Function Of State Research Articles

The renin-angiotensin-aldosterone system: An old tree sprouts new shoots

The intricate physiological and pathological diversity of the Renin-Angiotensin-Aldosterone System (RAAS) underpins its role in maintaining bodily equilibrium. This paper delves into the classical axis (Renin-ACE-Ang II-AT1R axis), the protective arm (ACE2-Ang (1–7)-MasR axis), the prorenin-PRR-MAP kinases ERK1/2 axis, and the Ang IV-AT4R-IRAP cascade of RAAS, examining their functions in both physiological and pathological states. The dysregulation or hyperactivation of RAAS is intricately linked to numerous diseases, including cardiovascular disease (CVD), renal damage, metabolic disease, eye disease, Gastrointestinal disease, nervous system and reproductive system diseases. This paper explores the pathological mechanisms of RAAS in detail, highlighting its significant role in disease progression. Currently, in addition to traditional drugs like ACEI, ARB, and MRA, several novel therapeutics have emerged, such as angiotensin receptor-enkephalinase inhibitors, nonsteroidal mineralocorticoid receptor antagonists, aldosterone synthase inhibitors, aminopeptidase A inhibitors, and angiotensinogen inhibitors. These have shown potential efficacy and application prospects in various clinical trials for related diseases. Through an in-depth analysis of RAAS, this paper aims to provide crucial insights into its complex physiological and pathological mechanisms and offer valuable guidance for developing new therapeutic approaches. This comprehensive discussion is expected to advance the RAAS research field and provide innovative ideas and directions for future clinical treatment strategies.

Efficiency of reversible MCMC methods: elementary derivations and applications to composite methods

Abstract We review criteria for comparing the efficiency of Markov chain Monte Carlo (MCMC) methods with respect to the asymptotic variance of estimates of expectations of functions of state, and show how such criteria can justify ways of combining improvements to MCMC methods. We say that a chain on a finite state space with transition matrix P efficiency-dominates one with transition matrix Q if for every function of state it has lower (or equal) asymptotic variance. We give elementary proofs of some previous results regarding efficiency dominance, leading to a self-contained demonstration that a reversible chain with transition matrix P efficiency-dominates a reversible chain with transition matrix Q if and only if none of the eigenvalues of $Q-P$ are negative. This allows us to conclude that modifying a reversible MCMC method to improve its efficiency will also improve the efficiency of a method that randomly chooses either this or some other reversible method, and to conclude that improving the efficiency of a reversible update for one component of state (as in Gibbs sampling) will improve the overall efficiency of a reversible method that combines this and other updates. It also explains how antithetic MCMC can be more efficient than independent and identically distributed sampling. We also establish conditions that can guarantee that a method is not efficiency-dominated by any other method.

Quantum transport of topological surface states in presence of circular n-p junctions

The surface states of topological insulators are characterized by spin-momentum locking, where the electron spin is locked perpendicular to its momentum. This property is preserved under gate potentials which can be used to manipulate spin currents without an external magnetic field enhancing the prospects for spintronic applications. Here, we investigate the scattering of the wave functions of topological surface states within the circular n-p junction positioned on the upper surface of the quintuple-layered three-dimensional topological insulator. With the analytical calculations we explain the scattering of these surface states in such systems.

A zero-dimensional 1-butylpiperazine-cadmium(II) hybrid material: Synthesis, structural analysis, and DFT studies

This study reports the synthesis and characterization of an organoammonium-cadmium(II) hybrid material, (BPH₂)₂[Cd₂Cl₈] (BP = 1-butylpiperazine), using a combination of experimental and theoretical techniques. Single-crystal X-ray diffraction shows a centrosymmetric crystal structure in the P1¯ space group, featuring a zero-dimensional (0D) arrangement where binuclear [Cd₂Cl₈]⁴⁻ anions and (C₈H₂₀N₂⁺) cations are linked by N—H···Cl and C—H···Cl hydrogen bonds. Hirshfeld surface analysis further elucidates these intermolecular noncovalent interactions, highlighting the dominant role of H···Cl contacts in the molecular packing. The crystal morphology is further investigated via the Bravais-Friedel-Donnay-Harker (BFDH) model. Infrared (IR) spectroscopic analysis was conducted to identify vibrational modes, confirm structure, and elucidate bonding features. Additionally, Experimental UV–visible study indicates an optical band gap energy of 4.75 eV, and density functional theory (DFT) calculations corroborate these findings, predicting a direct band gap of 4.45 eV. Moreover, theoretical calculations, including the complex dielectric function, band structure, and total density of states (DOS), were performed to explore the electrical and optical properties. Finally, the chemical reactivity was evaluated using conceptual-DFT descriptors at the B3LYP/SDD/aug-cc-pVTZ level of theory.

High-throughput optimized prime editing mediated endogenous protein tagging for pooled imaging of protein localization.

The subcellular organization of proteins carries important information on cellular state and gene function, yet currently there are no technologies that enable accurate measurement of subcellular protein localizations at scale. Here we develop an approach for pooled endogenous protein tagging using prime editing, which coupled with an optical readout and sequencing, provides a snapshot of proteome organization in a manner akin to perturbation-based CRISPR screens. We constructed a pooled library of 17,280 pegRNAs designed to exhaustively tag 60 endogenous proteins spanning diverse localization patterns and explore a large space of genomic and pegRNA design parameters. Pooled measurements of tagging efficiency uncovered both genomic and pegRNA features associated with increased efficiency, including epigenetic states and interactions with transcription. We integrate pegRNA features into a computational model with predictive value for tagging efficiency to constrain the design space of pegRNAs for large-scale peptide knock-in. Lastly, we show that combining in-situ pegRNA sequencing with high-throughput deep learning image analysis, enables exploration of subcellular protein localization patterns for many proteins in parallel following a single pooled lentiviral transduction, setting the stage for scalable studies of proteome dynamics across cell types and environmental perturbations.

Correlation functions from tensor network influence functionals: The case of the spin-boson model.

We investigate the application of matrix product state (MPS) representations of the influence functionals (IFs) for the calculation of real-time equilibrium correlation functions in open quantum systems. Focusing specifically on the unbiased spin-boson model, we explore the use of IF-MPSs for complex time propagation, as well as IF-MPSs for constructing correlation functions in the steady state. We examine three different IF approaches: one based on the Kadanoff-Baym contour targeting correlation functions at all times, one based on a complex contour targeting the correlation function at a single time, and a steady state formulation, which avoids imaginary or complex times, while providing access to correlation functions at all times. We show that within the IF language, the steady state formulation provides a powerful approach to evaluate equilibrium correlation functions.

Intrinsic squeezing of mechanical motion of a harmonically trapped atom with spin-orbit coupling

In this paper we investigated one-dimensional harmonically trapped atom with Raman-induced spin-orbit coupling by mapping to quantum-like model. Using displacement Fock states in quantum optics and variational methods we found the odd-parity superposition state of left- and right-displaced oscillator state is a good approximate solution to the ground state, which captures the essential physics of the system. The ground state wave function owes nodes which is remarkably different from the conventional no-node theory in quantum mechanics. The results show the atomic motion of center of mass exhibits intrinsic squeezing properties with relation to the Raman and spin-orbit coupling strength characterized by the variance in position and momentum, information entropy, as well as the Wigner function of the ground state. The dynamics of center of mass are also studied which demonstrates intuitive Zitterbewegung oscillations in momentum space and real space. Our results could be used for observing Zitterbewegung oscillations in neutral atomic gases and engineering nonclassic states.

Court Navigators and Opportunities for Disseminating Overdose Prevention Strategies.

Objective. Describe how navigator programs from three New England states (Connecticut, Maine, and Massachusetts) function to connect individuals using court services to community-based treatment and services. Hypothesis. Implementation science frameworks can be used to analyze how multiple court programs function to inform replication and address gaps in the use of overdose prevention strategies. Method. The Template for Intervention Description and Replication (TIDieR) Implementation informed semi-structured interviews as part of an exploratory mixed-methods analysis of court navigator programs. Analysis of interviews based on the TIDieR and administrative data on client contacts (n = 436) were analyzed. A subsample of clients with additional background information (n = 249) was used to examine court navigator recommendations. Results. The TIDieR revealed court navigator programs shared basic intervention characteristics but varied dramatically by resources and organization contexts. Nearly half (46.5%) of clients were self-referred and more than two-thirds (69.1%) approved follow-up but varied by program. Of those allowing follow-up, more than one-third (35.7%) had previously experienced an overdose. Court navigators were significantly more likely to refer clients with a history of overdose to locations where they can receive naloxone (the opioid overdose antidote) though only one program had naloxone on hand. Conclusion. Navigators are employed by community organizations with access to courthouses to provide resources to those passing through. These efforts can be implemented to support linkages to treatment and services but there is a significant gap in the allocation of overdose prevention strategies in court settings and court navigator programs have the potential to address this unmet need.

Police and civil society partnership: Peculiarities of implementation in modern conditions

The purpose of the article is to find out the peculiarities of the implementation of partnership relations between the police and civil society in modern conditions, based on the analysis of current Ukrainian and foreign legislation, as well as scientific literature. Partnership as a type of social interaction is characterized by the authors of the article. The essence of the term “partnership” in modern foreign science is analyzed. The main features of the partnership model of interaction of subjects are characterized, with an emphasis on the partnership between the police and civil society institutions. The main components of the mechanism of partnership interaction between the institutions of the State and civil society institutions in the field of law enforcement are considered. The experience of different countries related to the partnership of law enforcement agencies and civil society institutions is described, with the aim of promoting the formation of effective forms of partnership between the police and civil society institutions in modern Ukraine. The importance of building in Ukraine an effective partnership model of cooperation between the police and civil society institutions in modern Ukraine is emphasized. The importance of public participation in the implementation of state functions in the field of security in modern conditions is proved. The importance of trust for effective partnership is emphasized.

Constrained Model Predictive Control for Generation Power Distribution on Aircraft Engines

Aiming at the increasing demand for electric energy in aircraft in the future, a multi-objective optimization aircraft engine constrained model predictive control method based on generation power distribution is proposed. Firstly, based on the aircraft engine component level model and the equilibrium manifold theory, the aircraft engine equilibrium manifold expansion model is established. Secondly, the influence of the power generation is modeled, and the influence of the low- and high-pressure shaft generators on the normal operation of the aircraft engine is studied and compared. The control variables such as fuel flow and total generation power are taken as the constraint conditions to design the constraint model predictive controller. Furthermore, the multi-objective grey wolf optimization algorithm is introduced to intelligently optimize the parameters of the designed controller. At last, the simulation based on the component level model shows that the high-pressure shaft generator has less influence on the state quantity, including engine thrust, than the low-pressure shaft generator. The proposed control method using the multi-objective gray wolf optimization (MOGWO) algorithm has rapid response and no steady-state error.

Behavioral state and stimulus strength regulate the role of somatostatin interneurons in stabilizing network activity.

Inhibition stabilization enables cortical circuits to encode sensory signals across diverse contexts. Somatostatin-expressing (SST) interneurons are well-suited for this role through their strong recurrent connectivity with excitatory pyramidal cells. We developed a cortical circuit model predicting that SST cells become increasingly important for stabilization as sensory input strengthens. We tested this prediction in mouse primary visual cortex by manipulating excitatory input to SST cells, a key parameter for inhibition stabilization, with a novel cell-type specific pharmacological method to selectively block glutamatergic receptors on SST cells. Consistent with our model predictions, we find antagonizing glutamatergic receptors drives a paradoxical facilitation of SST cells with increasing stimulus contrast. In addition, we find even stronger engagement of SST-dependent stabilization when the mice are aroused. Thus, we reveal that the role of SST cells in cortical processing gradually switches as a function of both input strength and behavioral state.

State feedback control of HPR1000 average coolant temperature based on dominant pole

Control of nuclear power plant is still based on the traditional PID control system, which is difficult to obtain high control quality in the process of a wide range of load changes. To effectively use the measurable information of the system and consider the constraints, state feedback control based on the dominant pole method is proposed for the average coolant temperature control of HPR1000. The control system is divided into two parts: one part is a feedback branch, which realizes the state feedback by using the measurable system state quantity including the core inlet temperature, the core outlet temperature and the reactor power, and at the same time introduces the integral link to reduce the steady-state error; the other part is a feedforward branch, which uses the nominal load change to make feedforward compensation to improve the control performance of load tracking. At the same time, Particle Swarm Optimization (PSO) method is used to optimize the controller parameters, and the dominant pole meeting the requirements is obtained. The control performance under different working conditions is verified on the HPR1000 model. The test results show that the state feedback control can effectively improve the setpoint tracking ability and anti-disturbance ability.

Production of dileptonic bound states in the Higgs boson decay

The production of single and paired lepton bound states in the decay of the Higgs boson has been studied. We explore different decay mechanisms that contribute significantly to the decay width. The decay widths are calculated taking into account relativistic corrections in the decay amplitude and in the wave function of the bound state of leptons. Published by the American Physical Society 2024

Two-Stage Hyperelliptic Kalman Filter-Based Hybrid Fault Observer for Aeroengine Actuator under Multi-Source Uncertainty

An aeroengine faces multi-source uncertainty consisting of aeroengine epistemic uncertainty and the control system stochastic uncertainty during operation. This paper investigates actuator fault estimation under multi-source uncertainty to enhance the fault diagnosis capability of aero-engine control systems in complex environments. With the polynomial chaos expansion-based discrete stochastic model quantification, the optimal filter under multi-source uncertainty, the Hyperelliptic Kalman Filter, is proposed. Meanwhile, by treating actuator fault as unknown input, the Two-stage Hyperelliptic Kalman Filter (TSHeKF) is also proposed to achieve optimal fault estimation under multi-source uncertainty. However, considering that the biases of the model are often fixed for the individual, the TSHeKF-based fault estimation is robust and leads to inevitable conservativeness. By adding the additional estimation of the unknown deviation in state function caused by probabilistic system parameters, the hybrid fault observer (HFO) is proposed based on the TSHeKF and realizes conservativeness-reduced estimation for actuator fault under multi-source uncertainty. Numerical simulations show the effectiveness and optimality of the proposed HFO in state estimation, output prediction, and fault estimation for both single and multi-fault modes, when considering multi-source uncertainty. Furthermore, Monte Carlo experiments have demonstrated that the HFO-based optimal fault estimation is less conservative and more accurate than the Two-stage Kalman Filter and TSHeKF, providing better safety and more reliable aeroengine operation assurance.

Cell-based therapies reverse the heart failure-altered right ventricular proteome.

Congenital heart defects can lead to right ventricular (RV) pressure-overload and heart failure. Cell-based therapies, including mesenchymal stromal cells (MSCs) and c-kit positive cells (CPCs) have been studied clinically as options to restore heart function in disease states. Many studies have indicated these cells act through paracrine mechanisms to prevent apoptosis, promote cellular function, and regulate gene/protein expression. We aimed to determine the proteomic response of diseased hearts to cell therapy. We utilized an animal model of RV pressure overload created by banding the pulmonary artery (PAB). Two weeks post-banding, bone marrow-derived mesenchymal stromal cells (MSCs) and 3 populations of CPCs (nCPCs, cCPCs, ES-CPCs) were delivered to the RV free wall. RV function and cellular retention were measured for four weeks post-injection, at which point hearts were extracted and the RV was excised for liquid chromatography and tandem mass spectrometry. Resulting RV proteomes were compared and analyzed using systems biology and bioinformatics. Proteomic profiling identified 1156 total proteins from the RV, of which 5.97% were significantly changed after PAB. This disease-altered proteome was responsive to cellular therapy, with 72% of the PAB-altered proteome being fully or partially reversed by MSC therapy. This was followed by nCPCs (54%), ES-CPCs (52%), and cCPCs (39%). Systems biology and bioinformatics analysis showed MSC, nCPC, or ES-CPC cell therapy is associated with a decrease in predicted adverse cardiac effects. We also observed an effect of cell therapy on the non-altered RV proteome, however, this was associated with minor predicted pathological endpoints. Our data indicate MSCs, ES-CPCs, and nCPCs significantly reverse the PAB-altered proteome towards a pre-disease state. These results indicate cell-based therapies show promise in improving RV function after pressure overload through partial restoration of the disease-altered cardiac proteome.

Trust, trustworthiness and AI governance

An emerging issue in AI alignment is the use of artificial intelligence (AI) by public authorities, and specifically the integration of algorithmic decision-making (ADM) into core state functions. In this context, the alignment of AI with the values related to the notions of trust and trustworthiness constitutes a particularly sensitive problem from a theoretical, empirical, and normative perspective. In this paper, we offer an interdisciplinary overview of the scholarship on trust in sociology, political science, and computer science anchored in artificial intelligence. On this basis, we argue that only a coherent and comprehensive interdisciplinary approach making sense of the different properties attributed to trust and trustworthiness can convey a proper understanding of complex watchful trust dynamics in a socio-technical context. Ensuring the trustworthiness of AI-Governance ultimately requires an understanding of how to combine trust-related values while addressing machines, humans and institutions at the same time. We offer a road-map of the steps that could be taken to address the challenges identified.

Ab Initio Manganese Kα and Kβ Energy Eigenvalues, Shake-Off Probabilities, Auger Rates, with Convergence Tests.

This work presents ab initio calculations for the Kα spectrum of manganese (Z = 25, [Ar]3d54s2), a highly complex system due to the five open orbitals in the 3d shell. The spectrum is composed of the canonical diagram line [1s]→[2p] and shake-off satellite lines [1snl]→[2pnl] (nl∈{2s,2p,3s,3p,3d,4s}), where square brackets denote a hole state. The multiconfiguration Dirac-Hartree-Fock method with the active set approach provides the initial and final atomic wavefunctions. Results are presented as energy eigenvalue spectra for the diagram and satellite transitions. The calculated wavefunctions include over one hundred million configuration state functions and over 280,000 independent transition energies for the seven sets of spectra considered. Shake-off probabilities and Auger transition rates determine satellite intensities. The number of configuration state functions ensures highly-converged wavefunctions. Several measures of convergence demonstrate convergence in the calculated parameters. We obtain convergence of the transition energies in all eight transitions to within 0.06 eV and shake-off probabilities to within 4.5%.

Performance Evaluation of Model-Based Online Condition Monitoring Algorithms for Li-Ion Battery State Estimation

This discovery examines and tests four model-based charge-state (SOC) estimation methods for lithium-ion (Li-ion) batteries. This work evaluates some parts of the SOC estimation, such as error distribution evaluation, rise time estimation, consumption time estimation, etc., instead of the former probing. The battery comparison model is introduced and the state function of the model is inferred. The first step is to study four model-based SOC estimation strategies. The four systems are then tested using simulation and analysis. To mimic the driving conditions of an electric vehicle, the Urban Dynamometer Driving Schedule (UDDS) flow profiles are used. A genetic calculation is then used to find the limits of the model to determine the optimal limits of the Li-ion battery model. The simulations are run continuously and without interruption, and the results are analyzed. To test the device in circle discovery, a battery test bench is developed and uses a Li-ion battery.

Liver toxicity and repair evaluated by histopathology and electric modulus.

Detoxification is one of the most important liver functions. Therefore, liver is the front line of defense when the biosystem faces drug overdose, toxins, and anything that may cause harm. Some famous antibiotics are known for their side effects on liver; one of them is amoxicillin, AM. This work has investigated the toxic effect of amoxicillin on rat's liver with overdose (90mg/kg) and has studied the ameliorative role of protective and therapeutic Ashwagandha seeds extract (ASE) at doses (100, 200, and 300mg/kg) against this toxicity. To achieve this work, the authors used two modalities; the first is liver histopathology to figure out the amoxicillin and ASE effects and to detect the sensitivity of another modality; the electric modulus, and its related thermodynamic parameters of liver tissue. Histopathological examination showed that the role of therapeutic ASE in reducing amoxicillin (AM) toxicity was more effective than the protective one. Also, most dielectric and thermodynamic results achieved the same result. Histopathology confirmed the liver injury by amoxicillin and the partial repair by the biosystem using ASE. Moreover, electric modulus, related dielectric parameters, and their thermodynamic state functions showed different changes in their values under the effect of amoxicillin. Using ASE helped the biosystem to restore these changes near their control values.

Modeling and prediction of workpiece nonlinear physical quantities based on extended Kalman filter

Abstract For the workpiece from the tool withdrawal time until the lifting of the fixture constraint is called the in-situ state. In this process, the workpiece’s state quantity changes with time, and the state quantity can be regarded as a time series physical quantity. Therefore, the physical state and geometric physical quantities in the in-situ stage can be characterized by time sequence through the deformation theory. Kalman filter is a kind of optimal estimation method that includes two processes: prediction and correction. In the process of prediction estimation, only the optimal estimation of the last time needs to be stored, which can reduce the operation cost and improve the prediction efficiency. Since the state quantity of the workpiece in situ becomes nonlinear, this paper uses the extended Kalman filter for characterization modeling and nonlinear prediction, combines the typical heat-force coupling model with the extended Kalman filter for representation, and finally obtains the modeling characterization and result prediction of the filter state quantity.