the value of applying CR for generating knowledge about a phenomenon through causal explanations.

Measuring differential fitness costs and interactions between genetic cassettes using fluorescent spectrophotometry.

In this article, we present a method for designing, executing, and analyzing data from a microbial competition experiment. We use fluorescent reporters to label different competing strains and resolve individual growth curves using a fluorescent spectrophotometer. Our comprehensive data analysis pipeline integrates multiple experiments to simultaneously infer sources of variation, extract selection coefficients, and estimate the genetic contributions to fitness for various synthetic genetic cassettes (SGCs). To demonstrate the method, we employ a synthetic biological system based on Escherichia coli. Strains carry 1 of 10 different plasmids and one of three genomically integrated fluorescent markers. All strains are co-cultured to obtain real-time measurements of optical density (total population density) and fluorescence (sub-population densities). We identify challenges in calibrating between fluorescence and density and of fluorescent proteins maturing at different rates. To resolve these issues, we compare two methods of fluorescence calibration and correct for maturation by measuring in vivo maturation times. We provide evidence of genetic interactions occurring between our SGCs and further show how to use our statistical model to test some hypotheses about microbial growth and the costs of protein expression.IMPORTANCEFluorescently labeled co-cultures are becoming increasingly popular. The approach proposed here offers a high standard for experimental design and data analysis to measure selection coefficients and growth rates in competition. Measuring competitive differences is useful in many laboratory studies, allowing for fitness cost-correction of growth rates and ecological interactions and testing hypotheses in synthetic biology. Using time-resolved growth curves, rather than endpoint measurements, for competition assays allows us to construct a detailed scientific model that can be used to ask questions about fine-grained phenomena, such as bacterial growth dynamics, as well as higher-level phenomena, such as the interactions between synthetic cassette expression.

Editor's Introduction: Best Papers from the 20th International Conference on Cognitive Modeling.

The International Conference on Cognitive Modelling is dedicated to understanding how the complex processes of the mind can be explained in terms of detailed inner processing. In this issue, we present four representative papers of this field of research from our 20th meeting, ICCM 2022. This meeting was our first hybrid meeting, with a virtual version happening July 11-15, 2022, and an in-person event from July 23-27, 2022, held in Toronto, Canada. The four papers presented here were the top-ranked papers across both the virtual and in-person events. Three of the papers develop novel computational theories about low-level components within the mind and how those components result in high-level phenomena such as motivation, anhedonia, and attention. The final paper demonstrates the use of cognitive modeling to develop novel explanations of a paired associate learning task, and uses those insights to develop and explain human performance in a more complex version of that task.

The Stroop effect and mental imagery.

The classic Stroop task is very simple: you have to name the color of words printed on a page. If these words are color words (like "red" or "blue"), where the color named and the color it is printed in are different (say, "red" printed in blue), the reaction time increases significantly. My aim is to argue that the existing psychological explanations of the Stroop effect need to be supplemented. The Stroop effect is not exclusively about access to motor control. It is also, to a large extent, about interferences in perceptual processing. To put it briefly, reading the color word triggers-laterally and automatically-visual imagery of the color and this interferes with the processing of the perceived color of the word. In other words, the Stroop effect is to a large extent a sensory phenomenon, and it has less to do with attention, conflict monitoring, or other higher-level phenomena.

Agential possibilities

We ordinarily think that we human beings have agency: we have control over our choices and make a difference to our environments. Yet it is not obvious how agency can fit into a physical world that is governed by exceptionless laws of nature. In particular, it is unclear how agency is possible if those laws are deterministic and the universe functions like a mechanical clockwork. In this short paper, I first explain the apparent conflict between agency and physical determinism (referring to recent work by Helen Steward), then review some salient responses one might give to this conflict, and finally sketch a response that rests on a distinction between “physical” and “agential possibilities.” Agency, I suggest, is a higher-level phenomenon, which comes with its own level-specific notion of possibility, and it cannot be adequately analyzed in physical terms alone or just through the lens of physical possibility.

Thriving together: conceptual and methodological considerations for examining thriving in interdependent sport

ABSTRACT Despite conceptual advances and preliminary associations highlighting the benefits of thriving in sport, opportunities for continued research are numerous. Notably, sport-specific research involving thriving has predominantly taken an individual athlete perspective. Interestingly, evidence from the organisational domain suggests that thriving can manifest at a collective level through interdependent team member interactions. Given the potential for thriving to emerge as a higher-level phenomenon in interdependent sport, a critique of thriving at the group-level is advanced. More specifically, we provide a summary of existing individual athlete thriving literature and organisational thriving research at the group-level (Part 1), propose three approaches to conceptualising thriving in interdependent sport (i.e. common, team, and collective thriving) grounded in multilevel research (Part 2), pose guiding questions and key considerations for future exploration (Part 3), and conclude by emphasising the potential value of examining thriving as a higher-level construct for sport researchers and invested partners (Part 4).

Uniting Contemplative Theory and Scientific Investigation: Toward a Comprehensive Model of the Mind

ObjectivesResearch into meditation-related emergent phenomenology is advancing, yet progress is hampered by significant incongruities between meditator self-reports and objective measurements (e.g., of brain states). We address these incongruities by developing and demonstrating the potential of contemplative theory to support scientific investigation.MethodOur approach is to translate key theories from Buddhist contemplative traditions into scientific terms, and then systematize these translations as a functionalist model of the mind—the Thin Model—able to inform scientific inquiry.ResultsBuddhist doctrine is shown to be consistent with objective descriptions of mental function, and the Thin Model derived from these translations demonstrates immediate explanatory power. The nested nature of the model allows explanations to be restricted to the specific problem being studied. The model enables connection of complex higher-level phenomena, such as self-reports of mental states, to complex lower-level phenomena, such as empirically measured brain states. This connection does not require simplistic assumptions to be made. A detailed demonstration illustrates how the model can convert subjective accounts of the ecstatic meditative states known as jhānas into testable neuroscientific hypotheses.ConclusionsWe provide an account of contemplative theory that is amenable to scientific investigation. Our approach, exemplified in the Thin Model, offers immediate explanatory power, allows meaningful dialogue between different research traditions, and provides an organizing principle for explanations of mental phenomena. The Thin Model may also be relevant to other fields concerned with autonomous entities or the nature and operation of the mind.

Extending the two-component model of delusion to substance use disorder etiology and recovery

The brain disease model (BMDA) and psychosocial models of addiction attend to phenomena at different levels of biological organization, and evidence suggests neither is sufficient to explain substance use disorder (SUD). Here, we extend a Bayesian model of the emergence and persistence of delusions to SUD etiology and recovery, building upon efforts to link lower-level impacts of psychoactive compounds to higher-level phenomena such as attitudes, beliefs, and self-control. According to the resulting two-component model of SUD, psychoactive substances interact with genetic and environmental factors to produce delusions about the biological importance of substance use and its contexts by perturbating basic human affective systems. These delusions are most often revised or rejected based on individuals’ existing belief systems. But in some individuals, factors explaining the persistence of an array of delusions (e.g., lower levels of executive functioning) prevent the evaluation and revision system from rejecting or revising beliefs that attribute high salience to substance-related stimuli. This theory provides novel hypotheses regarding the potential roles of factors such as dichotomous thinking, positive illusions and self-deception, and denial or lack of awareness in SUD etiology and recovery. Furthermore, it provides an account of SUD that may result in less stigma than the BDMA.

Bridging Hierarchies in Multi-Scale Models of Neural Systems: Look-Up Tables Enable Computationally Efficient Simulations of Non-linear Synaptic Dynamics.

Synapses are critical actors of neuronal transmission as they form the basis of chemical communication between neurons. Accurate computational models of synaptic dynamics may prove important in elucidating emergent properties across hierarchical scales. Yet, in large-scale neuronal network simulations, synapses are often modeled as highly simplified linear exponential functions due to their small computational footprint. However, these models cannot capture the complex non-linear dynamics that biological synapses exhibit and thus, are insufficient in representing synaptic behavior accurately. Existing detailed mechanistic synapse models can replicate these non-linear dynamics by modeling the underlying kinetics of biological synapses, but their high complexity prevents them from being a suitable option in large-scale models due to long simulation times. This motivates the development of more parsimonious models that can capture the complex non-linear dynamics of synapses accurately while maintaining a minimal computational cost. We propose a look-up table approach that stores precomputed values thereby circumventing most computations at runtime and enabling extremely fast simulations for glutamatergic receptors AMPAr and NMDAr. Our results demonstrate that this methodology is capable of replicating the dynamics of biological synapses as accurately as the mechanistic synapse models while offering up to a 56-fold increase in speed. This powerful approach allows for multi-scale neuronal networks to be simulated at large scales, enabling the investigation of how low-level synaptic activity may lead to changes in high-level phenomena, such as memory and learning.

A robust model of Stimulus-Specific Adaptation validated on neuromorphic hardware

Stimulus-Specific Adaptation (SSA) to repetitive stimulation is a phenomenon that has been observed across many different species and in several brain sensory areas. It has been proposed as a computational mechanism, responsible for separating behaviorally relevant information from the continuous stream of sensory information. Although SSA can be induced and measured reliably in a wide variety of conditions, the network details and intracellular mechanisms giving rise to SSA still remain unclear. Recent computational studies proposed that SSA could be associated with a fast and synchronous neuronal firing phenomenon called Population Spikes (PS). Here, we test this hypothesis using a mean-field rate model and corroborate it using a neuromorphic hardware. As the neuromorphic circuits used in this study operate in real-time with biologically realistic time constants, they can reproduce the same dynamics observed in biological systems, together with the exploration of different connectivity schemes, with complete control of the system parameter settings. Besides, the hardware permits the iteration of multiple experiments over many trials, for extended amounts of time and without losing the networks and individual neural processes being studied. Following this “neuromorphic engineering” approach, we therefore study the PS hypothesis in a biophysically inspired recurrent networks of spiking neurons and evaluate the role of different linear and non-linear dynamic computational primitives such as spike-frequency adaptation or short-term depression (STD). We compare both the theoretical mean-field model of SSA and PS to previously obtained experimental results in the area of novelty detection and observe its behavior on its neuromorphic physical equivalent model. We show how the approach proposed can be extended to other computational neuroscience modelling efforts for understanding high-level phenomena in mechanistic models.

A Minimal Framework for Describing Living Systems: A Multi-Dimensional View of Life Across Scales.

The almost limitless complexity of biology has led to two general approaches to understanding biological phenomena. One approach is dominated by reductionism in which high-level phenomena of whole systems are viewed as emerging from relatively simple and generally understood interactions at a substantially lower level. Although this approach is theoretically general, it can become intractable in practice when attempting to simultaneously explain a wide range of systems. A second approach is for specialists to investigate biological phenomena within one of many different hierarchical levels of description that are separated to decouple from concerns at other levels. Although this approach reduces the explanatory burden on specialists that operate within each level, it also reduces integration from insights gained at other levels. Thus, as beneficial as these approaches have been, they limit the scope and integration of knowledge across scales of biological organization to the detriment of a truly synoptic view of life. The challenge is to find a theoretical and experimental framework that facilitates a broader understanding of the hierarchy of life-providing permeability for the exchange of ideas among disciplinary specialists without discounting the peculiarities that have come to define those disciplines. For this purpose, coarse-grained, scale-invariant properties, and resources need to be identified that describe the characteristic features of a living system at all spatiotemporal scales. The approach will be aided by a common vernacular that underscores the realities of biological connections across a wide range of scales. Therefore, in this vision paper, we propose a conceptual approach based on four identified resources-energy, conductance, storage, and information (ECSI)-to reintegrate biological studies with the aim of unifying life sciences under resource limitations. We argue that no functional description of a living system is complete without accounting for at least all four of these resources. Thus, making these resources explicit will help to identify commonalities to aid in transdisciplinary discourse as well as opportunities for integrating among the differently scoped areas of specialized inquiry. The proposed conceptual framework for living systems should be valid across all scales and may uncover potential limitations of existing hypotheses and help researchers develop new hypotheses addressing fundamental processes of life without having to resort to reductionism.

SADOIY VA G‘OZIY DEVONLARIDA ALISHER NAVOIY AN'ANALARI(HAMD, NA'T, MUNOJOT VA MANQABAT MAVZULARIDAGI G‘AZALLAR MISOLIDA)

Literary continuity is a unique cultural, high-level literary phenomenon in which the concepts of creative inspiration, imitation and the continuation of great talent are one of the most important features of Eastern classical literature. Regardless of which branch of art is formed in this cultural and literary process, it becomes clear that the main goal is to "renew", learning "from the past" and developing their ideas and artistic abilities. The article examines the issues of tradition and originality of poems by Mirhasan Sadoi and Muhammad Gazi, who grew up in the workshop of Alisher Navoi. The poet's poems analyze the artistic perfection of the Salaf traditions on this topic from an ideological and artistic point of view.Key words: devan, theme, idea, artistic symbol, art, tradition and originality.

Conceptual difficulties of applying the theory of mirror neurons in the neural network tools of artificial societies

The article presents a methodological analysis of the neurophysiological concepts of mirror neurons, which offer both explanatory models of the functioning of consciousness and social interaction, and the development of their computer model. The physicalist project for the study of consciousness and social interaction, based on the study of mirror neurons, tries to offer a highly specialized, neurobiological explanation of consciousness and social interaction. The two most priority tasks of this project are: through the most accurate study and description of the functioning of the natural neurobiological system, to offer an explanation of natural high-level (relative to the neurobiological level) mental and social phenomena and phenomena; and based on the neurobiological methodological apparatus, the creation of such an artificial system that, like the natural, neurobiological one, would have a mentality and could enter into social interaction. These tasks are directly related to the reductionist natural science attitude, which assumes the existence of a strict causal connection between the neural organization and the functioning of consciousness and social interaction. The article considers the possibility of combining neurophysiological data on the work of mirror neurons and interpretations in the understanding of consciousness, as well as the possibility of creating their computer model. As a result, arguments are proposed both against the restriction of the methodology of scientific research of social and mental phenomena exclusively by natural scientific practices, and the need to distinguish between low-level neurobiological processes and high-level mental and social phenomena. Using these arguments, the authors hypothesize that the study of the brain is insufficient to create artificial systems endowed with consciousness and capable of entering into social interaction.

The Effect of Tropical Cyclone Nicholas (11–20 February 2008) on Sea Level Anomalies in Indonesian Waters

As reported extensively in both electronic and print media in Indonesia, high wave and anomalously high sea level phenomena occurred in February 2008 in Indonesian waters, mainly along the western coast of Sumatra and the southern coasts of Java-Bali. Tropical Cyclone (TC) Nicholas, occurring in northwestern coastal waters of Australia between 11 and 20 February 2008, might have contributed to the existence of these phenomena in the Indonesian region. This study focused on investigating the effect of TC Nicholas on the increases in sea levels in the Indonesian waters by analyzing residual water levels (non-astronomic tide). In this regard, a storm tide event (the sum of the astronomical tide and storm surge generated by the TC Nicholas) was simulated in this region using the Regional Ocean Modeling System (ROMS). The residual water levels were obtained by removing the tidal part (astronomic tide) from the ROMS simulated total water levels. In addition, to confirm possible influences of TC Nicholas, a lagged correlation analysis was applied between atmospheric pressure at the center of TC Nicholas and residual water level oscillations in the Indonesian waters. It was found that the residual water levels showed a strong correlation with the atmospheric pressure at the center of TC Nicholas in some areas of the Indonesian seas, such as the western coast of Sumatra, the southern coast of Java, Lesser Sunda Islands, and the southern coast of Papua. The increased sea levels on the western coast of Sumatra are up to 16 cm, with TC Nicholas leading the residual water level by 4.18 days (TL: time lag). Meanwhile, they are up to 20 cm (TL = 5.75 days), 21 cm (TL = 1.12 days), and 38 cm (TL = 3.96 days) on the southern coast of Java, the Lesser Sunda Islands, and the southern coast of Papua, respectively. The results of this study could be used as an initial assessment to investigate the most vulnerable Indonesian coastal areas to the impact of the TC and they might be significantly beneficial for designing both a proper disaster risk reduction program and investment policies in the region, particularly in the context of flood risk reduction and adaptation.

Exploring the microfoundations of nomadic dynamic capabilities: The example of flying winemakers

Using the illustration of flying winemakers, this conceptual paper looks at international entrepreneurship and the microfoundations of dynamic capabilities to explore how nomad entrepreneurs manage dynamic capabilities in global contexts. We first identify the key features of nomad entrepreneurs and their relationship with their environment to conceptualize nomadic dynamic capabilities. We then analyze the specific role of knowledge transfer in managing nomadic dynamic capabilities and put forward a stylized model of the microfoundations of nomadic dynamic capabilities. We contribute to the international entrepreneurship and global dynamic capabilities literature by investigating the role of nomad entrepreneurs as connectors both across and beyond borders for globalized industries. We also contribute to the microfoundations of the dynamic capabilities stream of literature by emphasizing the sources of nomadic dynamic capabilities and their role in a micro-level driven research agenda in terms of the concrete actions of nomad entrepreneurs to elucidate higher-level phenomena.

Empirical Consequences of Emergent Mass

The Lagrangian that defines quantum chromodynamics (QCD), the strong interaction piece of the Standard Model, appears very simple. Nevertheless, it is responsible for an astonishing array of high-level phenomena with enormous apparent complexity, e.g., the existence, number and structure of atomic nuclei. The source of all these things can be traced to emergent mass, which might itself be QCD’s self-stabilising mechanism. A background to this perspective is provided, presenting, inter alia, a discussion of the gluon mass and QCD’s process-independent effective charge and highlighting an array of observable expressions of emergent mass, ranging from its manifestations in pion parton distributions to those in nucleon electromagnetic form factors.

Free will as a higher-level phenomenon?

List (2014, 2019) has recently argued for a particular view of free will as a higher-level phenomenon compatible with determinism. According to List, one could refute his account by showing that determinism at the physical level implies the impossibility of doing otherwise at the agential level. This paper takes up that challenge. Based on assumptions to which List's approach is committed, I provide a simple probabilistic model that establishes the connection between physical determinism and the impossibility of doing otherwise at the agential level that is needed to refute free will as a higher-level phenomenon.

Байесовский разум и природа сознания

В статье оценивается способность программы предсказывающей обработки и байесовских моделей познавательных процессов внести вклад в совре­менные исследования сознания. Автор отталкивается от вопроса, рассмот­ренного в недавних работах философов Э. Кларка и Н. Блока, а именно: если механизмы восприятия, как предполагается сторонниками байесов­ских моделей познавательных процессов, являются вероятностными, то по­чему сознание не отражает в себе характер находящихся в его основании вероятностных перцептивных репрезентаций? При этом, в противополож­ность Кларку и Блоку, автор указывает на отсутствие оснований полагать, что сознание как высокоуровневый феномен в принципе должно отражать в себе характеристики каких-либо более базовых процессов и репрезента­ций. Соответственно предпочтение отдается именно вопросу о возможно­стях и ограничениях байесовских моделей в когнитивной науке, психоло­гии и нейронауке в деле объяснения человеческого опыта. С целью ответа на этот вопрос в работе в первую очередь исследуется статус самих байе­совских моделей познавательных процессов, относительно которого среди исследователей существуют значительные разногласия. Утверждается, что байесовские модели в когнитивной науке, психологии и нейронауке могут формулироваться на всех трех уровнях анализа систем обработки инфор­мации по Д. Марру. При этом приоритетным для байесовских моделей является вычислительный уровень по Марру, предполагающий описание вы­числительной задачи и доступной организму информации в среде. Тем не ме­нее указывается, что к настоящему моменту применительно к исследовани­ям сознания преимущественное развитие получили модели, относящиеся к уровню системы репрезентации и алгоритмов по Марру. В заключение выдвигается предположение, что, чтобы охарактеризовать сознание с по­зиции вычислительного уровня по Марру, программе предсказывающей обработки, вероятно, потребуется интеграция с теорией глобального рабо­чего пространства.

XII—What’s Wrong with the Consequence Argument: A Compatibilist Libertarian Response

Abstract The most prominent argument for the incompatibility of free will and determinism is Peter van Inwagen’s consequence argument. I offer a new diagnosis of what is wrong with this argument. Proponents and critics typically accept the way the argument is framed, and only disagree on whether the premisses and rules of inference are true. I suggest that the argument involves a category mistake: it conflates two different levels of description, namely, the physical level at which we describe the world from the perspective of fundamental physics and the agential level at which we describe agents and their actions. My diagnosis is based on an account of free will as a higher-level phenomenon. I call this account ‘compatibilist libertarianism’, for reasons that will become clear. Although the paper addresses a primarily metaphysical question, it uses tools similar to those employed in philosophy-of-science work on determinism and indeterminism, higher-level phenomena, and dynamical systems.

Two Kinds of High-Level Probability

AbstractAccording to influential views the probabilities in classical statistical mechanics and other special sciences are objective chances, although the underlying mechanical theory is deterministic, since the deterministic low level is inadmissible or unavailable from the high level. Here two intuitions pull in opposite directions: One intuition is that if the world is deterministic, probability can only express subjective ignorance. The other intuition is that probability of high-level phenomena, especially thermodynamic ones, is dictated by the state of affairs in the world. We argue in support of this second intuition and we show that in fact there are two different ways in which high-level probability describes matters of fact, even if the underlying microscopic reality is deterministic. Our analysis is novel, but supports approaches by, e.g., Loewer, Albert, Frigg and Hoefer, List and Pivato. In particular, the reductive view we propose here can be seen as a naturalization of the above approaches. We consider consequences of our result for nonreductive physicalist approaches, such as functionalism, that admit multiple realization of the kinds that appear in the special sciences by physical kinds. We show that nonreductive physicalism implies the existence of nonphysical matters of fact.