Fundamental Systems Research Articles

Inner Working of the Human Body.

Description This evocative artwork is inspired by the inner workings of the human body, specifically the complexities of blood flow and vascular systems. The deep reds and dynamic patterns represent the movement of blood through arteries and veins, while the interplay of lighter hues evokes the diffusion of oxygen and nutrients. This abstract interpretation aims to capture the vibrancy and essential functions of circulatory processes, celebrating the unseen yet vital life force that sustains us. The piece invites viewers to appreciate the intricate beauty and power of the human body's most fundamental systems.

Vibrio cholerae: a fundamental model system for bacterial genetics and pathogenesis research.

Species of the Vibrio genus occupy diverse aquatic environments ranging from brackish water to warm equatorial seas to salty coastal regions. More than 80 species of Vibrio have been identified, many of them as pathogens of marine organisms, including fish, shellfish, and corals, causing disease and wreaking havoc on aquacultures and coral reefs. Moreover, many Vibrio species associate with and thrive on chitinous organisms abundant in the ocean. Among the many diverse Vibrio species, the most well-known and studied is Vibrio cholerae, discovered in the 19th century to cause cholera in humans when ingested. The V. cholerae field blossomed in the late 20th century, with studies broadly examining V. cholerae evolution as a human pathogen, natural competence, biofilm formation, and virulence mechanisms, including toxin biology and virulence gene regulation. This review discusses some of the historic discoveries of V. cholerae biology and ecology as one of the fundamental model systems of bacterial genetics and pathogenesis.

Efficient data-driven nonlinear system identification for structural health monitoring: A proof-of-principle study

Structural health monitoring (SHM) is the process of detecting damage in structures. Typically, the damage-sensitive feature identification is based on fitting some models to the measured system response data. The parameters of these models or the prediction errors associated with these models then become the desired damage-sensitive features. Real-world structures usually exhibit significant nonlinear behaviors. Data-driven nonlinear system identification (NSI) is essential to obtain accurate models of structural dynamics for reliable damage detection. However, on the one hand, the data acquisition of real-world structures for damage detection is usually difficult or scarce. On the other hand, NSI generally needs to solve a nonlinear optimization problem that requires more computational time for convergence than linear system identification. Data efficiency and computational efficiency become two critical challenges in data-driven NSI. To address these challenges, this work presents a proof-of-principle study on developing a meta learning-based method for efficient data-driven NSI. Specifically, the meta learning algorithm leverages a previously collected database of similar but different systems to learn the meta-knowledge about how to identify a new system, enabling a fast identification/modeling with limited data. Numerical simulations are performed to validate the method on fundamental nonlinear dynamical systems widely seen in civil engineering. It is observed that the presented meta learning-based method outperforms the conventional method in terms of both data and computational efficiency. Limitations of this work are further discussed.

The ecological and evolutionary dynamics of inselbergs.

Islands are fundamental model systems in ecology, biogeography, and evolutionary biology. However, terrestrial islands, unlike their aquatic counterparts, have received comparatively less attention. Among these land islands, inselbergs (i.e. isolated rock outcrops with diverse lithologies and a modest topographical prominence) stand out as iconic examples distributed worldwide across global biomes. Due to their durable lithology, inselbergs change slowly, persisting for tens of millions of years. In this review, we propose a biological definition for inselbergs that captures three fundamental characteristics of inselbergs from the perspective of biota. These are old age, isolation and the presence of unique microhabitats that are rare or absent in the surrounding matrix, fostering distinct communities often with unique and endemic biota. We synthesise the state of the art and formulate a set of testable hypotheses to deepen our understanding of the origins and maintenance of diversity on inselbergs, which are increasingly exposed to anthropogenic threats. By offering different habitats compared to the surrounding habitat matrix (e.g. moist microhabitats in dryland landscapes and xeric environments in humid tropical landscapes), inselbergs may allow specific lineages to thrive beyond their typical geographical limits. Particularly in drylands and degraded landscapes, inselbergs may not just provide different habitats but also act as ecological refuges or evolutionary refugia by providing a wider range of potential microhabitats than the surrounding matrix, enhancing resilience and promoting regional biodiversity. The central role of the matrix ensures that the ecological and evolutionary dynamics of inselbergs differ from those of true islands such as oceanic islands. Given that inselberg biota coexist within a terrestrial matrix, interactions between inselberg and matrix populations impact each other significantly. Over evolutionary timescales, matrix species may contract to inselberg refugia, preserving lineages while cycles of isolation and reconnection may drive speciation via a species pump. Although inselberg biodiversity has been studied predominantly from an island biogeography perspective, we argue that depending on the spatial scale, habitat specificity and mobility of the organisms considered, a range of different theories and paradigms can help explain the biogeography and local distribution patterns of different taxonomic and functional groups of inselberg species.

Synergy of the mirror neuron system and the mentalizing system in a single brain and between brains during joint actions

Cooperative action involves the simulation of actions and their co-representation by two or more people. This requires the involvement of two complex brain systems: the mirror neuron system (MNS) and the mentalizing system (MENT), both of critical importance for successful social interaction. However, their internal organization and the potential synergy of both systems during joint actions (JA) are yet to be determined. The aim of this study was to examine the role and interaction of these two fundamental systems—MENT and MNS—during continuous interaction. To this hand, we conducted a multiple-brain connectivity analysis in the source domain during a motor cooperation task using high-density EEG dual-recordings providing relevant insights into the roles of MNS and MENT at the intra- and interbrain levels.In particular, the intra-brain analysis demonstrated the essential function of both systems during JA, as well as the crucial role played by single brain regions of both neural mechanisms during cooperative activities. Specifically, our intra-brain analysis revealed that both neural mechanisms are essential during Joint Action (JA), showing a solid connection between MNS and MENT and a central role of the single brain regions of both mechanisms during cooperative actions. Additionally, our inter-brain study revealed increased inter-subject connections involving the motor system, MENT and MNS. Thus, our findings show a mutual influence between two interacting agents, based on synchronization of MNS and MENT systems. Our results actually encourage more research into the still-largely unknown realm of inter-brain dynamics and contribute to expand the body of knowledge in social neuroscience.

Developing Methods to Interrogate Nanomaterials in Action for Electrochemical Energy Conversion Reactions

We are observing unprecedented growth in electrified processes at industrial scales for the production of fuels and chemicals. This includes the production of hydrogen, carbon-based molecules (e.g. CO, ethylene), and ammonia, among others. Nevertheless, a number of technical challenges remain in order to meet cost targets for these technologies to scale. Understanding nanomaterials under reaction conditions is essential to designing and developing systems with improved performance and durability, addressing key needs. This paper will describe efforts to understand electrified interfaces at the nanoscale, ranging from fundamental systems to applied systems, and doing so under relevant operating regimes. Methods include X-ray techniques to observe the chemical dynamics of catalysts, vibrational spectroscopy and neutron reflectometry to monitor electrified interfaces at the nanoscale, microscopy to observe mass transport and crystallization within porous media, and inductively coupled plasma mass spectrometry to quantitatively measure corrosion phenomena. The development and implementation of these in-situ/operando techniques are providing the insights needed to advance these emerging technologies towards more widespread commercialization.

A Deep Learning–Derived Transdiagnostic Signature Indexing Hypoarousal and Impulse Control: Implications for Treatment Prediction in Psychiatric Disorders

BackgroundPsychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. The Research Domain Criteria (RDoC) constitute a research classification system for psychiatric disorders based on dimensions within domains that cut across these psychiatric diagnoses. The overall aim of RDoC is to better understand mental illness in terms of dysfunction in fundamental neurobiological and behavioral systems, leading to better diagnosis, prevention, and treatment. MethodsA unique electroencephalographic feature, referred to as spindling excessive beta, has been studied in relation to impulse control and sleep as part of the arousal/regulatory system RDoC domain. Here, we studied electroencephalographic frontal beta activity as a potential transdiagnostic biomarker capable of diagnosing and predicting impulse control and sleep problems. ResultsWe showed in the first dataset (n = 3279) that the probability of having spindling excessive beta, classified by a deep learning algorithm, was associated with poor sleep maintenance and low daytime impulse control. Furthermore, in 2 additional, independent datasets (iSPOT-A [International Study to Predict Optimized Treatment in ADHD], n = 336; iSPOT-D [International Study to Predict Optimized Treatment in Depression], n = 1008), we revealed that conventional frontocentral beta power and/or spindling excessive beta probability, referred to as Brainmarker-III, is associated with a diagnosis of attention-deficit/hyperactivity disorder, with remission to methylphenidate in children with attention-deficit/hyperactivity disorder in a sex-specific manner, and with remission to antidepressant medication in adults with major depressive disorder in a drug-specific manner. ConclusionOur results demonstrate the value of the RDoC approach in psychiatry research for the discovery of biomarkers with diagnostic and treatment prediction capacities.

Graceful bases in solution spaces of differential and difference equations

We construct fundamental systems of solutions to linear ordinary differential equations, linear difference equations, and systems of partial differential equations whose elements remain linearly independent for all values of algebraically independent symbolic parameters.

Metabolic and Immune Systems Are the Primary Tenets of Biological Life

A theory is much broader than a hypothesis or a conjecture if it can provide explanations for a wide range of observations while remaining robust to challenges through experimentation. There is a paucity of such theories in biology. The main motivation behind this research was to propose a broad theory of biological life and to explore whether it can be used as a framework for understanding health and disease conditions. A conceptual and theoretical approach was followed for this purpose. Extensive exploration and analysis of the biomedical literature in a non-systematic but purposeful manner were undertaken. They were then extrapolated using a top-down approach to identify the fundamental systems mediating life processes. Two attributes must exist for the survival of any biological life form, including the ability to grow and the ability to self-protect. These two functions are performed by the metabolic system and immune system, respectively. It is proposed that all other processes and every entity in a life form are involved in conducting these two fundamental functions. It is inferred that both of these functions exhibit the universal characteristics of duality and complementarity, features that cut across disciplines. A given life form may thus be biased toward one of the two processes mediated by the immune system and metabolic system at different stages in its life history. Identifying factors that confer bias might provide a better understanding of biology with direct implications for medicine. It is proposed that life and disease could be the result of the interplay of immune and metabolic systems acting complementarily. Other physiological systems lend support to the balancing act between the immune and metabolic systems in a biological life form.

Cell-Free Protein Expression by a Reconstituted Transcription-Translation System Energized by Sugar Catabolism.

Cooperation between catabolism and anabolism is crucial for maintaining homeostasis in living cells. The most fundamental systems for catabolism and anabolism are the glycolysis of sugars and the transcription-translation (TX-TL) of DNA, respectively. Despite their importance in living cells, the in vitro reconstitution of their cooperation through purified factors has not been achieved, which hinders the elucidation of the design principle in living cells. Here, we reconstituted glycolysis using sugars and integrated it with the PURE system, a commercial in vitro TX-TL kit composed of purified factors. By optimizing key parameters, such as glucokinase and initial phosphate concentrations, we determined suitable conditions for their cooperation. The optimized system showed protein synthesis at up to 33% of that of the original PURE system. We observed that ATP consumption in upstream glycolysis inhibits TX-TL and that this inhibition can be alleviated by the co-addition of glycolytic intermediates, such as glyceraldehyde 3-phosphate, with glucose. Moreover, the system developed here simultaneously synthesizes a subset of its own enzymes, that is, glycolytic enzymes, in a single test tube, which is a necessary step toward self-replication. As glycolysis and TX-TL provide building blocks for constructing cells, the integrated system can be a fundamental material for reconstituting living cells from purified factors.

Oxytocin and women's health in midlife.

Menopause marks the cessation of fertility and the transition to post-reproductive years. Nearly 1 million US women experience menopause annually, but despite the significant impact it has on their physical and mental health, menopause has been insufficiently studied. Oxytocin is a neurohormone that regulates emotionality, social behaviors, and fundamental physiological systems. Localization of oxytocin receptors in the brain, reproductive tissues, bone, and heart support their role in mental health and potentially sleep, along with reproductive and cardiovascular functions. While experimental data linking oxytocin to behavior and physiology in animals are largely consistent, human data are correlative and inconclusive. As women transition into menopause, oxytocin levels decrease while their susceptibility to mood disorders, poor sleep, osteoporosis, and cardiovascular diseases increases. These concurrent changes highlight oxytocin as a potential influence on the health and mood of women along their reproductive life span. Here, we summarize experimental rodent and non-human primate studies that link oxytocin to reproductive aging and metabolic health and highlight the inconclusive findings in studies of women. Most human studies relied on a single oxytocin assessment in plasma or on intranasal oxytocin administration. The pulsatile release and short half-life of plasma oxytocin limit the validity of these methods. We discuss the need for oxytocin assessments in stable bio-samples, such as urine, and to use valid assays for assessment of associations between changing oxytocin levels and well-being across the reproductive life span. This work has the potential to guide therapeutic strategies that will one day alleviate adverse health outcomes for many women.

Active Fault-Tolerant and Attack-Resilient Control for a Renewable Microgrid Against Power-Loss Faults and Data Integrity Attacks.

The next-generation power grid evolves from the development of fundamental cyber-physical energy systems called smart microgrids. In order to improve the reliability, safety, and security of smart microgrids and achieve a more cost-effective operation, innovative approaches for physical fault diagnosis and fault-tolerant control (FTC) as well as intrusion detection and attack-resilient control (ARC) should be investigated. Given that, this article considers a smart hybrid renewable-based microgrid with different types of distributed generation units, including solar photovoltaic (PV) array, wind turbines, and battery energy storage system. Novel active FTC and ARC strategies are designed for pulse-width modulation (PWM) converters at microgrid level. The proposed fault-tolerant controller is based on an optimal fuzzy gain-scheduling technique that is used to accommodate the adverse impacts of PV power-loss faults. Also, the proposed attack-resilient controller relies on the estimated values of sensor measurements during the occurrence of data integrity cyber-attacks. To access and evaluate the microgrid's real-time health status, both FTC and ARC strategies employ an integrated model-based intrusion detection and fault diagnosis (IDFD) system that is designed using a fuzzy modeling and identification technique. Finally, the effectiveness of the proposed solutions is demonstrated via a series of simulations in MATLAB/Simulink using an advanced microgrid benchmark.

High-rate multiplexed entanglement source based on time-bin qubits for advanced quantum networks

Entanglement distribution based on time-bin qubits is an attractive option for emerging quantum networks. We demonstrate a 4.09-GHz repetition rate source of photon pairs entangled across early and late time bins separated by 80 ps. Simultaneous high rates and high visibilities are achieved through frequency multiplexing the spontaneous parametric down conversion output into eight time-bin entangled channel pairs. We demonstrate entanglement visibilities as high as 99.4%, total entanglement rates up to 3.55×106 coincidences/s, and predict a straightforward path towards achieving up to an order of magnitude improvement in rates without compromising visibility. Finally, we resolve the density matrices of the entangled states for each multiplexed channel and express distillable entanglement rates in ebit/s, thereby quantifying the trade-off between visibility and coincidence rates that contributes to useful entanglement distribution. This source is a fundamental building block for high-rate entanglement-based quantum key distribution systems or advanced quantum networks.

Mechanical Self-Organization of Particle Networks during Uniaxial Compression Yielding

Colloidal gels, sparse particle networks with large voids, are fundamental model systems of disordered porous materials. Unlike dense amorphous solids, they exhibit significant volumetric deformation while expelling solvents when subjected to external compression. Despite their importance in both natural and industrial settings, the relationship between their network microstructure and compressive yielding behavior has remained elusive. To address this problem, we employ confocal microscopy and a specially designed sample cell to observe the gravity-induced collapsing of colloidal gels at a single-particle level. The experimental insight gained is complemented by simulation results for gravitational collapse and homogeneous uniaxial compression. We find that, during compression, the microstructure of gels is uniquely determined solely by the local volume fraction. This relationship remains independent of the deformation strain history but is subtly influenced by the preparation history of the initial state. In contrast, compressive stress evolves as a unique function of local volume fraction, unaffected by both preparation and strain history, as long as the interparticle interaction remains identical. Moreover, we unveil that local yielding occurs in highly strained, narrow network domains, while highly stressed particles form chainlike structures to support the external stress. These findings suggest that colloidal gels undergoing compressive plastic deformation mechanically self-organize into a unique history-independent state to satisfy mechanical balance in a quasistatic condition, providing crucial microscopic insights into the compressive yielding behavior of particle network materials. Published by the American Physical Society 2024

Modification of rotor modal properties based on structural changes in the stiffness of its bearings and shaft

The rotor structures are fundamental mechanical systems that realize the transfer of rotary motion in technical devices and systems. In some operating regimes, the rotor systems are often subjected to undesirable and damaging phenomena resulting in resonant state. The ability to prevent or reduce the level of unwanted rotor vibrations in the given operating mode is an important task in the process of structural design of rotor structures. In general, the dynamic properties of rotor systems depend on their spatial properties - geometric parameters and material properties, i.e. distribution of mass and stiffness properties of rotor structures. For the structural design of the rotor or its structural modification, which will allow the redistribution of its spatial properties (mass and stiffness), two approaches based on changing the bearing stiffness and also on the shaft stiffness are presented in this paper. The main goal for modifying the spatial properties of the rotor is to get the critical rotor speed out of the operating speed range.

Investigation of shear band strengthening by using different strengthening criteria

To prevent a critical failure mechanism, it is possible to simply strengthen the potential shear bands, which is a patented idea. The localization of potential shear bands that are most likely to form shear can be calculated. Before these shear bands can appear, they can be strengthened by injecting a cement suspension or using jet grouting at the locations where the most likely shear bands would occur. As a result, it is possible to increase the bearing capacity of the geotechnical system by focusing solely on the shear bands that are moste likely to form, minimizing the use of materials. Numerical modeling is employed to analyze the increase in bearing capacity. Four criteria for strengthening the shear bands are applied by incorporating them into a hypoplastic soil model, taking into consideration the material transition from soil to cement, as well as intermediate materials that can arise from jet grouting, which are mixtures of soil and cement. Two fundamental geotechnical systems, namely a shallow foundation and a retaining wall, are analyzed using ABAQUS/Standard for finite element analysis. The results demonstrate the potential of numerical modeling to identify the most critical localized areas in the soil that require strengthening, as well as the substantial increase in bearing capacity achieved after reinforcing the identified areas.

Development and evaluation of low-cost flat plate photobioreactors for microalgae and cyanobacteria cultivation with biotechnological potential.

The high performance of biomass and metabolite biosynthesis by photosynthetic microorganisms is directly influenced by the cultivation system employed. Photobioreactors (PBRs) stand out as controlled and fundamental systems for increasing the production of biocompounds. However, the high costs associated with these systems hinder their viability. Thus, a more practical and economical approach is necessary. Accordingly, this study aimed to design and evaluate low-cost flat-panel photobioreactors on a laboratory scale for the cultivation of photosynthetic microorganisms, using economical materials and instruments. Additionally, internal optimization of the low-cost system was aimed to maximize growth and biomass production. The PBRs were designed and built with uniform dimensions, employing 4 mm translucent glass and agitation through compressors. The internally optimized system (PBR-OII) was equipped with perforated acrylic plates used as static mixers. To evaluate the performance of the low-cost PBR-OII, a comparison was made with the control photobioreactor (PBR-CI), of the same geometry but without internal optimization, using a culture of Synechocystis sp. CACIAM 05 culture. The results showed that the PBR-OII achieved maximum biomass yield and productivity of 6.82 mg/mL and 250 mg/L/day, respectively, values superior to the PBR-CI (1.87 mg/mL and 62 mg/L/day). Additionally, the chlorophyll concentration in the PBR-OII system was 28.89 ± 3.44 µg/mL, while in the control system, the maximum reached was 23.12 ± 1.85 µg/mL. Therefore, low-cost photobioreactors have demonstrated to be an essential tool for significantly increasing biomass production, supporting research, and reducing costs associated with the process, enabling their implementation on a laboratory scale.

Bridges and Mechanisms: Integrating Systems Science Thinking into Implementation Research.

We present a detailed argument for how to integrate, or bridge, systems science thinking and methods with implementation science. We start by showing how fundamental systems science principles of structure, dynamics, information, and utility are relevant for implementation science. Then we examine the need for implementation science to develop and apply richer theories of complex systems. This can be accomplished by emphasizing a causal mechanisms approach. Identifying causal mechanisms focuses on the "cogs and gears" of public health, clinical, and organizational interventions. A mechanisms approach focuses on how a specific strategy will produce the implementation outcome. We show how connecting systems science to implementation science opens new opportunities for examining and addressing social determinants of health and conducting equitable and ethical implementation research. Finally, we present case studies illustrating successful applications of systems science within implementation science in community health policy, tobacco control, health care access, and breast cancer screening.

Dynamic simulation for process hazard analysis: Affordances and limitations in the application to complex process systems

Improving process safety is a high priority in process and manufacturing industries to address unwanted accidents and process disruptions. Research into the applications of dynamic simulators for hazard analysis has been rapidly growing. However, there is scant discussion in literature regarding the benefits and limitations associated with the utilization of dynamic simulations for process hazard analysis. A fundamental systems conceptualization, underpinned by the P3 model of people, plant and procedures, provides a framework for the characteristics to be considered by subject matter expertise when identifying the affordances and limitations within a dynamic simulation used for process hazard analysis. This subject matter expertise includes people with operations, process engineering, process safety and process simulation experience. All dynamic simulations will have limitations and understanding the affordances and limitations is crucial for the correct use of a model and the interpretation of results. A case study is presented on the application of a systematic approach for interrogating the dynamic simulation from an industrial operator training simulator of an operating residue catalytic cracking complex with the aim of conducting failure mode and effects analysis by identifying the significant consequences and the associated independent protection layers. Issues with respect to how one could automate the analysis rather than use human observation to assess the outcomes are considered and how to present the outcomes to complement existing process hazard analysis techniques are discussed. Future research requirements and developments that may assist in practically and effectively applying the technique in industry are also discussed.

The Independent Medicines and Medical Devices Safety Review: Regulatory Reform and Remedies

For years, groups of patients and their families in the United Kingdom raised their concerns about three medical interventions. The first was a possible link between hormone pregnancy tests and fetal malformations and deaths; the second was the physical and neurodevelopmental impacts of in utero valproate exposure; and the third was life-changing adverse events caused by pelvic mesh implants for pelvic organ prolapse repair and stress urinary incontinence management. In response to their tireless campaigning, the Independent Medicines and Medical Devices Safety (IMMDS) Review was commissioned by the Secretary of State for Health and Social Care in 2018. The review, chaired by Baroness Cumberlege, found a catalogue of institutional, systems and structural failures within both the medical establishment and healthcare system more broadly. Drawing on the IMMDS Review findings on pelvic mesh, in this article, I consider the dire consequences when medical devices go wrong. Drawing on firsthand experience as lead researcher for the IMMDS Review, I examine some of the background, outline some key findings and reflect on the strategic changes recommended to medical device regulation and the redress prompted by the pelvic mesh scandal. In so doing, I contextualise and consider the relevant regulatory frameworks, the fundamental systems failures and the other issues identified. Three years on, this article also provides an opportunity to assess the extent to which the IMMDS Review recommendations have been successfully operationalised, as well as to take stock of the improvements that still need to be made.