State Transition Research Articles

Guidance Strategy and Fast Robustness Analysis for Space Debris Flyby

Envisioning the scenario of space debris inspection by orbital flyby, this paper investigates the guidance strategy and fast robustness analysis method considering the relative state constraints. First, the corrected state transition matrix is derived to predict and correct the perturbed relative state at the flyby moment. Based on the state transition matrix, a free-flight corridor model is established to characterize the maximum allowed magnitude of the deviation, which can quickly estimate the robustness of the trajectory under uncertainties and circumvent intensive numerical sampling. The corresponding optimization, with four norm-extreme constraints, can be solved by a proposed double-layer algorithm with proven convergence. Numerical simulations demonstrate that the guidance algorithm is effective, and the free-flight corridor can accurately and efficiently reflect the robustness of the nominal trajectory.

Observing Array Designed for Improving the Short‐Term Prediction of Kuroshio Extension State Transition Processes

AbstractGiven the essential implications of Kuroshio Extension (KE) bimodality on oceanic dynamical environment and climate, the present study investigates the targeted observation schemes, based on the conditional nonlinear optimal perturbation (CNOP) method and a reduced‐gravity shallow‐water model, to improve the forecast skills of transition processes of KE bimodal states. To obtain a suitable observing array, the observation schemes, with different numbers of observation sites and observation distances between two sites, are designed. Furthermore, to demonstrate the superiority of the observing networks in predicting KE transition processes, two existing observation schemes and six random observation schemes are compared with the CNOP‐determined observing array. Based on this, a relatively optimal observing array with three sites and observation distance of 90 km is established, which is mainly located between 31°N and 33°N in the south of Japan. This targeted observing network is universal for two KE transition processes. The removal of initial errors on this array results in the mean prediction improvements of about 9.2% and 22.5% for KE transition processes from the low‐ to the high‐energy state and from the high‐ to the low‐energy state, respectively.

A note on the computation of multi-revolution NRHO under the ephemeris model

Near Rectilinear Halo Orbits (NRHOs) are vital to manned lunar and deep space exploration, which nowadays are of great interest for different space agencies and in particular with regard to the future space station. However, the required computation of multi-revolution NRHO under the ephemeris model is difficult, especially for the NRHOs with low periapsis relative to the secondary body. This paper explores this issue from the perspective of multiple shooting, first analyzing the influence of the state transition matrices by means of their condition number and then, focusing on a good selection of trajectory segments with suitable patch points. The methodology considerably improves the convergence and the computation under the ephemeris model. Numerical simulations show that at least 30 revolutions can be achieved for NRHOs with perilune radius of less than 12,000 km around L1 or period less than 8.8 days around L2; meanwhile, the number of segments used can be as low as 2 for each single revolution. As for the position of patch points, the first and last points of each revolution should be apart from the Moon, and the distance can be reduced only when the number of segments increases. The proposed method requires no dedicated optimization algorithm or commercial software to produce the multi-revolution NRHOs.

Numerical study on micro-fracture mechanism of rock dynamic failure induced by abrupt unloading under high in-situ stresses

Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of rocks. The macro failure behaviors of rocks are primarily formed after experiencing the initiation, propagation, and coalescence of micro-cracks. In this paper, the grain-based discretized virtual internal bond model is employed to investigate the fracturing process of unloaded rock under high in-situ stresses from the micro-fracture perspective. The simulated micro-fracturing process reveals that the longitudinal stress waves induced by unloading lead to the visible unloading effect. The influences of in-situ stresses, mineral grain sizes, and grain heterogeneity on rock macro and micro fracture are investigated. Micro-crack areas of tensile and shear cracks and micro-crack angles are statistically analyzed to reveal the rock micro-fracture characteristics. The simulated results indicate that the combined effect of the stress state transition and the unloading effect dominates the rock unloading failure. The vertical and horizontal in-situ stresses determine the stress state of surrounding rock after unloading and the unloading effect, respectively. As the vertical stress increases, the stress level after unloading is higher, and the shear failure characteristics become more obvious. As the horizontal stress increases, the unloading effect increases, leading to the intensification of tensile failure. The mineral grain size and grain heterogeneity also have nonnegligible influences on rock unloading failure. The micro-fracture perspective provides further insight into the unloading failure mechanism of deep rock excavation.

Cold Atmospheric Plasma in Cancer Therapy: Molecular Insights, Novel Concepts, and Future Opportunities

Over the past 2 decades, cold atmospheric plasma (CAP) has been playing increasingly pivotal roles in cutting edge biomedical applications and has developed into an innovative field of research of growing importance. One promising new medical application of CAP is cancer treatment. Being able to richly induce both reactive oxygen and nitrogen species, CAP has been shown to effectively control events critical to cancer initiation/progression; selectively inducing Deoxyribonucleic acid (DNA) damage and apoptotic cell deaths, reducing tumor volume and vasculature, halting metastasis and conferring anti-tumor effects by taking advantage of e.g., synergies among and between chemotherapeutic drugs and nanoparticles. This paper discusses molecular and immunological mechanisms of CAP treatment as a potential tool against cancers, with a focus on the novel mechanisms by which CAP interacts with chemotherapeutic drugs and nanotechnology. We then attempt to draw parallels between what is already known about the mechanisms of CAP activity, some novel concepts and attempts of CAP synergy, and the knowledge we would need to develop CAP as a potential therapeutic strategy in oncotherapy. HIGHLIGHTS This article focused on critical review of cold atmospheric plasma’s (CAP) application in cancer therapy. CAP technology in cancer treatment has been expected to cause a medical and therapeutic implications. CAP has strong anticancer efficacy and has been reported about the cell migration and apoptosis. The major role of reactive oxygen and nitrogen species of plasma discharge is to control the core state of cancer transition. GRAPHICAL ABSTRACT

Multiomic analysis of familial adenomatous polyposis reveals molecular pathways associated with early tumorigenesis.

Familial adenomatous polyposis (FAP) is a genetic disease causing hundreds of premalignant polyps in affected persons and is an ideal model to study transitions of early precancer states to colorectal cancer (CRC). We performed deep multiomic profiling of 93 samples, including normal mucosa, benign polyps and dysplastic polyps, from six persons with FAP. Transcriptomic, proteomic, metabolomic and lipidomic analyses revealed a dynamic choreography of thousands of molecular and cellular events that occur during precancerous transitions toward cancer formation. These involve processes such as cell proliferation, immune response, metabolic alterations (including amino acids and lipids), hormones and extracellular matrix proteins. Interestingly, activation of the arachidonic acid pathway was found to occur early in hyperplasia; this pathway is targeted by aspirin and other nonsteroidal anti-inflammatory drugs, a preventative treatment under investigation in persons with FAP. Overall, our results reveal key genomic, cellular and molecular events during the earliest steps in CRC formation and potential mechanisms of pharmaceutical prophylaxis.

Dibenzoquinone Cyclopentadithiophene Diradicaloids Show Optical Transitions of Different Spin States and Anomalous Near‐Infrared Emission

AbstractWe have prepared a series of bis(semiquinone) compounds with dithiophene bridges of different length that evolve from closed‐shell (smaller compound) to full diradical (longer compound) for which the narrow singlet‐triplet energy gap allows the triplet population at 298 K. The medium size system has a variety of photonic properties with absorptions and emission in the optical near‐infrared region mediated by a unique case of anti‐Kasha emission. A whole set of optical absorption/emission and vibrational steady state spectroscopies as well as picosecond transient absorption spectroscopy, all complemented with spectroelectrochemistry and theoretical calculations, is presented.

2.B. Scientific session: Learning from intercountry comparisons in digital healthcare transition monitoring

Abstract In many countries, healthcare is facing several challenges, including increasing healthcare demand, healthcare workforce shortages, rising healthcare costs, and keeping healthcare accessible. It is thought that the use of digital health might help to tackle these challenges. However, digital health programs and interventions are often not (systematically) monitored or evaluated. Monitoring of the digital healthcare transition in countries over time helps policymakers and healthcare professionals to investigate which digital services work well, and which do not, to (partly) solve the experienced challenges. In Europe, several countries monitor the digital healthcare transition within the primary and secondary care in their country. Comparing and sharing the monitoring methodologies between countries and describing the current state of the digital healthcare transition in primary and secondary care, will help to learn from other countries about how digital health could help to tackle the frequently experienced healthcare challenges. During this workshop, three countries throughout Europe (the Netherlands, Italy and Denmark) will briefly share their methodologies used for monitoring the digital healthcare transition in their country and will provide an up-to-date overview of the current state of the digital healthcare transition in primary and secondary care in their country. Challenges, achievements and future plans for the monitoring of this transition will also be shortly discussed in 10-minute presentations. Further, there will be 25 minutes for audience interaction which will be moderated by the chairperson. During this discussion, there is time to hear experiences from other countries and explore best practices in monitoring the digital healthcare transition. Key messages • The digital healthcare transition can be monitored in different ways. Experiences from three European countries may inspire others to organize national monitoring programs. • The speed and nature of the digital healthcare transition differs between European countries. Experiences from three European countries provide insight into state of the art of national transitions.

Advanced model for a non-adiabatic capillary tube considering both subcooled liquid and non-equilibrium two-phase states of R-600a

Previous empirical correlations have largely failed to predict the mass flow rate variations of R-600a during the transient pull-down operation of household refrigerators. This shortcoming is attributed to the fact that these correlations were developed for specific thermodynamic states of the refrigerant at the capillary inlet, whereas the thermodynamic state varies during transient operations, particularly involving non-equilibrium two-phase states. To address these limitations, a novel model has been developed. This model comprises two distinct sub-models corresponding to the refrigerant state at the capillary tube inlet: one for the subcooled liquid state and the other for the non-equilibrium two-phase state. These sub-models are integrated to account for the transitions in the thermodynamic state of R-600a at the capillary inlet. The integrated model demonstrates excellent agreement with observed variations in the R-600a mass flow rate during the pull-down operation of actual refrigerators. The mean absolute percentage error between the measured and estimated mass flow rates is approximately 10 % over the entire period of pull-down operations tested under various environmental conditions.

Uhlmann quench and geometric dynamic quantum phase transition of mixed states

Uhlmann quench and geometric dynamic quantum phase transition of mixed states

Impact of modal gain and waveguide design on two-state lasing in quantum well-dot lasers.

We study the current-controlled lasing switching from the ground state (GS) to the excited state (ES) transition in broad-area (stripe width 100 µm) InGaAs/GaAs quantum well-dot (QWD) and quantum well (QW) lasers. In the lasers with one QWD layer and a 0.45 µm-thick GaAs waveguide, pure GS lasing takes place up to an injection current as high as 8 A (40 kA/cm2). In contrast, in QW lasers with a similar design, ES lasing emerges already at 3 A (15 kA/cm2). The ES lasing in the QWD lasers is observed only in the devices with a waveguide thickness of 0.78 µm that supports a 2nd order transverse mode at the wavelength of the ES transition. Increasing the modal gain in the lasers with 0.78 µm-thick waveguide by using two QWD layers in the active region suppresses the ES lasing.

Research on Complete Coverage Path Planning of Agricultural Robots Based on Markov Chain Improved Genetic Algorithm

Due to the limitations of low coverage, high repetition rate, and slow convergence speed of the basic genetic algorithm (GA) in robot complete coverage path planning, the state transition matrix of the Markov chain is introduced to guide individual mutation based on the genetic mutation path planning algorithm, which can improve the quality of population individuals, enhancing the search ability and convergence speed of the genetic algorithm. The proposed improved genetic algorithm is used for complete coverage path planning simulation analysis in different work areas. The analysis results show that compared to traditional genetic algorithms, the improved genetic algorithm proposed in this paper reduces the average path length by 21.8%, the average number of turns by 6 times, the repetition rate by 83.8%, and the coverage rate by 7.76% in 6 different work areas. The results prove that the proposed improved genetic algorithm is applicable in complete coverage path planning. To verify whether the Markov chain genetic algorithm (MCGA) proposed is suitable for agricultural robot path tracking and operation, it was used to plan the path of an actual land parcel. An automatic navigation robot can track the planned path, which can verify the feasibility of the MCGA proposed.

The pluripotent-to-totipotent state transition in mESCs activates the intrinsic apoptotic pathway through DUX-induced DNA replication stress

The pluripotent mouse embryonic stem cell (mESCs) can transit into the totipotent-like state, and the transcription factor DUX is one of the master regulators of this transition. Intriguingly, this transition in mESCs is accompanied by massive cell death, which significantly impedes the establishment and maintenance of totipotent cells in vitro, yet the underlying mechanisms of this cell death remain largely elusive. In this study, we found that the totipotency transition in mESCs triggered cell death through the upregulation of DUX. Specifically, R-loops are accumulated upon DUX induction, which subsequently lead to DNA replication stress (RS) in mESCs. This RS further activates p53 and PMAIP1, ultimately leading to Caspase-9/7-dependent intrinsic apoptosis. Notably, inhibiting this intrinsic apoptosis not only mitigates cell death but also enhances the efficiency of the totipotency transition in mESCs. Our findings thus elucidate one of the mechanisms underlying cell apoptosis during the totipotency transition in mESCs and provide a strategy for optimizing the establishment and maintenance of totipotent cells in vitro.

The thylakoid phosphatase TEF8 is involved in state transition and high light stress resistance in Chlamydomonas.

The sophisticated regulation of state transition is required to maintain optimal photosynthetic performance under fluctuating light condition, through balancing the absorbed light energy between photosystem II andphotosystem I. This exquisite process incorporates phosphorylation and dephosphorylation of light-harvesting complexes and PSII core subunits, accomplished by thylakoid membrane-localized kinases and phosphatases that have not been fully identified. In this study, one Chlamydomonas high light response gene, THYLAKOID ENRICHED FRACTION 8 (TEF8), was characterized. The Chlamydomonas tef8 mutant showed high light sensitivity and defective state transition. The enzymatic activity assays showed that TEF8 is a bona fide phosphatase localized in thylakoid membranes. Biochemical assays, including BN-PAGE, pull-down, and phosphopeptide mass spectrometry, proved that TEF8 associates with photosystem II and is involved in the dephosphorylation of D2 and CP29 subunits during state 2 to state 1 transition. Taken together, our results identified TEF8 as a thylakoid phosphatase with multiple dephosphorylation targets on photosystem II, and provide new insight into the regulatory mechanism of state transition and high light resistance in Chlamydomonas.

Role of Oxide-Derived Cu on the Initial Elementary Reaction Intermediate During Catalytic CO2 Reduction.

The catalytic role of oxide-derived Cu (OD-Cu) in promoting CO2 reduction (CO2R) to C2+ products has been appreciated for decades. However, the dynamic evolution of the surface oxidation states, together with their real correlation to the binding of reaction intermediates, remains unclear due to technical challenges. Here, we show the time-resolved spectroscopic signatures of key OD-Cu-CO2•- intermediates during catalytic CO2 reduction through one electron transfer from nanoseconds to seconds time scale. We generated the initial intermediate CO2•- radicals in the bulk solution and monitored the interfacial reaction kinetics with well-defined OD-Cu (Cu(0), Cu(I), and Cu(II)) nanoparticles. Combined with molecular simulations, transient absorption profiles analysis reveals that Cu(I) induced a faster CO2•- radical coupling reaction than Cu(0), whereas Cu(II) is only reduced to Cu(I) by the CO2•- radical. Furthermore, the newly developed multistep cumulative pulse methodology uncovered the transition in chemical states of mixed OD-Cu during radical coupling reactions. This pulse radiolysis study provides compelling evidence for the beneficial role of subsurface oxides in early time catalytic CO2 transformation.

Prior exposure to racial discrimination and patterns of acute parasympathetic nervous system responses to a race-related stress task among Black adults.

Black adults' prior exposure to racial discrimination may be associated with their acute parasympathetic reactivity to and recovery from a new race-related stressor. Existing analytical approaches to investigating this link obscure nuances in the timing, magnitude, and patterns of these acute parasympathetic nervous system (PNS) responses. In a re-analysis of a prior study, we utilize an hidden Markov model (HMM) approach to examine how prior experiences of racial discrimination are associated with intraindividual patterns of (1) physiological states of PNS activity and (2) patterns of and variability in transitions between these physiological states. Participants (N = 118) were Black young adults (range 18-29 years; Mage = 19.67, SDage = 2.04) who completed an online survey to index prior racial discrimination exposure, followed by an in-person lab visit during which their PNS activity in response to a race-related stress task was measured via electrocardiogram and converted into respiratory sinus arrhythmia. HMMs indicated evidence for two states: baseline and a second state representing a significant reduction in respiratory sinus arrhythmia. Most participants (93.22%) demonstrated a blunted response to the task, indicating that they did not transition from baseline during the procedure. Prior racial discrimination was not associated with HMM states or state transition parameters. Blunted physiological responses may be an important area of future investigation that could inform early life course mental and physical health screenings.

Harnessing AlphaFold to reveal hERG channel conformational state secrets.

To design safe, selective, and effective new therapies, there must be a deep understanding of the structure and function of the drug target. One of the most difficult problems to solve has been resolution of discrete conformational states of transmembrane ion channel proteins. An example is K v 11.1 (hERG), comprising the primary cardiac repolarizing current, I kr . hERG is a notorious drug anti-target against which all promising drugs are screened to determine potential for arrhythmia. Drug interactions with the hERG inactivated state are linked to elevated arrhythmia risk, and drugs may become trapped during channel closure. However, the structural details of multiple conformational states have remained elusive. Here, we guided AlphaFold2 to predict plausible hERG inactivated and closed conformations, obtaining results consistent with multiple available experimental data. Drug docking simulations demonstrated hERG state-specific drug interactions in good agreement with experimental results, revealing that most drugs bind more effectively in the inactivated state and are trapped in the closed state. Molecular dynamics simulations demonstrated ion conduction for an open but not AlphaFold2 predicted inactivated state that aligned with earlier studies. Finally, we identified key molecular determinants of state transitions by analyzing interaction networks across closed, open, and inactivated states in agreement with earlier mutagenesis studies. Here, we demonstrate a readily generalizable application of AlphaFold2 as an effective and robust method to predict discrete protein conformations, reconcile seemingly disparate data and identify novel linkages from structure to function.

Measuring the dynamic balance of integration and segregation underlying consciousness, anesthesia, and sleep in humans

Consciousness requires a dynamic balance of integration and segregation in brain networks. We report an fMRI-based metric, the integration-segregation difference (ISD), which captures two key network properties: network efficiency (integration) and clustering (segregation). With this metric, we quantify brain state transitions from conscious wakefulness to unresponsiveness induced by the anesthetic propofol. The observed changes in ISD suggest a profound shift towards the segregation of brain networks during anesthesia. A common unimodal-transmodal sequence of disintegration and reintegration occurs in brain networks during, respectively, loss and return of responsiveness. Machine learning models using integration and segregation data accurately identify awake vs. unresponsive states and their transitions. Metastability (dynamic recurrence of non-equilibrium transient states) is more effectively explained by integration, while complexity (diversity of neural activity) is more closely linked with segregation. A parallel analysis of sleep states produces similar findings. Our results demonstrate that the ISD reliably indexes states of consciousness.

Variable Ionized Disk Winds in MAXI J1803−298 Revealed by NICER

We present the results from the NICER observation data of MAXI J1803−298 across the entire 2021 outburst. In the intermediate and soft state, we detect significant absorption lines at ∼7.0 and ∼6.7 keV, arising from X-ray disk winds outflowing with a velocity of hundreds of km s−1 along our line of sight. The fitting results from the photoionized model suggest that the winds are driven by thermal pressure and the mass-loss rate is low. We find a clear transition for iron from predominantly H-like to predominantly He-like during the intermediate-to-soft state transition. Our results indicate this transition for iron is caused by the evolution of the illuminating spectrum and the slow change of the geometric properties of the disk winds together. The coexistence of disk winds and quasiperiodic oscillation features in the intermediate state is also reported. Our study makes MAXI J1803−298 the first source in which a transition from optical winds to X-ray winds is detected, offering new insights into the evolution of disk winds across an entire outburst and long-term coupling of accretion disks and mass outflows around accreting black holes.

Optimal control of discrete event systems under uncertain environment based on supervisory control theory and reinforcement learning

Discrete event systems (DESs) are powerful abstract representations for large human-made physical systems in a wide variety of industries. Safety control issues on DESs have been extensively studied based on the logical specifications of the systems in various literature. However, when facing the DESs under uncertain environment which brings into the implicit specifications, the classical supervisory control approach may not be capable of achieving the performance. So in this research, we propose a new approach for optimal control of DESs under uncertain environment based on supervisory control theory (SCT) and reinforcement learning (RL). Firstly, we use SCT to gather deliberative planning algorithms with the aim to safe control. Then we convert the supervised system to Markov Decision Process simulation environments that is suitable for optimal algorithm training. Furthermore, a SCT-based RL algorithm is designed to maximize performance of the system based on the probabilistic attributes of the state transitions. Finally, a case study on the autonomous navigation task of a delivery robot is provided to corroborate the proposed method by multiple simulation experiments. The result shows the proposed approach owning 8.27%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} performance improvement compared with the non-intelligent methods. This research will contribute to further studying the optimal control of human-made physical systems in a wide variety of industries.