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Purpose: This study aimed to assess the prevalence of literature applying LHS and learning organisation (LO) concepts to rehabilitation, gather definitions and core features, and document their application and resultant organisational changes., Materials and Methods: We searched five electronic databases and included peer-reviewed qualitative, quantitative, and mixed-methods studies, reviews, and grey literature in English. Full texts were screened, resulting in 27 included papers., Results: Most of the included papers discussed the concept of LHS, emphasising key aspects like infrastructure and learning mechanisms. However, only a minority described practical implementation ( n  = 4) or assessed the effects of applying LHS frameworks within rehabilitation settings ( n  = 1)., Conclusions: This scoping review highlights the limited empirical focus on implementing and operationalising LHS frameworks in rehabilitation services. Based on the available literature, we offer recommendations for rehabilitation services transitioning to a LHS. Our findings emphasise the need for increased dissemination of knowledge and research on the implementation and evaluation of rehabilitation-focused LHS.

The action of ozone in medicine is a subject of interest and lively, controversial debates. Its mechanisms of action are still far from fully understood. However, it is possible that ozone triggers a series of dynamics in living organisms related to chaos, multi-stable phenomena, and oscillatory processes. Ozone may be involved in adaptive chaos. Adaptive chaos in health and the reduction of complexity in pathology are interconnected phenomena that describe the functional dynamics of biological systems. Adaptive chaos refers to a state of controlled, complex, and flexible behaviour exhibited by healthy biological systems. It allows for a dynamic balance between order and unpredictability, enabling the system to respond to various internal and external stimuli. In pathological states, the system loses its adaptive chaos, often becoming either too rigid or overly chaotic. This reduction in complexity limits the ability of the system to respond effectively to stimuli, making it prone to dysfunction. This paper addresses the role of ozone in these scenarios., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The preference for simple explanations, known as the parsimony principle, has long guided the development of scientific theories, hypotheses, and models. Yet recent years have seen a number of successes in employing highly complex models for scientific inquiry (e.g., for 3D protein folding or climate forecasting). In this paper, we reexamine the parsimony principle in light of these scientific and technological advancements. We review recent developments, including the surprising benefits of modeling with more parameters than data, the increasing appreciation of the context-sensitivity of data and misspecification of scientific models, and the development of new modeling tools. By integrating these insights, we reassess the utility of parsimony as a proxy for desirable model traits, such as predictive accuracy, interpretability, effectiveness in guiding new research, and resource efficiency. We conclude that more complex models are sometimes essential for scientific progress, and discuss the ways in which parsimony and complexity can play complementary roles in scientific modeling practice., Competing Interests: Competing interests statement:The authors declare no competing interest.

Introduction: The Spanish National Health System has defined complexity as a set of factors of increased difficulty that require the intervention of a palliative care team . Palliative care aims to improve the quality of life of patients with chronic terminal illnesses. This study aims to describe the degree of complexity of cancer patients in palliative care, to determine which elements of complexity are most prevalent and to determine which other hospital clinical factors are associated with the level of complexity., Methods: This study is a descriptive, observational, and cross-sectional analysis that included patients diagnosed with advanced oncological pathology undergoing palliative treatment who were admitted to the Medical Oncology ward of the Miguel Servet University Hospital between March and April 2023., Result: A total of 100 patients were selected for the study. According to the IDC-Pal, 68% of patients were classified as highly complex, 26% of patients were complex and only 6% of patients were classified as non-complex. The presence of pain ( P < .001), nausea and vomiting ( P = .027), depression ( P = .033) and functional status ( P = .011) were statistically independent predictors of high complexity., Discussion: This study has shown that a high proportion of hospitalized palliative care cancer patients have high complexity, suggesting a good matching of healthcare resources to patient complexity. Four factors related to complexity have been identified, namely pain, nausea and vomiting, depression and a bedridden functional state. The presence of any of the 4 factors could help healthcare professionals to identify patients for early specialized palliative care., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Introduction: HIV infection has become a chronic disease with a good long-term prognosis, necessitating a change in the care model. For this study, we applied a proposal for an Optimal Care Model (OCM) for people with HIV (PHIV), which includes tools for assessing patient complexity and their classification into profiles to optimize care provision., Methods: Observational, cross-sectional, and retrospective study. Adult PHIV treated at the Tropical Medicine consultations at Ramón y Cajal Hospital from January 1 to June 30, 2023, were included. The complexity calculation and the stratification into profiles for each patient were done according to the OCM., Results: Ninety-four participants were included, 76.6% cisgender men, with a median age of 41 years (range 23-76). Latin America and Africa were the main regions of origin (72.4%). 98% had an undetectable HIV viral load. The degree of complexity was 78.7% low, 11.7% medium, 1% high, and 8.5% extreme. The predominant profile was blue (64.9%), followed by lilac (11.7%), purple (6.3%), and green (4.3%). 7.4% were unclassifiable, of whom 57.2% had high/extreme complexity. Among the unclassifiable, mental health problems were the most common., Conclusions: The OCM tools for People Living with HIV (PLWH) allow for the classification and stratification of most patients in a consultation with a non-standard population. Patients who did not fit into the pre-established profiles presented high complexity. Creating a profile focused on mental health or mixed profiles could facilitate the classification of more patients., (Copyright © 2024 Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. Published by Elsevier España, S.L.U. All rights reserved.)

Humans can remember a vast amount of scene images; an ability often attributed to encoding only low-fidelity gist traces of a scene. Instead, studies show a surprising amount of detail is retained for each scene image allowing them to be distinguished from highly similar in-category distractors. The gist trace for images can be relatively easily captured through both computational and behavioural techniques, but capturing detail is much harder. While detail can be broadly estimated at the categorical level (e.g. man-made scenes more complex than natural), there is a lack of both ground-truth detail data at the sample level and a way to operationalise it for measurement purposes. Here through three different studies, we investigate whether the perceptual complexity of scenes can serve as a suitable analogue for the detail present in a scene, and hence whether we can use complexity to determine the relationship between scene detail and visual long term memory for scenes. First we examine this relationship directly using the VISCHEMA datasets, to determine whether the perceived complexity of a scene interacts with memorability, finding a significant positive correlation between complexity and memory, in contrast to the hypothesised U-shaped relation often proposed in the literature. In the second study we model complexity via artificial means, and find that even predicted measures of complexity still correlate with the overall ground-truth memorability of a scene, indicating that complexity and memorability cannot be easily disentangled. Finally, we investigate how cognitive load impacts the influence of scene complexity on image memorability. Together, findings indicate complexity and memorability do vary non-linearly, but generally it is limited to the extremes of the image complexity ranges. The effect of complexity on memory closely mirrors previous findings that detail enhances memory, and suggests that complexity is a suitable analogue for detail in visual long-term scene memory., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Changes to the variability within biomechanical signals may reflect a change in the health of the human system. However, for running gait variability measures calculated from wearable device data, it is unknown whether a between-day difference reflects a shift in system dynamics reflective of a change in human health or is a result of poor between-day reliability of the measurement device or the biomechanical signal. This study investigated the reliability of stride time and sacral acceleration variability measures calculated from inertial measurement units (IMUs). Nineteen runners completed six treadmill running trials on two occasions seven days apart. Stride time and sacral acceleration signals were obtained using IMUs. Stride time variability and complexity were calculated using the coefficient of variation (CV) and detrended fluctuation analysis (DFA), respectively. Sacral acceleration regularity was quantified using sample entropy with a range of input parameters m (vector length) and r (similarity threshold). Between-day reliability was assessed using the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and minimum detectable change. Stride time CV displayed moderate relative reliability (ICC = 0.672), but with a large absolute minimum detectable change = 0.525 %, whilst stride time DFA-α displayed poor relative reliability (ICC = 0.457) and yielded large minimum detectable changes (≥ 0.208). Sample entropy displayed good relative reliability in mediolateral and resultant sacral acceleration signals for certain combinations of the parameters m and r, although again with large minimum detectable changes. Researchers should be cognisant of these reliability metrics when interpreting changes in running gait variability measures in clinical contexts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: This study aimed to identify the fluence smoothing threshold that preserves the dosimetric quality of planning for breast cancer intensity-modulated radiation therapy (IMRT)., Material and Methods: We conducted automated treatment planning for 60 breast cancer patients using the Eclipse Scripting Application Programming Interface. The plans included four-field IMRT, emphasizing smoothing weight combinations while maintaining a 4:3 aspect ratio between the X and Y directions. Four weight sets (40 × 30, 100 × 75, 150 × 115.2, and 200 × 150) were tested, resulting in four plans per patient. A total dose of 40.05 Gy over 15 fractions was prescribed. Optimization weigths were dynamically adjusted based on dosimetric evaluations, with the maximum coverage priority set at 200. Statistical analyses were used to assess the dosimetric data., Results: The median planning target volume (PTV) coverage varied across smoothing levels, with default smoothing (40 × 30) providing superior median PTV coverage. Lung constraints showed significant differences mainly at higher smoothing levels. Heart constraints exhibited less variation between smoothing levels, with significant differences primarily in the maximum and mean doses for right-sided patients and between default and higher smoothing levels for left-sided patients. No significant differences were observed in contralateral breast constraints among all smoothing levels, except at the maximum level for right-sided patients. Monitor units decreased with increasing smoothing weight, showing significant differences between default and other settings. For right-sided patients, the median number of monitor units varied from 1346 (40 × 30) to 754 (200 × 150), and for left-sided patients, from 1333 (40 × 30) to 804 (200 × 150). Chi-square tests revealed differences in dose constraint adherence between default and maximum smoothing levels, particularly in target coverage., Conclusion: Our findings suggest that using a ratio of smoothing weights to target priorities between 1:1.5 and 1:1.6 leads to a favorable balance between complexity and dosimetric plan quality, with no significant impacts on dose constraint adherence., (© 2024 The Author(s). Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Objective: This article, based on a plenary presentation from ICCH 2024, examines the challenge of balancing objectivity and complexity, and the risk of violent simplification, when it comes to teaching and assessing interprofessional healthcare communication., Discussion: Interpersonal communication, that is, conversation, makes all aspects of human social life possible. Conversation is complex and is managed by participants in emergent and dynamic ways. To facilitate the practical needs of teaching and assessment, we simplify conversation into produced objectivities that reflect disciplinary and dominant cultural norms and values at the time of their creation. These objectivities do not necessarily adequately reflect the way in which conversations unfold in dynamic, participant-managed ways as they often list specific contextualized behaviors rather than the context-free system of conversation. Despite this, they often become standardized and used in ways that can lead to harm for students, patients and carers, and educators. This violent simplification is made possible through educational and healthcare systems that reinforce disciplinary silos and underinvest in communication education., Conclusions: Engaging with the complexity of conversation within our educational practices is necessary to reduce the risk of harm. This involves explicit consideration of how objective tools are created and used in communication education, increased investment from education and healthcare sectors, and integrating knowledge about how conversation works from research of communication-in-practice., Competing Interests: Declaration of Competing Interest The author declares that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose : External factors can disrupt postural control, but the intricate workings of the postural control system enable an appropriate response. This study seeks to assess how external perturbations affect postural control. Methods : Twenty women participated in study, which consisted four trials involved quiet standing and experiencing induced perturbations by being struck with a boxing bag from the back, right, and left sides, respectively. The center of pressure (CoP) path length was recorded for each of the mentioned trials. Sample Entropy (SampEn), Lyapunov Exponent (LyE), and Fractal Dimension (FD) were computed for the CoP time series, separately for the anterior-posterior (AP) and mediolateral (ML) directions. The nonparametric Friedman ANOVA with Dunn-Bonferroni post-hoc analysis was employed to investigate the influence of external perturbations on both linear and nonlinear parameters on postural control. Results : The post-hoc analysis showed for LyE&#95;AP&#95;quiet (1.02 ± 0.18) significantly higher values than for LyE&#95;AP&#95;right (0.92 ± 0.22) and significantly higher for LyE&#95;AP&#95;left. Lyapunov Exponent was the parameter that differentiated the most between samples. Conclusions : The greatest number of significant differences between samples were demonstrated by the Lyapunov Exponent. This nonlinear parameter should be used to evaluate various perturbations during upright position in healthy subjects., (© 2024 Justyna Kędziorek et al., published by Sciendo.)

Multicellularity spans a wide gamut in terms of complexity, from simple clonal clusters of cells to large-scale organisms composed of differentiated cells and tissues. While recent experiments have demonstrated that simple forms of multicellularity can readily evolve in response to different selective pressures, it is unknown if continued exposure to those same selective pressures will result in the evolution of increased multicellular complexity. We use mathematical models to consider the adaptive trajectories of unicellular organisms exposed to periodic bouts of abiotic stress, such as drought or antibiotics. Populations can improve survival in response to the stress by evolving multicellularity or cell differentiation-or both; however, these responses have associated costs when the stress is absent. We define a parameter space of fitness-relevant traits and identify where multicellularity, differentiation, or their combination is fittest. We then study the effects of adaptation by allowing populations to fix mutations that improve their fitness. We find that while the same mutation can be beneficial to populations of different complexity, e.g., strict unicellularity or life cycles with stages of differentiated multicellularity, the magnitudes of their effects can differ and alter which is fittest. As a result, we observe adaptive trajectories that gain and lose complexity. We also show that the order of mutations, historical contingency, can cause some transitions to be permanent in the absence of neutral evolution. Ultimately, we find that continued exposure to a selective driver for multicellularity can either lead to increasing complexity or a return to unicellularity., Competing Interests: Competing interests statement:The authors declare no competing interest.

Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogram (EEG) plays an important role in diagnosing PD as it offers a non-invasive continuous assessment of the disease progression and reflects these complex patterns. This study focuses on the non-linear analysis of resting state EEG signals in PD, with a gender-specific, brain region-specific, and EEG band-specific approach, utilizing recurrence plots (RPs) and machine learning (ML) algorithms for classification. For this an open EEG dataset consisting of 14 PD and 14 healthy (HC) subjects is utilized. Recurrence plots and cross-recurrence plots (CRPs) were constructed for each frequency band and brain region, extracting complexity measures such as determinism (DET) and entropy (ENT). The interpretability of the ML model decisions is investigated using explainability technique. The scattered distribution of points in RPs of male PD individuals reflects the complex and dynamic nature of abnormal brain function. Also, CRPs confirms the enhanced effect of Beta Gamma synchronization during PD in the Parietal region. Low DET and high ENT corresponds to the complex non-linear characteristics of EEG signals and brain neuronal circuits during PD condition in male subjects. The extracted recurrence features served as inputs to the ML models, which achieved high classification performance, across all the scenarios. This study demonstrates the potential of recurrence plot-based complexity analysis combined with machine learning for the gender-specific, region-specific, and band-specific assessment of EEG signals during resting state in Parkinson's disease., Competing Interests: Declarations. Competing interests: The authors have no relevant financial or non-financial interests to disclose., (© 2025. Australasian College of Physical Scientists and Engineers in Medicine.)

This paper explores the intersections of constructal thermodynamics, and its semantic ontology within the context of autopoetic, digital and computational design in protocell inspired numerical architectural and urban narratives that are examined here as open systems. Constructal law is the thermodynamic theory based on the analysis of fluxes across the border of an open system. Protocells, as dynamic and adaptive open finite size systems, serve in this paper as a compelling metaphor and design model for responsive and sustainable manmade architectural and urban environments. The ability of protocells to harness energy, minimize entropy, and adapt to environmental changes mirrors the principles of constructal thermodynamics, which govern the flow and distribution of resources in complex self-organizing information open systems in nature. By applying these principles to digital architecture, this study investigates how relational dynamics between spaces, materials, and functions can create adaptive designs that "go with the flow" of ecological and cultural systems. The research demonstrates using the Gouy-Stodola theorem as a variational principle, how protocell-inspired processes facilitate exergy-efficient designs, minimizing waste while maximizing resilience and flexibility. The present through an applied case study argues for a paradigm where protocell digital architecture serves not only as an ecological and material model but also as a spatial narrative driver, blending constructal and digital tools with cultural mythos. Finally, this paper exploring simultaneously the semantic complexity of such systems, in turn, connects these constructal driven digital designs to broader méta-narratives, embedding cultural, symbolic, philosophical and functional predicates into architectural forms., Competing Interests: Declaration of Competing Interest ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier B.V.)

Importance: The pathophysiology of ADHD is complicated by high rates of psychiatric comorbidities, thus delineating unique versus shared functional brain perturbations is critical in elucidating illness pathophysiology., Objective: To investigate resting-state fMRI (rsfMRI)-complexity alterations among children with ADHD, oppositional defiant disorder (ODD), and obsessive-compulsive disorder (OCD), respectively, and comorbid ADHD, ODD, and OCD, within the cool and hot executive function (EF) networks., Design: We leveraged baseline data (wave 0) from the Adolescent Brain and Cognitive Development (ABCD) Study., Setting: The data was collected between September 2016 and September 2019 from 21 sites in the USA., Participants: Children who singularly met all DSM-5 behavioral criteria for ADHD ( N = 61), ODD ( N = 38), and OCD ( N = 48), respectively, were extracted, alongside children with comorbid ADHD, ODD, OCD, and/or other psychiatric diagnoses ( N = 833). A control sample of age-, sex-, and developmentally-matched children was also extracted ( N = 269)., Main Outcomes and Measures: Voxel-wise sample entropy (SampEn) was computed using the LOFT Complexity Toolbox. Mean SampEn within all regions of the EF networks was calculated for each participant and hierarchical models with Generalized Estimating Equations compared SampEn of comorbid-free and comorbid ADHD, ODD, and OCD within the EF networks., Results: SampEn was reduced in comorbid-free ADHD and ODD in overlapping regions of both EF networks, including the bilateral superior frontal gyrus, anterior/posterior cingulate gyrus, and bilateral caudate (Wald statistic = 5.682 to 10.798, p < 0.05 & BH corrected), with ADHD additionally affected in the right inferior/middle frontal gyrus and bilateral frontal orbital cortex (Wald statistic = 7.231 to 9.420, p < 0.05 & BH corrected). Among comorbid presentations, the additional presence of ADHD symptomatology was associated with significantly lower SampEn in every region of interest ( z = -3.973 to -2.235, p < 0.05 & BH corrected)., Conclusions and Relevance: ADHD and ODD shared common impairments underlying the EF networks in the comorbid-free presentations, with ADHD showing more widespread complexity reduction. When ADHD co-occurred with other psychiatric disorders, the reduction in SampEn extended beyond the regions affected in comorbid-free ADHD, indicating that comorbidities amplify neural complexity deficits.

Core-shell structures demonstrate superior capability in customizing properties across multiple scales, offering valuable potential in catalysis, medicine, and performance materials. Integrating functional nanoparticles in a spatially controlled manner is particularly appealing for developing sophisticated architectures that support heterogeneous characteristics and tandem reactions. However, creating such complex structures with site-specific features remains challenging due to the dynamic microenvironment during the shell-forming process, which considerably impacts colloidal particle assembly. Here, we describe a method to spatially deploy nanoscale assemblies within microscale structures comprising a dense shell and a liquid core through colloidal surface decoration coupled with emulsion-based synthesis. Exploiting a spectrum of nanoparticles grafted with incrementally varying densities of organic ligands, we reveal that nanofeatures can be selectively sculpted onto the shell exterior, within the shell wall, and on the interior surface. The versatility of this mechanism is validated by systematically arranging nanoparticles with various compositions, shapes, and dimensions. Spatially integrated nanotitania endows the core-shell structures with localized photocatalytic abilities. Additionally, distinctive surface modifications enable the simultaneous yet independent implantation of diverse nanoparticles, yielding intricate architectures with programmable functions. This generalizable approach showcases a synthetic strategy to attain structural complexity and functional sophistication reminiscent of those of biological systems in nature.

Background: Informational integration and differentiation of the cortex can be tested by methods such as the perturbational complexity index (PCI) combined with TMS-induced activity perturbation. The PCI is obtained by stimulating the cortex with TMS and measuring the resulting spatiotemporal cortical responses with high-density EEG., Methods: We have compared PCI between 26 patients with schizophrenia (15 males), 15 of them First Episode (FE) (7 males), and 22 healthy controls (12 males)., Results: Values of PCI were significantly lower in patients with schizophrenia, as well as in FE considered alone. There was no significant relation between anomalous self-experiences or symptoms and PCI values in the patients: PCI values were unrelated to treatment doses or illness duration., Conclusions: Our data suggest that spatiotemporal cortical responses to TMS pulses are reduced in patients regarding variability or spatial extension, which could imply a lower capacity for sustaining informational complexity., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2025 Elsevier Inc. All rights reserved.)

Irregularity measures tend to describe the complexity of networks. Chemical graph theory is a branch of mathematical chemistry that has a significant impact on the development of the chemical sciences. The study of irregularity indices has recently become one of the most active research areas in chemical graph theory. Irregularity indices help us to examine many chemical and biological properties of chemical structures under study. In this article, we study the irregularity indices of the octahedral and icosahedral networks. These networks are used in crystallography, where the topology and structural aspects are carrying some important facts to determine the properties of large structures theoretically. Our results play an important role in pharmacy, drug design, and many other applied areas. We also compared our results graphically to conclude the irregularity with a change in the parameter of structures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Zhang, ur Rehman and Munir.)

This research addresses complexity in manufacturing systems from an entropic perspective for production improvement. The main objective is to develop and validate a methodology that develops an entropic metric of complexity in an integral way in production environments, through simulation and programming techniques. The methodological proposal is composed of six stages: (i) Case study, (ii) Hypothesis formulation, (iii) Discrete event simulation, (iv) Measurement of entropic complexity by applying Shannon's information theory, (v) Entropy analysis, and (vi) Statistical analysis by ANOVA. The results confirm that factors such as production sequence and product volume significantly influence the structural complexity of the workstations, with station A being less complex (0.4154 to 0.9913 bits) compared to stations B and C, which reached up to 2.2084 bits. This analysis has shown that optimizing production scheduling can reduce bottlenecks and improve system efficiency. Furthermore, the developed methodology, validated in a case study of the metalworking sector, provides a quantitative framework that combines discrete event simulation and robust statistical analysis, offering an effective tool to anticipate and manage complexity in production. In synthesis, this research presents an innovative methodology to measure static and dynamic complexity in manufacturing systems, with practical application to improve efficiency and competitiveness in the industrial sector.

Functional plasticity has been demonstrated in multiple sclerosis (MS) studies. However, the intrinsic brain activity complexity alterations remain unclear. Here, using a coarse-graining time-series procedure algorithm, we obtained multiscale entropy (MSE) from a retrospective multi-centre dataset (208 relapsing-remitting MS patients and 228 healthy controls). By linear mixed model analysis, we demonstrated (1) increased entropy at scale 1 and decreased entropy at scale 6, indicating that regional brain activity shifted towards randomness in the stable MS subgroups (n = 159), and (2) decreased entropy across scales 1-6, trending towards regularity in the acute MS subgroups (n = 49). The main results of the correlation analysis included the following: (1) Decreased entropy was associated with lesion volume and brain volume specifically on longer time scales (scale 3-5), and (2) increased entropy of scale 3 was associated with clinical disability scores. These findings reflect the critical role of structural disruption in the brain activity complexity of BOLD signals in MS patients., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest. Ethics approval: This is a retrospective observational study. This study was approved by the Ethics Committee of the First Affilicated Hospital of Nanchang University’s institute (No. [2021]4–074) and conducted in accordance with the Declaration of Helsinki. Consent to participate: Informed consent was obtained from all individual participants included in the study., (© 2024. Italian Society of Medical Radiology.)

Competing Interests: Competing interests: None declared.

With the ongoing digitization, digital circuits have become increasingly present in everyday life. However, as circuits can be faulty, their verification poses a challenging but essential challenge. In contrast to formal verification techniques, simulation techniques fail to fully guarantee the correctness of a circuit. However, due to the exponential complexity of the verification problem, formal verification can fail due to time or space constraints. To overcome this challenge, recently Polynomial Formal Verification (PFV) has been introduced. Here, it has been shown that several circuits and circuit classes can be formally verified in polynomial time and space. In general, these proofs have to be conducted manually, requiring a lot of time. However, in recent research, a method for automated PFV has been proposed, where a proof engine automatically generates human-readable proofs that show the polynomial size of a Binary Decision Diagram (BDD) for a given function. The engine analyses the BDD and finds a pattern, which is then proven by induction. In this article, we formalize the previously presented BDD patterns and propose algorithms for the pattern detection, establishing new possibilities for the automated proof generation for more complex functions. Furthermore, we show an exemplary proof that can be generated using the presented methods.This article is part of the theme issue 'Emerging technologies for future secure computing platforms'.

Background: Clinical uncertainty is associated with increased resource utilization, worsened health-related quality of life for patients, and provider burnout, particularly during critical illness. Existing data are limited, because determining uncertainty from notes typically requires manual, qualitative review. We sought to develop a consensus list of descriptors of clinical uncertainty and then, using a thematic analysis approach, describe how respondents consider their use in intensive care unit (ICU) notes, such that future work can extract uncertainty data at scale., Design: We conducted a Delphi consensus study with physicians across multiple institutions nationally who care for critically ill patients or patients with advanced illnesses. Participants were given a definition for clinical uncertainty and collaborated through multiple rounds to determine which words represent uncertainty in clinician notes. We also administered surveys that included open-ended questions to participants about clinical uncertainty. Following derivation of a consensus list, we analyzed participant responses using thematic analysis to understand the role of uncertainty in clinical documentation., Results: Nineteen physicians participated in at least 2 of the Delphi rounds. Consensus was achieved for 44 words or phrases over 5 rounds of the Delphi process. Clinicians described comfort with using uncertainty terms and used them in a variety of ways: documenting and processing the diagnostic thinking process, enlisting help, identifying incomplete information, and practicing transparency to reflect uncertainty that was present., Conclusions: Using a consensus process, we created an uncertainty lexicon that can be used for uncertainty data extraction from the medical record. We demonstrate that physicians, particularly in the ICU, are comfortable with uncertainty and document uncertainty terms frequently to convey the complexity and ambiguity that is pervasive in critical illness., Highlights: Question: What words do physicians caring for critically ill patients use to document clinical uncertainty, and why?Findings: A consensus list of 44 words or phrases was identified by a group of experts. Physicians expressed comfort with using these words in the electronic health record.Meaning: Physicians are comfortable with uncertainty words and document them frequently to convey the complexity and ambiguity that is pervasive in critical illness., Competing Interests: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support for this study was provided in part by grants from the NIH (P0546214), UCSF (UCSF Noyce Initiative for Digital Transformation in Computational Biology & Health, the Hellman Fellows Foundation, UCSF Anesthesia Department Seed Grant) and the NIA (P30 AG044281, R01AG057751 and K24AG068312). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.

Psychoneuroimmunology (PNI) is a field of research that deals with the interactions between psyche, nervous, endocrine, and immune systems. Investigating these complex PNI relationships under as ecologically valid as possible conditions ("life as it is lived") necessitates a paradigm change in research. This shift places factors such as "time" and "subjective meaning" of personal experiences at the center of the research methodology. For this purpose, the biosemiotic-systemic research design "Integrative Single-Case Study" was developed. Initial results from healthy individuals as well as patients with systemic lupus erythematosus (SLE), breast cancer, and rheumatoid arthritis (RA) support the validity of the research approach. Specifically, in connection with the occurrence of emotionally meaningful everyday incidents, we repeatedly observed stress system reactions, which were (1) delayed over several days, (2) cyclically patterned, (3) anticipatory, and (4) opposing, depending on a) whether participants experienced emotionally positive or negative everyday incidents, b) whether they were healthy or ill, and c) which stress system parameter was investigated. In this chapter, the Integrative Single-Case Study design is introduced as a holistic research option, presented in detail in its methodology, and critically discussed in terms of its limitations., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The factors contributing to the persistence and stability of life are fundamental for understanding complex living systems. Organisms are commonly challenged by harsh and fluctuating environments that are suboptimal for growth and reproduction, which can lead to extinction. Many species contend with unfavourable and noisy conditions by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. Here, we develop Spore Life, a model to investigate the effects of dormancy on population dynamics. It is based on Conway's Game of Life (GoL), a deterministic cellular automaton where simple rules govern the metabolic state of an individual based on the metabolic state of its neighbours. For individuals that would otherwise die, Spore Life provides a refuge in the form of an inactive state. These dormant individuals (spores) can resuscitate when local conditions improve. The model includes a parameter [Formula: see text] that controls the survival probability of spores, interpolating between GoL ([Formula: see text]) and Spore Life ([Formula: see text]), while capturing stochastic dynamics in the intermediate regime ([Formula: see text]). In addition to identifying the emergence of unique periodic configurations, we find that spore survival increases the average number of active individuals and buffers populations from extinction. Contrary to expectations, stabilization of the population is not the result of a large and long-lived seed bank. Instead, the demographic patterns in Spore Life only require a small number of resuscitation events. Our approach yields novel insight into what is minimally required for the origins of complex behaviours associated with dormancy and the seed banks that they generate.

Plant electrophysiology has unveiled the involvement of electrical signals in the physiology and behavior of plants. Spontaneously generated bioelectric activity can be altered in response to changes in environmental conditions, suggesting that a plant's electrome may possess a distinct signature associated with various stimuli. Analyzing electrical signals, particularly the electrome, in conjunction with Machine Learning (ML) techniques has emerged as a promising approach to classify characteristic electrical signals corresponding to each stimulus. This study aimed to characterize the electrome of common bean ( Phaseolus vulgaris L.) cv. BRS-Expedito, subjected to different water availabilities, seeking patterns linked to these stimuli. For this purpose, bean plants in the vegetative stage were subjected to the following treatments: (I) distilled water; (II) half-strength Hoagland's nutrient solution; (III) -2 MPa PEG solution; and (IV) -2 MPa NaCl solution. Electrical signals were recorded within a Faraday's cage using the MP36 electronic system for data acquisition. Concurrently, plant water status was assessed by monitoring leaf turgor variation. Leaf temperature was additionally measured. Various analyses were conducted on the electrical time series data, including arithmetic average of voltage variation, skewness, kurtosis, Probability Density Function (PDF), autocorrelation, Power Spectral Density (PSD), Approximate Entropy (ApEn), Fast Fourier Transform (FFT), and Multiscale Approximate Entropy (ApEn(s)). Statistical analyses were performed on leaf temperature, voltage variation, skewness, kurtosis, PDF µ exponent, autocorrelation, PSD β exponent, and approximate entropy data. Machine Learning analyses were applied to identify classifiable patterns in the electrical time series. Characterization of the electrome of BRS-Expedito beans revealed stimulus-dependent profiles, even when alterations in water availability stimuli were similar in terms of quality and intensity. Additionally, it was observed that the bean electrome exhibits high levels of complexity, which are altered by different stimuli, with more intense and aversive stimuli leading to drastic reductions in complexity levels. Notably, one of the significant findings was the 100% accuracy of Small Vector Machine in detecting salt stress using electrome data. Furthermore, the study highlighted alterations in the plant electrome under low water potential before observable leaf turgor changes. This work demonstrates the potential use of the electrome as a physiological indicator of the water status in bean plants.

Despite the availability of effective vaccines for preventing common childhood infectious diseases, there is still significant disparities in access and utilization across many low- and middle-income countries (LMIC). The factors that drive these disparities are often multilevel, originating from individuals, health facilities, health systems and communities, and also multifaceted. Implementation science has emerged as a field to help address "know-do" gaps in health systems, and can play a significant role in strengthening immunization systems to understand and solve implementation barriers that limit access and uptake within their contexts. This article presents a reflexive perspective on how to position implementation research in immunization programmes to improve coverage equity. Furthermore, key points of synergy between implementation research and vaccination are highlighted, and some potential practice changes that can be applied within specific contexts were proposed. Using a human rights lens, it was concluded that the cost that is associated with implementation failure in immunization programmes is significant and unjust, and future directions for implementation research to optimize its application in practice settings have been recommended.

Background: Entropy quantifies the level of disorder within a system. Low entropy reflects increased rigidity of homeostatic feedback systems possibly reflecting failure of protective physiological mechanisms like cerebral autoregulation. In traumatic brain injury (TBI), low entropy of heart rate and intracranial pressure (ICP) predict unfavorable outcome. Based on the hypothesis that entropy is a dynamically changing process, we explored the origin and value of entropy time trends., Methods: 232 continuous recordings of arterial blood pressure and ICP of TBI patients with available clinical information and 6-month outcome (Glasgow Outcome Scale) were accessed form the Brain Physics database. Biosignal entropy was estimated as multiscale entropy (MSE) that aggregates entropy at several time scales (20 coarse graining steps starting from 0.1 Hz). MSE was calculated repeatedly for consecutive, overlapping 6 h segments. Percentage monitoring time (ptime) or dosage (duration*level/hour) below different cutoffs were evaluated against outcome using univariable and multivariable analyses, and propensity score matching. Associations to clinical and monitoring metrics were explored using correlation coefficients. Lastly, individual secondary brain insults (deviations in ICP, cerebral perfusion pressure - CPP, or pressure reactivity) were assessed in relation to changes in MSE., Results: Increased MSE abp and MSE cpp ptime (OR 1.28 (1.07-1.58) and OR 1.50 (1.16-2.03) for MSE abp and cpp respectively) and dose (OR 1.12 (1.02-1.27) and OR 1.21 (1.06-1.46) for MSE abp and cpp respectively) were associated with poor outcome even after propensity score matching within multivariable models correcting for ICP, CPP, and the pressure reactivity index. MSE trajectories differed significantly dependent on outcome. The entropy metrics displayed weak correlations to clinical parameters. Individual episodes of deranged physiology were associated with decreases in the MSE metrics from both cerebral and systemic biosignals., Conclusions: Biosignal entropy of changes dynamically after TBI. The assessment of these variations augments individualized, dynamic, outcome prognostication and identification of secondary cerebral insults. Additionally, these explorations allow for further exploitation of the extensive physiological data lakes acquired for each TBI patient within an intensive care environment., Competing Interests: Declarations. Conflicts of interest: Peter Smielewski receives part of the licensing fees for ICM + software, licensed by Cambridge Enterprise Ltd, University of Cambridge, Cambridge. The other authors declare no financial or non-financial conflicts of interest. Ethics approval: The data was accessed through the Brain Physics database that is approved by the local ethics committee (REC 23/YH/0085). Consent to participate: Informed consent was waived by the local ethics committee., (© 2024. The Author(s).)

Here, we suggest a procedure through which one can identify when the accumulation of stresses before major earthquakes (EQs) (of magnitude M 8.2 or larger) occurs. Analyzing the seismicity in natural time, which is a new concept of time, we study the evolution of the fluctuations of the entropy change of seismicity under time reversal for various scales of different length i (number of events). Although the stress might be accumulating throughout the entire process of EQ preparation due to tectonic loading, here we find that the proposed complexity measure reveals different stress accumulation characteristics from those in the long-term background when the system approaches the critical stage. Specifically, we find that anomalous intersections between scales of different i are observed upon approaching a major EQ occurrence. The investigation is presented for the seismicity in Japan since 1984 including the M9 Tohoku EQ on 11 March 2011, which is the largest EQ ever recorded there, as well as for the seismicity before 2017 Chiapas M8.2 EQ, which is Mexico's largest EQ in more than a century. Based on this new complexity measure, a preprint submitted on 5 December 2023 anticipated the 1 January 2024 M7.6 EQ in Japan., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Changes in postural control associated with clinical practice or specific conditions such as the presence of neck pain remain unexplored in dental students. Therefore, this study aimed to explore the time-course changes in postural control complexity among dental students enrolled in clinical practice, comparing those with and without neck pain. We used an online Nordic Musculoskeletal Questionnaire for group allocation and center of pressure (CoP) oscillations with a tri-axial Bertec force plate. Baseline data were acquired from dental students with neck pain (NP) (n = 21) and asymptomatic in a control group (n = 23), before starting their clinical practice, and assessments were repeated after their first semester. CoP fluctuations were determined through the calculation of sample entropy. Both groups had similar postural control at baseline, but asymptomatic students exhibited more irregular CoP AP (p = 0.013) and ML (p = 0.015) oscillations, while students with neck pain showed a more rigid pattern (p = 0.004) in the AP direction at the endpoint. Our results showed that dental students' postural control complexity decreased during the first semester of clinical practice. Over time, asymptomatic students exhibited more random postural control patterns, while students with neck pain demonstrated more rigid postural control during upright stance, indicating that postural control complexity differs between students with and without neck pain when exposed to clinical training., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethical statement: Informed consent was obtained from all participants., (© 2024. The Author(s).)

Viral quasispecies refers to the complex and dynamic mutant distributions (also termed mutant spectra, clouds or swarms) that arise as a result of high error rates during RNA genome replication. The mutant spectrum of individual RNA virus populations is modified by continuous generation of variant genomes, competition and interactions among them, environmental influences, bottleneck events, and bloc transmission of viral particles. Quasispecies dynamics provides a new perspective on how viruses adapt, evolve and cause disease, and sheds light on strategies to combat them. Molecular flexibility, together with ample opportunity of mutant cloud traffic in our global world, are key ingredients of viral disease emergences, as exemplified by the recent COVID-19 pandemic. In the present article we present a brief overview of the molecular basis of mutant swarm formation and dynamics, and how the latter relates to viral disease and epidemic spread. We outline future challenges derived of the highly diverse cellular world in which viruses are necessarily installed., (Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder, characterized by impairments in social interaction and communication with restricted and repetitive behavior. Postural and motor disturbances occur more often in ASD, in comparison to typically developing subjects, affecting the quality of life. Linear and non-linear indexes derived from the trajectory of the center of pressure (COP) while subjects stand on force platforms are commonly used to assess postural stability. The aim of the present feasibility study was to investigate whether combining linear and non-linear parameters of the COP during stance in subjects with ASD, could provide insight on specific features of motor dysfunction possibly linked to ASD cognition and clinical characteristics., Methods: Twenty-two males, aged 10-15 years, including subjects with ASD and healthy controls (N = 11, respectively), were studied. They all had normal cognitive level and independent walking ability. A piezoelectric force platform was used to evaluate posture over three feet positions, with eyes open, closed and during visually-guided saccades. Linear (sway path, total area and root mean square) and non-linear parameters (fractal dimension and sample entropy) of the COP were measured to determine postural stability and the complexity and regularity of the COP signals. GLMM analyses were performed to assess COP parameter changes across experimental conditions and subject groups. Finally, Spearman correlations evaluated the significance of potential relationships between linear and non-linear measures as well as between non-linear parameters and clinical data in patients with ASD., Results: Compared to controls, subjects with ASD showed reduced postural stability and complexity, with higher regularity of COP trajectories, particularly in the most unstable feet positions, during visually-guided saccades and in the medial-lateral direction. Spearman correlations indicated that, in the patients' group, postural instability was associated with a decrease in the geometric complexity and an increase in the regularity of the COP trajectory. Moreover, the increase in regularity of the COP trajectory was associated to the severity of restricted and repetitive behavior., Conclusions: The results of this study highlight the importance of combining linear and non-linear measures in evaluating postural control in patients with ASD, also with respect to the outcome of interventions on these patients targeting postural balance., Competing Interests: Declarations. Ethics approval and consent to participate: The current study was part of an overall larger study aimed at identifying markers, predictors and developmental trajectories of ASD. The larger overall study was approved by the local ethics committee at Policlinico “G. Rodolico-San Marco”, University Hospital of Catania. Written informed consent was obtained from the parents of all participants. Consent for publication: Consent for publication of individual data has been obtained from all the participants of the study. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The Constrained Disorder Principle (CDP) defines all systems in nature by their degree of inherent variability. Per the CDP, the intrinsic variability is mandatory for their proper function and is dynamically changed based on pressures. The CDP defines the boundaries of inherent variability as a mechanism for continuous adaptation to internal and external perturbations, enabling survival and function under dynamic conditions. The laws of nature govern the world's natural phenomena and underlie the function of all systems. Nevertheless, the laws of physics do not entirely explain systems' functionality under pressure, which is essential for determining the correct operation of complex systems in nature. Variability and noise are two broad sources of inherent unpredictability in biology and technology. This paper explores how the CDP defines the function of systems and provides examples from various areas in nature where the CDP applies, including climate, genetic, biology, and human behavioral variabilities. According to the CDP, system malfunction results from inappropriate performance of the boundaries of inherent variability. The environment influences the physiological variability, and species interactions influence eco-evolutionary outcomes. The CDP defines human behavior as being driven by randomness and accounts for malfunctions and their corrections. The paper reviews variability-based CDP algorithms and CDP-based second-generation artificial intelligence systems and their potential for improving systems' prediction and efficiency by using variability., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. YI is the founder of Oberon Sciences., (Copyright © 2024 Ilan.)

Inspired by the way that digital artists zoom out of the canvas to assess the visual impact of their works, we introduce a conceptually simple yet effective metric for quantifying the clarity of digital images. This metric contrasts original images with progressively "melted" counterparts, produced by randomly flipping adjacent pixel pairs. It measures the presence of stable structures, assigning the value zero to completely uniform or random images and finite values for those with discernible patterns. This metric respects the color diversity of the original image and withstands image compression and color quantization. Its suitability for diverse image analysis problems is demonstrated through its effective evaluation of textural images, the identification of structural transitions in physical systems like the Potts model, and its consistency with color theory in digital arts. This allows us to demonstrate that color in visual art functions as a state variable, akin to the spin configuration in magnets, driving artistic designs to transition between states with distinct clarity. When combined with the Shannon entropy, which quantifies color diversity, the structural stability metric can serve as a navigation tool for artists to explore pathways on the complex structural information landscape toward the completion of their artwork. As a practical demonstration, we apply our metric to refine and optimize an emote design for a video game. The structural stability metric emerges as a versatile tool for extracting nuanced structural information from digital images, which may enhance decision-making and data analysis across scientific and creative domains., Competing Interests: Competing interests statement:The authors declare no competing interest.

Competing Interests: Competing interests: None declared.

Objective: To date, the identification of objective biomarkers of neural epileptic activity (EA) remains challenging. We therefore investigated whether neuronal complexity could serve as an interictal electroencephalographic measure of EA, independent of interictal epileptiform discharges (IEDs). By tapering anti-seizure medication (ASM) during video-EEG (electroencephalography) monitoring (VEM), we studied whether changes in neuronal complexity could reliably indicate the increase in EA and identify patients with epilepsy., Methods: The study included 27 patients with unilateral mesial temporal lobe epilepsy (TLE) and 24 control patients with non-epileptic episodes (NEEs) only, each undergoing ASM reduction during VEM. Thirteen additional patients undergoing intracranial recordings during VEM were included to study the relation of surface EEG complexity to intracranial IED. Neuronal complexity was quantified using sample entropy. Delta power served as a control parameter. Receiver-operating characteristic (ROC) analysis was used to evaluate diagnostic performance., Results: As ASM was reduced, patients with epilepsy showed a significant decrease in neuronal complexity over consecutive days (p = .0008). In contrast, patients with NEE showed no significant change in neuronal complexity (p = .78). Delta power in contrast increased and did not differ significantly between patients with TLE and patients with NEE (p = 1). ROC analysis demonstrated that neuronal complexity effectively distinguished between patients with epilepsy and patients with NEE (area under the curve [AUC] = .76), whereas delta power performed at chance level (AUC = .5). Analysis of simultaneously recorded surface and intracranial EEG showed that hippocampal IEDs are followed by an increase in surface EEG delta power (p = 1.8 × 10 -18 ) without any significant change in complexity (p = .39)., Significance: An increase in EA caused by ASM reduction resulted in a loss of neuronal complexity in surface EEG recordings of patients with epilepsy, independent of IEDs. These findings suggest that neuronal complexity could serve as a potential biomarker to differentiate between epilepsy patients and those with NEEs only. This holds promise for improving the clinical evaluation of EA in epilepsy, addressing the limitations of seizure frequency and IED identification., (© 2024 The Author(s). Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

With the use of matter (carbon dioxide, nutrients, and water) and solar energy, phytoplankton produce oxygen and carbohydrates, which are transported to predators through the oceanic food web hierarchy. From the viewpoint of irreversible processes of non-equilibrium thermodynamics, oceanic photosynthesis gives a mechanistic picture of living things characterized by double sets of self-organizations supported by flows of energy and entropy discarded into the ocean environment. This produces biological, ocean circulation, and climate interactions.

While the Banff classification dichotomizes kidney allograft rejection based on the localization of the cells in the different compartments of the cortical kidney tissue [schematically interstitium for T cell mediated rejection (TCMR) and glomerular and peritubular capillaries for antibody-mediated rejection (AMR)], there is a growing evidences that subtyping the immune cells can help refine prognosis prediction and treatment tailoring, based on a better understanding of the pathophysiology of kidney allograft rejection. In the last few years, multiplex IF techniques and automatic counting systems as well as transcriptomics studies (bulk, single-cell and spatial techniques) have provided invaluable clues to further decipher the complex puzzle of rejection. In this review, we aim to better describe the inflammatory infiltrates that occur during the course of kidney transplant rejection (active AMR, chronic active AMR and acute and chronic active TCMR). We also discuss minor components of the inflammatory response (mastocytes, eosinophils, neutrophils, follicular dendritic cells). We conclude by discussing whether the over simplistic dichotomy between AMR and TCMR, currently used in clinical routine, remains relevant given the great diversity of immune actors involved in rejections., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Terinte-Balcan, Lebraud, Zuber, Anglicheau, Ismail and Rabant.)

The thalamus is crucial for supporting various cognitive behaviors due to its extensive connectivity with multiple cortical regions. However, the role of the thalamus and its functional connections with cortical regions in cognitive reasoning remains unclear, since previous research has mainly focused on cortical regions when studying the neural mechanisms underlying cognitive reasoning. To fill this knowledge gap, we utilized 7 T functional magnetic resonance imaging (fMRI) to study the activation patterns of the thalamus and its functional connections with cortical regions during cognitive reasoning task, while also examining how the complexity of reasoning tasks affects thalamic activation and functional connections with cortical regions. Our findings showed that cognitive reasoning processes are related to increased activation of the thalamus and its functional connections with a specific set of cortical regions, consisting of dorsolateral prefrontal cortex, inferior frontal sulcus, intraparietal sulcus, anterior cingulate cortex/presupplementary motor area, precuneus, and ventral medial prefrontal cortex. Moreover, the increase in relational complexity of the reasoning tasks led to a corresponding increase in thalamic activation and functional connectivity with cortical regions. Given the complex thalamus structure, including multiple distinct nuclei exhibiting specific functional connections with particular cortical regions, we used an atlas defined thalamic subdivisions based on its structural connectivity with different cortical regions. Our findings indicated that these different thalamic subregions not only exhibited distinct connectivity patterns with specific cortical regions during performance of cognitive reasoning, but also showed distinct connectivity patterns varied with task complexity. Overall, our study presents evidence of the thalamus's role and its connections with cortical regions in supporting increasingly complex cognitive reasoning behavior, illuminating its contribution to higher-order cognitive functions, such as reasoning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

This study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer's disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a complexity measure particularly sensitive to intra- and inter-subject variations in signal amplitude, as well as the selection of key parameters such as embedding dimension ( m ) and similarity criterion ( r ), which often result in inconsistent outcomes when applied to multivariate data, such as electroencephalography signals. To address these challenges and to generalize the possibility of adopting Multiscale Fuzzy Entropy as a diagnostic tool for Alzheimer's disease, this research explores amplitude transformation preprocessing on electroencephalography signals in Multiscale Fuzzy Entropy calculation across varying parameters. The statistical analysis of the obtained results demonstrates that amplitude transformation preprocessing significantly enhances Multiscale Fuzzy Entropy's ability to detect Alzheimer's disease, achieving higher and more consistent significant comparison percentages, with an average of 73.2% across all parameter combinations, compared with only one raw data combination exceeding 65%. Clustering analysis corroborates these findings, showing that amplitude transformation improves the differentiation between Alzheimer's disease patients and healthy subjects. These results highlight the potential of amplitude transformation to stabilize Multiscale Fuzzy Entropy performance, making it a more reliable tool for early Alzheimer's disease detection.

Innovative eHealth technologies are becoming increasingly common worldwide, with researchers and policy makers advocating their scale-up within and across health care systems. However, examples of successful scale-up remain extremely rare. Although this issue is widely acknowledged, there is still only a limited understanding of why scaling up eHealth technologies is so challenging. This article aims to contribute to a better understanding of the complexities innovators encounter when attempting to scale up eHealth technologies and their strategies for addressing these complexities. We draw on different theoretical perspectives as well as the findings of an interview-based case study of a prominent remote patient monitoring (RPM) innovation in the Netherlands. Specifically, we create a cross-disciplinary theoretical framework bringing together 3 perspectives on scale-up: a structural perspective (focusing on structural barriers and facilitators), an ecological perspective (focusing on local complexities), and a critical perspective (focusing on mutual adaptation between innovation and setting). We then mobilize these perspectives to analyze how various stakeholders (n=14) experienced efforts to scale up RPM technology. We provide 2 key insights: (1) the complexities and strategies associated with local eHealth scale-up are disconnected from those that actors encounter at a broader level scale-up, and this translates into a simultaneous need for stability and malleability, which catches stakeholders in an impasse, and (2) pre-existing circumstances and associated path dependencies shape the complexities of the local context and facilitate or constrain opportunities for the scale-up of eHealth innovation. The 3 theoretical perspectives used in this article, with their diverging assumptions about innovation scale-up, should be viewed as complementary and highlight different aspects of the complexities perceived as playing an important role. Using these perspectives, we conclude that the level at which scale-up is envisaged and the pre-existing local circumstances (2 factors whose importance is often neglected) contribute to an impasse in the scale-up of eHealth innovation at the broader level of scale., (©Sanne Allers, Chiara Carboni, Frank Eijkenaar, Rik Wehrens. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 02.12.2024.)

Recent studies focusing on neural activity captured by neuroimaging modalities have provided various metrics for elucidating the functional networks and dynamics of the entire brain. Functional magnetic resonance imaging (fMRI) can depict spatiotemporal functional neural networks and dynamic characteristics due to its excellent spatial resolution. However, its temporal resolution is limited. Neuroimaging modalities such as electroencephalography (EEG) and magnetoencephalography (MEG), which have higher temporal resolutions, are utilized for multi-temporal scale and multi-frequency-band analyzes. With this advantage, numerous EEG/MEG-bases studies have revealed the frequency-band specific functional networks involving dynamic functional connectivity and multiple temporal-scale time-series patterns of neural activity. In addition to analyzing neural data, the examination of behavioral data can unveil additional aspects of brain activity through unimodal and multimodal data analyzes performed using appropriate integration techniques. Among the behavioral data assessments, pupillometry can provide comprehensive spatial-temporal-specific features of neural activity. In this perspective, we summarize the recent progress in the development of metrics for analyzing neural data obtained from neuroimaging modalities such as fMRI, EEG, and MEG, as well as behavioral data, with a special focus on pupillometry data. First, we review the typical metrics of neural activity, emphasizing functional connectivity, complexity, dynamic functional connectivity, and dynamic state transitions of whole-brain activity. Second, we examine the metrics related to the time-series data of pupillary diameters and discuss the possibility of multimodal metrics that combine neural and pupillometry data. Finally, we discuss future perspectives on these multiple and multimodal metrics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Nobukawa, Shirama, Takahashi and Toda.)

Addressing Diversity, Equity and Inclusion in health care is a multidimensional challenge. From a US perspective, the third-party payment system has disempowered and depersonalized health-care delivery. The net result is wasteful and inefficient use of human and financial resources, burnout among providers, as well as care inequities. Financial integration at the point of patient care is essential to aligning the needs of patients with advances in medical technology. Complexity theory offers valuable insights into the roles of government, intermediaries and patients. The government must focus on equity as a rule compiler and referee of the system. Patient and providers who are actively engaged in shared decision-making will naturally address the diverse needs of multitudinous communities. Intermediaries address inclusion by connecting resources with the point of care. In a dynamic, emerging health-care system that serves diverse communities, patient and community-based financing, vouchers and defined contributions are necessary first steps in addressing cultural diversity, inclusion and equity., (© 2024 John Wiley & Sons Ltd.)

Explorations of barriers and enablers (or barriers and facilitators) to a desired health practice, implementation process, or intervention outcome have become so prevalent that they seem to be a default in much health services and public health research. In this article, we argue that decisions to frame research questions or analyses using barriers and enablers (B&Es) should not be default. Contrary to the strengths of qualitative research, the B&Es approach often bypasses critical reflexivity and can lead to shallow research findings with poor understanding of the phenomena of interest. The B&Es approach is untheorised, relying on assumptions of linear, unidirectional processes, universally desirable outcomes, and binary thinking which are at odds with the rich understanding of context and complexity needed to respond to the challenges faced by health services and public health. We encourage researchers to develop research questions using informed deliberation that considers a range of approaches and their implications for producing meaningful knowledge. Alternatives and enhancements to the B&Es approach are explored, including using 'whole package' methodologies; theories, conceptual frameworks, and sensitising ideas; and participatory methods. We also consider ways of advancing existing research on B&Es rather than doing 'more of the same': researchers can usefully investigate how a barrier or enabler works in depth; develop and test implementation strategies for addressing B&Es; or synthesise the B&Es literature to develop a new model or theory. Illustrative examples from the literature are provided. We invite further discussion on this topic., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Owing to recent advancements in brain science and AI, researchers tend to focus on the concept of self-organized criticality or the edge of chaos. On the other hand, quantum cognition, which is rooted in quantum mechanics, is promising for resolving various cognitive illusions. However, until recently, no connection between criticality and quantum mechanics was proposed. Gunji et al. (2024) recently introduced a linkage termed quantum logic automata, which encompasses not only quantum logic but also criticality characterized by power-law distributions. While quantum logic automata can be derived from various structures, only one of them has been proposed and discussed. Here, we define another type of quantum logic automata involving quantum logic and demonstrate that symmetric quantum logic automata lead to complex Class IV-like patterns and power-law distributions. Our findings support the association between criticality and quantum theory., Competing Interests: Declaration of competing interest The authors have no conflicts of interest directly relevant to the content of this article., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Chaotic sequences are widely used in secure communication due to their high randomness. Chaotic resonance (CR) refers to the resonant response of a system to weak signals induced by chaotic activity, but its practical application remains limited. This study designs a simplified FitzHugh-Nagumo (FHN) auditory neuron model by simulating the physiological activities of auditory neurons and considering the combined stimulation of chaotic activity and sound signals. It is found that the neuron dynamics depend on both external sound stimuli and chaotic current intensity. Chaotic currents induce spikes in the neuron output sequence through CR, and the spikes become more frequent with increasing current intensity, eventually leading to a chaotic state regardless of the initial state. However, the sensitivity of the initial value of this chaotic sequence shifts to the chaotic current excitation system. The injection of chaotic currents can reduce the system's average Hamiltonian energy under certain conditions. By measuring the complexity of the generated sequences, we find that the addition of chaotic currents can enhance the complexity of the original sequences, and the enhancement ability increases with the intensity. This provides a new approach to enhance the complexity of original chaotic sequences. Moreover, different chaotic currents can induce different chaotic sequences with varying abilities to enhance the complexity of the original sequences. We hope our work can contribute to secure communication., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)