Static Output Research Articles

Comprehensive non-invasive haemodynamic assessment in acute decompensated heart failure-related cardiogenic shock: a step towards echodynamics.

Haemodynamic assessment can be determinant in phenotyping cardiogenic shock (CS) and guiding patient management. Aim of this study was to evaluate the correlation between echocardiographic and invasive assessment of haemodynamics in acute decompensated heart failure-related CS (ADHF-CS). All consecutive ADHF-CS patients (SCAI shock stage ≥B) undergoing right heart catheterization (RHC) between 2020 and 2022 were prospectively enrolled. Patients underwent echocardiography 30 min before RHC. The evaluated haemodynamic parameters and their echocardiographic estimates ('e') comprised cardiac index (CI), wedge pressure (WP), pulmonary artery pressures (PAP), cardiac power output (CPO) and pulmonary artery pulsatility index (PAPi). Hundred and one ADHF-CS patients (56 ± 11 years, 64% SCAI shock stage C, left ventricular ejection fraction 29 ± 5%) were included. Good correlation was found for CI, systolic PAP, RAP, and CPO (Pearson r > 0.8 for all), moderate correlation for ePAPi (r = 0.67) and PVR (r = 0.51), while estimation of WP was weak. The sensitivity and specificity of eCI to identify low output state (CI ≤2.2 L/min/m2) were 0.97 and 0.73, respectively, those of eWP for elevated filling pressures (WP >15 mmHg) were 0.84 and 0.55, those of ePAPs for PAPs ≥35 mmHg were 0.87 and 0.63, those of eCPO for CPO <0.6 W were 0.76 and 0.85, those of ePAPi for PAPi <1.85 were 0.89 and 0.92. Echocardiographic phenotyping of CS showed a good agreement with invasive classification (K value 0.457, P < 0.001). Echocardiographic estimation of haemodynamics and subsequent phenotypization of CS is feasible with good agreement with invasive evaluation.

Provincial marine carbon sink transfer in China: structural drivers and key consumption pathways

The ocean is the largest carbon sink on Earth and an important pathway to China achieving carbon neutrality. From a consumption perspective, studying the capacity of marine carbon sink in each of China’s provinces and its inter-regional transfer is of great significance in harnessing the increase in ocean carbon sink driven by final demand. This article first calculates the production-side carbon sink in coastal provinces. Then, based on the 2007, 2012, 2015, and 2017 Chinese inter-regional input-output tables, each province’s consumption-side marine carbon sink is calculated. The article further examines the influencing factors and key transfer paths for the growth of marine carbon sink through Structural Decomposition Analysis (SDA) and Structural Path Analysis (SPA) methods. The results show that each province’s total consumption-side carbon sink continues to rise, with significant regional disparities, demonstrating a trend of higher carbon sink in coastal provinces than inland provinces. Among the nine coastal provinces, Hainan and Guangdong are in a net input state regarding carbon sink transfer, while the other seven are in a net output state. SDA results indicate that the carbon sink intensity effect and the consumption demand effect are important factors inhibiting and promoting carbon sink growth, respectively, while the influence of the input-output technical effect is weak and variable. SPA analysis reveals that carbon sink outputs are primarily transferred to the food and tobacco sector, the agricultural and forestry products and services sector, and the wood processing and furniture industry. The key transfer paths mostly occur within a province, with a relatively small proportion of interprovincial transfer paths. Based on the research findings, this article suggests steadily increasing the proportion of marine product consumption, actively expanding the value chain of shellfish and seaweed industries, continuously strengthening coordination between land and marine industries, and further promoting the domestic circulation of marine carbon sinks.

Quantum soft-covering lemma with applications to rate-distortion coding, resolvability and identification via quantum channels

We propose a quantum soft-covering problem for a given general quantum channel and one of its output states, which consists in finding the minimum rank of an input state needed to approximate the given channel output. We then prove a one-shot quantum covering lemma in terms of smooth min-entropies by leveraging decoupling techniques from quantum Shannon theory. This covering result is shown to be equivalent to a coding theorem for rate distortion under a posterior (reverse) channel distortion criterion by two of the present authors. Both one-shot results directly yield corollaries about the i.i.d. asymptotics, in terms of the coherent information of the channel. The power of our quantum covering lemma is demonstrated by two additional applications: first, we formulate a quantum channel resolvability problem, and provide one-shot as well as asymptotic upper and lower bounds. Second, we provide new upper bounds on the unrestricted and simultaneous identification capacities of quantum channels, in particular separating for the first time the simultaneous identification capacity from the unrestricted one, proving a long-standing conjecture of the last author.

Bound‐based control design for permanent magnet linear motor servo system with inequality constraints and uncertainties

AbstractThe permanent magnet linear motor (PMLM) systems are widely applied in various engineering fields. However, the state inequality constraints and uncertainties of parameters and unknown external disturbances need to be further explored. In this article, first, a state transformation method is proposed for converting bounded states to unbounded states. As a result, the output state of system is limited within the expected boundary constraint. Then, a new control strategy is constructed. This strategy can ensure that the controlled system with uncertainties is uniformly bounded and uniformly ultimately bounded. Finally, the effectiveness of the controller and the state transformation method are verified through simulation of PMLM system. The inequality constraints of the output state are satisfied, and the system performance is improved.

Thermodynamically optimal protocols for dual-purpose qubit operations

Information processing, quantum or classical, relies on channels transforming multiple input states to different corresponding outputs. Previous research has established bounds on the thermodynamic resources required for such operations, but no protocols have been specified for their optimal implementation. For the insightful case of qubits, we here develop explicit protocols to transform two states in an energetically optimal manner. We first prove conditions on the feasibility of carrying out such transformations at all, and then quantify the achievable work extraction. Our results uncover a fundamental incompatibility between the thermodynamic ideal of slow, quasistatic processes and the information-theoretic requirement to preserve distinguishability between different possible output states. Published by the American Physical Society 2024

Non-probabilistic reliability analysis with both multi-super-ellipsoidal input and fuzzy state

In real-world engineering scenarios, incomplete uncertainty information and ambiguous failure states persist and pose significant challenges for structural reliability analysis. This paper introduces a non-probabilistic fuzzy reliability analysis (NPFRA) model featuring fuzzy output states, where the input uncertainties are quantified by a multi-super-ellipsoidal model. Initially, we define both reliability and failure indices of NPFRA, and provide the corresponding Monte Carlo simulation (MCS) solution. Additionally, an extended variable space (EVS) method is established to transform the NPFRA problem into a conventional non-probabilistic reliability analysis (NPRA) one, and MCS based on EVS is derived accordingly. To address the efficiency issue of MCS, a novel method called active learning kriging with norm-constrained expected risk function (ALK-NERF) is developed explicitly for NPFRA. Four examples are adopted to verify the rationality and effectiveness of the proposed ALK-NERF for NPFRA.

Competition of decoherence and quantum speed limits for quantum-gate fidelity in the Jaynes-Cummings model

Quantum computers are operated by external driving fields, such as lasers, microwaves, or transmission lines, that execute logical operations on multiqubit registers, leaving the system in a pure state. However, the drive and the logical system might become correlated in such a way that, after tracing out the degrees of freedom of the driving field, the output state will not be pure. Previous works have pointed out that the resulting error scales inversely with the energy of the drive, thus imposing a limit on the energy efficiency of quantum computing. In this study, focusing on the Jaynes-Cummings model, we show how the same scaling can be seen as a consequence of two competing phenomena: the entanglement-induced error, which grows with time, and a minimal time for computation imposed by quantum speed limits. This evidence is made possible by quantifying, at any time, the computation error via the spectral radius associated with the density operator of the logical qubit. Moreover, we also prove that, in order to attain a given target state at a chosen fidelity, it is energetically more efficient to perform a single driven evolution of the logical qubits rather than to split the computation in subroutines, each operated by a dedicated pulse. Published by the American Physical Society 2024

Beta-blockade for the treatment of refractory hypoxaemia during venovenous extracorporeal membrane oxygenation: An in-silico study.

Venovenous extracorporeal membrane oxygenation (VV ECMO) is used for refractory hypoxemia, although despite this, in high cardiac output states, hypoxaemia may persist. The administration of beta-blockers has been suggested as an approach in this scenario, however the physiological consequences of this intervention are not clear. We performed an in-silico study using a previously described mathematical model to evaluate the effect of beta-blockade on mixed venous and arterial saturations (, SaO2), in three different clinical scenarios and considered the potential effects of beta-blockers on, cardiac output, oxygen consumption and recirculation. Additionally we assessed the interaction of beta-blockade with haemoglobin concentration. In scenario 1: simulating a patient with high cardiac output and partial lung shunt decreased from increased 53.5% to 44.7% despite SaO2 rising from 74.2% to 79.2%. In scenario 2 simulating a patient with high cardiac output and complete lung shunt remained unchanged at 52.2% and SaO2 rose from 71.9% to 85%. In scenario 3 a patient with normal cardiac output and high recirculation fell from 50.8% to 25.5% and also fell from 82.4% to to 78.3%. Across the remaining modelling examples the effect on varied but oxygen delivery was consistently reduced across all scenarios. The administration of beta-blockers for refractory hypoxemia during VV ECMO are unpredictable and may reduce oxygen delivery, although this will vary with patient and circuit features. This study does not support the use of beta-blockers for this indication.

Some Results on the Properties of Discrete-Time LTI State-Space Systems

Abstract This work brings forward several interesting facts about system properties of linear time-invariant discrete-time systems like output controllability, state controllability and state observability, trackability, and input and state observability. Particularly, the work brings about the inter-relationships between these properties while taking a state-space formulation-based approach to come up with simple facts that are backed up by proofs using preliminary linear algebra.

Generation of Bright–Dark Pulse Pairs in the Er-Doped Mode-Locked Fiber Laser Based on Doped Fiber Saturable Absorber

This study reports new types of passive mode-locked Er-doped fiber laser (EDFL) based on a segment of doped fiber saturable absorber (DFSA) with Tm/Ho-doped fiber (THDF), Yb-doped fiber (YDF), and Er-doped fiber (EDF). By employing THDF-SA, a bright pulse sequence with a fundamental repetition rate of 17.86 MHz was obtained. In addition, various mode-locked output states, including dark pulses, dark–bright pulse pairs, bright–dark pulse pairs, and second-harmonic pulses, were obtained through polarization modulation and gain modulation, and the orthogonality of dark–bright pulses in both polarization directions was verified. Furthermore, using EDF-SA and YDF-SA, dark pulses and dark–bright pulses were obtained. A comparison of the three experiments revealed that THDF-SA effectively reduces the mode-locked threshold and improves the average output power. Compared with bright pulses, dark pulses offer several advantages such as resisting noise, increasing propagation speed, and suppressing nonlinear scattering (such as pulse-intrinsic Raman scattering); thus, the EDFL can find broad application in long-distance transmission, precision measurement, and other fields.

Modeling NP-problems with families of extended graph-based reaction systems

In this paper, we continue the investigation of graph-based reaction systems. We extend the notion by input and output states as well as admitted context sequences to model explicitly input–output relations and decision problems on the inputs. Moreover, we combine extended graph-based reaction systems into families to cover infinite input–output relations and decision problems on infinite sets of graphs. This is used to model NP-problems on graphs and reductions between them as well as to prove their correctness.

Reliability Evaluation of Distribution Networks Considering Natural Gas Network Integration

Abstract With the transformation of energy structure, the distribution network in the form of multi-energy interconnection is gradually emphasized. The access of gas turbines to the distribution network puts high requirements on the reliability assessment of the distribution network counting and natural gas network access. Models of distribution network components and natural gas network equipment are established. Based on the traditional sequential MC reliability assessment, the calculation of reliability indexes for the distribution network with gas turbine access is accomplished by identifying the islanded areas under fault conditions and judging the gas turbine output state, taking into account the energy flow constraints. The results of the calculations show that the reliability of the distribution network with natural gas network access is improved, and the reliability of the load nodes near the gas turbine is improved significantly.

Dynamical encircling of multiple exceptional points in anti-PT symmetry system

Exceptional points (EPs) in non-Hermitian systems have turned out to be at the origin of many intriguing effects with no counterparts in Hermitian cases. A typically interesting behavior is the chiral mode switching by dynamically winding the EP. Most encircling protocols focus on the two-state or parity-time (PT) symmetry systems. Here, we propose and investigate the dynamical encircling of multiple EPs in an anti-PT-symmetric system, which is constructed based on a one-dimensional lattice with staggered lossy modulation. We reveal that dynamically encircling the multiple EPs results in the chiral dynamics via multiple non-Hermiticity-induced nonadiabatic transitions, where the output state is always on the lowest-loss energy sheet. Compared with the PT-symmetric systems that require complicated variation of the gain/loss rate or on-site potentials, our system only requires modulations of the couplings which can be readily realized in various experimental platforms. Our scheme provides a route to study non-Hermitian physics by engineering the EPs and implement novel photonic devices with unconventional functions.

Postselection-Free Learning of Measurement-Induced Quantum Dynamics

We address how one can empirically infer properties of quantum states generated by dynamics involving measurements. Our focus is on many-body settings where the number of measurements is extensive, making brute-force approaches based on postselection intractable due to their exponential sample complexity. We introduce a general-purpose scheme that can be used to infer any property of the postmeasurement ensemble of states (e.g., the average entanglement entropy, or frame potential) using a scalable number of experimental repetitions. We first identify a general class of “estimable properties” that can be directly extracted from experimental data. Then, based on empirical observations of such quantities, we show how one can indirectly infer information about any particular given nonestimable quantity of interest through classical postprocessing. Our approach is based on an optimization task, where one asks what are the minimum and maximum values that the desired quantity could possibly take, while ensuring consistency with observations. The true value of this quantity must then lie within a feasible range between these extrema, resulting in two-sided bounds. Narrow feasible ranges can be obtained by using a classical simulation of the device to determine which estimable properties one should measure. Even in cases where this simulation is inaccurate, unambiguous information about the true value of a given quantity realized on the quantum device can be learned. As an immediate application, we show that our method can be used to verify the emergence of quantum state designs in experiments. We identify some fundamental obstructions that in some cases prevent sharp knowledge of a given quantity from being inferred, and discuss what can be learned in cases where classical simulation is too computationally demanding to be feasible. In particular, we prove that any observer who cannot perform a classical simulation cannot distinguish the output states from those sampled from a maximally structureless ensemble. Published by the American Physical Society 2024

Pretty good measurement for bosonic Gaussian ensembles

The pretty good measurement is a fundamental analytical tool in quantum information theory, giving a method for inferring the classical label that identifies a quantum state chosen probabilistically from an ensemble. Identifying and constructing the pretty good measurement for the class of bosonic Gaussian states is of immediate practical relevance in quantum information processing tasks. Holevo recently showed that the pretty good measurement for a bosonic Gaussian ensemble is a bosonic Gaussian measurement that attains the accessible information of the ensemble [IEEE Trans. Inf. Theory 66(9) (2020) 5634]. In this paper, we provide an alternate proof of Gaussianity of the pretty good measurement for a Gaussian ensemble of multimode bosonic states, with a focus on establishing an explicit and efficiently computable Gaussian description of the measurement. We also compute an explicit form of the mean square error of the pretty good measurement, which is relevant when using it for parameter estimation. Generalizing the pretty good measurement is a quantum instrument, called the pretty good instrument. We prove that the post-measurement state of the pretty good instrument is a faithful Gaussian state if the input state is a faithful Gaussian state whose covariance matrix satisfies a certain condition. Combined with our previous finding for the pretty good measurement and provided that the same condition holds, it follows that the expected output state is a faithful Gaussian state as well. In this case, we compute an explicit Gaussian description of the post-measurement and expected output states. Our findings imply that the pretty good instrument for bosonic Gaussian ensembles is no longer merely an analytical tool, but that it can also be implemented experimentally in quantum optics laboratories.

Threat-dependent scaling of prelimbic dynamics to enhance fear representation

Promptly identifying threatening stimuli is crucial for survival. Freezing is a natural behavior displayed by rodents toward potential or actual threats. Although it is known that the prelimbic cortex (PL) is involved in both risk evaluation and in fear and anxiety-like behavior expression, here we explored whether PL neuronal activity can dynamically represent different internal states of the same behavioral output (i.e., freezing). We found that freezing can always be decoded from PL activity at a population level. However, the sudden presentation of a fearful stimulus quickly reshaped the PL to a new neuronal activity state, an effect not observed in other cortical or subcortical regions examined. This shift changed PL freezing representation and is necessary for fear memory expression. Our data reveal the unique role of the PL in detecting threats and internally adjusting to distinguish between different freezing-related states in both unconditioned and conditioned fear representations.

Mission reliability evaluation and selective maintenance approach for manufacturing systems considering epistemic uncertainty

For manufacturing systems, the states of operational performance and functional output are essential indicators of their reliability evaluation, operational health state monitoring, and maintenance decision. However, due to the instability of the 5M1E factors, that is, Man, Machine, Method, Material, Measurement, and Environment, in the manufacturing process, certain components within these systems could introduce epistemic uncertainty factors and thus interfere with the results of evaluation and decision. Consequently, a novel integrated mission reliability evaluation and selective maintenance approach considering epistemic uncertainty is proposed. First, an uncertain–random operational model for manufacturing systems, in which the uncertain operational mechanisms are specified, is established as the foundation. Second, a mission reliability evaluation method for uncertain–random manufacturing systems that fuses the conformity and fitness quality data is proposed to cope with the challenge of epistemic uncertainty. Third, a selective maintenance decision model that maximizes the system’s mission reliability is developed in consideration of the uncertain factors within the operation process. Finally, a case study of a ferrite phase shifting unit manufacturing system is conducted to validate the proposed approach.

Mapping the Intersubunit Interdomain FMN-Heme Interactions in Neuronal Nitric Oxide Synthase by Targeted Quantitative Cross-Linking Mass Spectrometry.

Nitric oxide synthase (NOS) in mammals is a family of multidomain proteins in which interdomain electron transfer (IET) is controlled by domain-domain interactions. Calmodulin (CaM) binds to the canonical CaM-binding site in the linker region between the FMN and heme domains of NOS and allows tethered FMN domain motions, enabling an intersubunit FMN-heme IET in the output state for NO production. Our previous cross-linking mass spectrometric (XL MS) results demonstrated site-specific protein dynamics in the CaM-responsive regions of rat neuronal NOS (nNOS) reductase construct, a monomeric protein [Jiang et al., Biochemistry, 2023, 62, 2232-2237]. In this work, we have extended our combined approach of XL MS structural mapping and AlphaFold structural prediction to examine the homodimeric nNOS oxygenase/FMN (oxyFMN) construct, an established model of the NOS output state. We employed parallel reaction monitoring (PRM) based quantitative XL MS (qXL MS) to assess the CaM-induced changes in interdomain dynamics and interactions. Intersubunit cross-links were identified by mapping the cross-links onto top AlphaFold structural models, which was complemented by comparing their relative abundances in the cross-linked dimeric and monomeric bands. Furthermore, contrasting the CaM-free and CaM-bound nNOS samples shows that CaM enables the formation of the intersubunit FMN-heme docking complex and that CaM binding induces extensive, allosteric conformational changes across the NOS regions. Moreover, the observed cross-links sites specifically respond to changes in ionic strength. This indicates that interdomain salt bridges are responsible for stabilizing and orienting the output state for efficient FMN-heme IET. Taken together, our targeted qXL MS results have revealed that CaM and ionic strength modulate specific dynamic changes in the CaM/FMN/heme complexes, particularly in the context of intersubunit interdomain FMN-heme interactions.

On V-Geometric Ergodicity Markov Chains of the Two-Inertia Systems

This study employs the diffusion process to construct Markov chains for analyzing the common two-inertia systems used in industry. Two-inertia systems are prevalent in commonly used equipment, where the load is influenced by the coupling of external force and the drive shaft, leading to variations in the associated output states. Traditionally, the control of such systems is often guided by empirical rules. This paper examines the equilibrium distribution and convergence rate of the two-inertia system and develops a predictive model for its long-term operation. We explore the qualitative behavior of the load end at discrete time intervals. Our findings are applicable not only in control engineering, but also provide insights for small-scale models incorporating dual-system variables.

All-optical polarization scrambler based on polarization beam splitting with an amplified fiber ring

Optical-fiber-based polarization scramblers can reduce the impact of polarization sensitive performance of various optical fiber systems. Here, we propose a simple and efficient polarization scrambler based on an all-optical Mach-Zehnder structure by combining a polarization beam splitter and an amplified fiber ring. To totally decoherence one polarization split beam, a fiber ring together with an amplifier is incorporated. The ratio of two orthogonal beams can be controlled by varying the amplification factor, and we observe different evolution trajectories of the output state of polarizations on the Poincaré sphere. When the amplification factor exceeds a certain threshold, the scrambler system exhibits nearly ideal polarization scrambling behavior. A commercial single wavelength laser with a linewidth of 3 MHz is utilized to characterize the scrambling performance. We found that when the sampling rate is 1.6 MSa/s, a scrambling speed up to 2000krad/s can be obtained for the average degree of polarization being less than 0.1. We also exploit these random polarization fluctuations to generate random binary numbers, indicating that the proposed technique is a good candidate for a random bit generator.