Steady-state Parameters Research Articles

A Novel Interpolation Method for Soil Parameters Combining RBF Neural Network and IDW in the Pearl River Delta

Soil fertility is a critical factor in agricultural production, directly impacting crop growth, yield, and quality. To achieve precise agricultural management, accurate spatial interpolation of soil parameters is essential. This study developed a new interpolation prediction framework that combines Radial Basis Function (RBF) neural networks with Inverse Distance Weighting (IDW), termed the IDW-RBFNN. This framework initially uses the IDW method to apply preliminary weights based on distance to the data points, which are then used as input for the RBF neural network to form a training dataset. Subsequently, the RBF neural network further trains on these data to refine the interpolation results, achieving more precise spatial data interpolation. We compared the interpolation prediction accuracy of the IDW-RBFNN framework with ordinary Kriging (OK) and RBF methods under three different parameter settings. Ultimately, the IDW-RBFNN demonstrated lower error rates in terms of RMSE and MRE compared to direct RBF interpolation methods when adjusting settings based on different power values, even with a fixed number of data samples. As the sample size decreases, the interpolation accuracy of OK and RBF methods is significantly affected, while the error of IDW-RBFNN remains relatively low. Considering both interpolation accuracy and resource limitations, we recommend using the IDW-RBFNN method (p = 2) with at least 60 samples as the minimum sampling density to ensure high interpolation accuracy under resource constraints. Our method overcomes limitations of existing approaches that use fixed steady-state distance decay parameters, providing an effective tool for soil fertility monitoring in delta regions.

Dynamic processes of fate decision in inducible bistable systems

The process of biological fate decision regulated by gene regulatory networks (GRNs) involves numerous complex dynamical interactions among many components. Mathematical modeling typically employed ordinary differential equations (ODEs) and steady-state analysis, which has yielded valuable quantitative insights. However, stable states predicted by theoretical models often fail to capture transient or metastable phenomena that occur during most observation periods in experimental or real biological systems. We attribute this discrepancy to the omission of dynamic processes of various complex interactions. Here, we demonstrate the influence of delays in gene regulatory steps and the time scales of the external induction on the dynamic processes of the fate decision in inducible bistable systems. We propose that steady-state parameters determine the landscape of fate decision. However, during the dynamic evolution along the landscape, the unequal delays of biochemical interactions as well as time scale of external induction cause deviations in the differentiation trajectories, leading to the formation of new transient distributions that persist long-term. Our findings emphasize the importance of considering dynamic processes in fate decision, instead of relying solely on steady-state analysis. We provide insights into the interpretation of experimental phenomena, and offer valuable guidance for future efforts in dynamical modeling and synthetic biology design.

Weightless Model Predictive Control for Permanent Magnet Synchronous Motors with Extended State Observer

Traditional model predictive torque control (MPTC) predicts the torque and flux values for the next time step and selects the voltage vector that minimizes the cost function as the optimal vector to apply to the inverter. This control approach is straightforward and allows for multi-objective control, but it has some issues in terms of the dynamic steady-state performance and parameter robustness. Therefore, this paper proposes a weightless model predictive control method based on an extended state observer (ESO). By designing an improved ESO to observe and compensate for motor parameter disturbances in real time, and employing a novel 2-D switching table and voltage vector sector selection diagram, the method evaluates three out of eight voltage vectors based on the torque and stator flux error signals. This reduces the computational load while increasing the number of candidate voltage vectors. Finally, a cost function without weighting factors is designed to lower the computational complexity. The simulation results show that the proposed new control method effectively reduces the torque and flux ripple and improves the current waveform compared to traditional MPTC.

Lubrication Characteristics of Dry-Gas Seals with Spiral Grooves

To obtain an optimal range of structural parameters for dry-gas seals with good performance, this study employed advanced sensing technology to monitor and analyze the internal flow characteristics of dry-gas seals in real time. Additionally, the validity of the calculation program was verified through experimentation. Using steady-state performance parameters as evaluation indices, a calculation model with lubrication characteristics was developed. The results indicate that when there are 12 grooves, the gas film pressure distribution is uniform and has a high value. At pressures greater than 2 MPa, the opening force, leakage, and gas film stiffness change significantly due to enhanced dynamic pressure effects with high-pressure differences, which reduces the local contact forces and frictional forces. At a constant speed, decreasing the gas film thickness increases the pressure difference while increasing both the opening force and film stiffness; however, at higher rotational speeds where the gas flow becomes non-uniform, the stability of the gas film is affected, leading to increased frictional forces. When there are between 10 and 16 grooves with depths ranging from 5.0 to 6.0 μm, dynamic pressure effects caused by pressure gradients become apparent, resulting in good dry-gas sealing performance being achieved. This research provides a theoretical reference for optimizing the design of dry-gas seals, as well as their steady-state seal performance.

TMS320F28379D microcontroller for speed control of permanent magnet direct current motor

<p><span>This paper aims to study the behavior of the <a name="_Hlk169245133"></a>proportional integral derivative (PID) and the fuzzy-based tuning PI-D controller for speed control of a permanent magnet direct current (PMDC) motor. The proposed method used a fuzzy-based tuning PI-D controller with a MATLAB/Simulink program to design and real-time implement a TMS320F28379D microcontroller for speed control of a PMDC motor. The performance of the study designed fuzzy-based tuning PI-D and PID controllers is compared and investigated. The fuzzy logic controller applies the controlling voltage based on motor speed errors. Finally, the result shows the fuzzy-based tuning PI-D controller approach has a minimum overshoot, and minimum transient and steady state parameters compared to the PID controller to control the speed of the motor. The PID controllers have poorer performance due to the non-linear features of the PMDC motor.</span></p>

Optimising creep constitutive modelling of layered soft rocks using particle swarm method

ABSTRACT Investigation of constitutive models is crucial for understanding the creep behaviour of soft rock and mitigating large deformation disasters. However, the presence of bedding layers in rock masses complicates the determination of creep parameters, increasing testing costs. Therefore, this study aims to conduct parameter optimisation analysis using the particle swarm method to refine creep parameters for soft rock with varying dip angles and analyse their effects. The framework and methodology of the model are presented, where the classical Burgers model was chosen as the constitutive model and the creep parameters to be optimised were determined. The dataset records the creep behaviours of soft rock with different dip angles prepared through laboratory experiments on 3D printing specimens. The proposed model is applied to this dataset to determine optimal creep parameters. Results indicate that transient and steady-state creep parameters increase proportionally with the dip angle, while the viscosity coefficient decreases. The optimised model demonstrates improved descriptive capabilities, contributing to understanding the creep properties of challenging geological formations and guiding on-site reinforcement measures.

Multiple-Dose Pharmacokinetics and Safety of Mitragynine, the Major Alkaloid of Kratom, in Rats.

This study reports the steady-state pharmacokinetic parameters for mitragynine and characterizes its elimination in male and female rats. Four male and female rats were dosed q12h with 40 mg/kg, and orally administered mitragynine for 5 and 6 days, respectively. Using a validated ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method, the plasma concentrations of mitragynine, its metabolites (7-hydroxymitragynine, 9-hydroxycorynantheidine, and mitragynine acid), and a non-CYP oxidation product (3-dehydromitragynine) were determined at various time points. Sex differences in pharmacokinetics were observed, with females demonstrating significantly higher systemic exposure of mitragynine than males. The mitragynine area under the curve normalized by the dose interval (AUC/τ) was 6741.6 ± 869.5 h*ng/mL in female rats and 1808.9 ± 191.3 h*ng/mL in males (p < 0.05). Both sexes produced similar metabolite profiles; the major metabolites were mitragynine acid and 9-hydroxycorynantheidine. 7-Hydroxymitragynine was a minor metabolite. However, higher exposure (AUCs) and the maximum plasma concentrations (C max) of active metabolites, 7-hydroxymitragynine and 9-hydroxycorynantheidine, were observed in female rats and exhibited substantial sex differences. Renal clearance of mitragynine (CLr) was low (0.64 ± 0.3 mL/h in males and 0.98 ± 0.4 mL/h in females), and unchanged mitragynine accounted for <1% of the dose excreted in feces (both sexes). The clinical chemistry, complete blood count, and hematological test results reported no abnormal hematological findings after multiple dosing in either sex.

Modelling Steady State and Transient Stability Parameters for Kainji Hydropower Station, Nigeria

The study explores the creation of a simulator for addressing the problem of predicting response of Nigeria’s Kainji’s Hydro Power Plant (KHPP) to system load variations and to determine parameters for stable operation. A virtual KHPP Simulation Model was designed and created using MatLab/Simulink software. The components of the HSS designed and incorporated in the virtual simulator include models of all eight (8) generating units (GUs). Each GU model consists of the Hydraulic Turbine Governor (PID), synchronous generator and an excitation system. The simulator was tested with steady state stability (SSS) and transient stability (TS) disturbances to obtain response values of system operating state parameters. The tests include a variable load increase, and three-phase short circuit fault for a duration of 0.2 s. The SSS limits established are the following: active load – 810 MW, load angle – 850, terminal voltage 0.68 pu, rotor speed 1.08 pu, excitation voltage 1.55 pu, and stator current 7.5 pu. TS limits established are load angle (1700), terminal voltage (0.60 pu), rotor speed (1.05) pu, excitation voltage (1.25 pu), stator current (7.1 pu), and critical clearing time (0.2s). Clearing time should be set at 0.2s to prevent KHPP and connected system’s instability.

Effect of Radial Neutron Reflector on the Characteristics of Nuclear Fuel Burn-Up Wave in a Fast Neutron Energy Spectrum Multiplying Medium: A Consistent Parametric Approach

Abstract The influence of radial neutron reflector on the build-up and propagation of a nuclear fuel burn-up wave in a fast multiplying medium is investigated using a consistent parametric approach. Coupled multigroup neutron diffusion equations with a burn-up evolution model are simulated on the two-dimensional cylindrical reactor geometry with azimuthal symmetry. Uranium–plutonium transmutation model is considered, and the simulation is performed by using the finite element multiphysics software package comsol. Transient characteristics of the burn-up wave are represented by two new parameters, namely, transient time (TT) and transient length (TL). TT and TL are defined as the time and distance required for the burn-up wave to attain its steady-state nature. Steady-state phases are characterized in terms of wave velocity, full width half maximum (FWHM), and full width 10% of maximum (FW10M). A sensitivity study of steady-state and transient parameters is conducted for the different values of radial reflector thickness. The potential relevance of these characterization parameters on the development of optimal geometrical configuration of radial neutron reflector in breed and burn (B&amp;B)-based reactor design is addressed based on the sensitivity study.

Saturation Mutagenesis and Molecular Modeling: The Impact of Methionine 182 Substitutions on the Stability of β-Lactamase TEM-1.

Serine β-lactamase TEM-1 is the first β-lactamase discovered and is still common in Gram-negative pathogens resistant to β-lactam antibiotics. It hydrolyzes penicillins and cephalosporins of early generations. Some of the emerging TEM-1 variants with one or several amino acid substitutions have even broader substrate specificity and resistance to known covalent inhibitors. Key amino acid substitutions affect catalytic properties of the enzyme, and secondary mutations accompany them. The occurrence of the secondary mutation M182T, called a "global suppressor", has almost doubled over the last decade. Therefore, we performed saturating mutagenesis at position 182 of TEM-1 to determine the influence of this single amino acid substitution on the catalytic properties, thermal stability, and ability for thermoreactivation. Steady-state parameters for penicillin, cephalothin, and ceftazidime are similar for all TEM-1 M182X variants, whereas melting temperature and ability to reactivate after incubation at a higher temperature vary significantly. The effects are multidirectional and depend on the particular amino acid at position 182. The M182E variant of β-lactamase TEM-1 demonstrates the highest residual enzymatic activity, which is 1.5 times higher than for the wild-type enzyme. The 3D structure of the side chain of residue 182 is of particular importance as observed from the comparison of the M182I and M182L variants of TEM-1. Both of these amino acid residues have hydrophobic side chains of similar size, but their residual activity differs by three-fold. Molecular dynamic simulations add a mechanistic explanation for this phenomenon. The important structural element is the V159-R65-E177 triad that exists due to both electrostatic and hydrophobic interactions. Amino acid substitutions that disturb this triad lead to a decrease in the ability of the β-lactamase to be reactivated.

Floquet engineering Higgs dynamics in time-periodic superconductors

Higgs modes emerge in superconductors as collective excitations of the order-parameter amplitude when periodically driven by electromagnetic radiation. In this work, we develop a Floquet approach to study Higgs modes in superconductors under time-periodic driving, where the dynamics of the order parameter is captured by anomalous Floquet Green's functions. We show that the Floquet description is particularly powerful as it allows one to exploit the time-periodic nature of the driving, thus considerably reducing the complexity of the time-dependent problem. Interestingly, the Floquet approach is also enlightening because it naturally offers a physical explanation for the renormalized steady-state order parameter as a result of photon-assisted transitions between Floquet sidebands. We demonstrate the usefulness of Floquet engineering Higgs modes in time-periodic s-wave superconductors. Published by the American Physical Society 2024

Anesthesia Considerations in Patients Undergoing Spine Surgery with Evoked Potential Monitoring

Intra-operative neuromonitoring (IONM) facilitates monitoring of the functional integrity of neural structures under general anesthesia. It aids in early detection of injury and minimizes postoperative neurologic deficit. IONM may be used during spine surgery, where either the blood supply to the spinal cord could be compromised or the surgical procedures where there is manipulation of the spinal cord. Somatosensory evoked potentials (SSEPs) and motor evoked potentials (MEPs) are used to monitor the sensory and motor tracts in the spinal cord, respectively. Preoperatively, a team of surgeons, anesthetists, and neurophysiologists must discuss about modalities of IONM to be used, expected changes, and alarm criteria. Anesthesia drugs need to be appropriately selected to facilitate IONM, as they affect the SSEP and MEP response obtained. Both total intravenous anesthesia and balanced anesthesia technique may be used, with appropriate titration of drugs. False-positive changes in evoked potentials (EPs) must be prevented by a steady anesthesia state and physiologic parameters. It is preferable to have a checklist to follow whenever changes in EP response are observed to rule out surgical, anesthetic, and monitoring-related causes for change in response. Risk–benefit must be assessed before the selection of a patient for EP monitoring as it may be rarely associated with complications such as burns, seizures, and bite injuries to lips, tongue, and endotracheal tube. Teamwork with meticulous planning, preparation, and multidisciplinary communication is essential for the safe conduct of spine surgeries with SSEP and MEP monitoring. In this review, we discuss various considerations for anesthesia management in patients with intraoperative EP monitoring.

A Comprehensive Study on Model Simplification and Parameter Estimation of Brushless Doubly Fed Standalone Generation System

Brushless doubly-fed induction generator (BDFIG) has great potential in stand-alone generation applications. Currently, lots of control strategies have been proposed based on the BDFIG d-q model with different machine parameters ignored for simplification, but the simplification influences on model accuracy have not been discussed systematically, and the application ranges are not clear. Therefore, aiming at controller design, this paper provides a comprehensive study on model simplification and parameter estimation of brushless doubly-fed stand- alone generation. Based on the intuitive DFIG-like BDFIG model and the typical electrical quantity relations widely used in stand-alone controller design, steady-state and dynamic parameter sensitivities of BDFIG are analyzed with operation condition fully considered. Based on the analysis, the universal BDFIG simplified d-q model aiming at stand-alone control is evaluated sufficiently, and the application range is clarified. The simplification of control analysis is illustrated, and a highly-targeted and simple parameter estimation method is proposed for simplified modeling and control. Finally, simulations and experiments verify the analysis accuracy of the simplified DFIG-like BDFIG model and the feasibility of the proposed parameter estimation method.

A novel solution to optimal power flow problems using composite differential evolution integrating effective constrained handling techniques

Optimal power flow is a complex and highly non-linear problem in which steady-state parameters are needed to find a network’s efficient and economical operation. In addition, the difficulty of the Optimal power flow problem becomes enlarged when new constraints are added, and it is also a challenging task for the power system operator to solve the constrained Optimal power flow problems efficiently. Therefore, this paper presents a constrained composite differential evolution optimization algorithm to search for the optimum solution to Optimal power flow problems. In the last few decades, numerous evolutionary algorithm implementations have emerged due to their superiority in solving Optimal power flow problems while considering various objectives such as cost, emission, power loss, etc. evolutionary algorithms effectively explore the solution space unconstrainedly, often employing the static penalty function approach to address the constraints and find solutions for constrained Optimal power flow problems. It is a drawback that combining evolutionary algorithms and the penalty function approach requires several penalty parameters to search the feasible space and discard the infeasible solutions. The proposed a constrained composite differential evolution algorithm combines two effective constraint handling techniques, such as feasibility rule and ɛ constraint methods, to search in the feasible space. The proposed approaches are recognized on IEEE 30, 57, and 118-bus standard test systems considering 16 study events of single and multi-objective optimization functions. Ultimately, simulation results are examined and compared with the many recently published techniques of Optimal power flow solutions owing to show the usefulness and performance of the proposed a constrained composite differential evolution algorithm.

Identification of a novel Scn3b mutation in a Chinese Brugada syndrome pedigree: implications for Nav1.5 electrophysiological properties and intracellular distribution of Nav1.5 and Navβ3.

The Scn3b gene encodes for Navβ3, a pivotal regulatory subunit of the fast sodium channel in cardiomyocytes. However, its mutation status in the Chinese population suffering from Brugada Syndrome (BrS) has not been characterized, and the contributory pathophysiological mechanisms to disease pathology remain undefined. A Scn3b (c.260C>T, p.P87l) mutation was identified in a patient with BrS of Chinese descent. Functional analyses demonstrated that sodium channel activation for the wild type, mutant samples, and co-expression of both commenced at -55 mv and peaked at -25 mv. The mutant group exhibited a notable reduction, approximately 60%, in peak sodium channel activation current (INa) at -25 mv. The parameters for half-maximal activation voltages (V1/2) and slope factors (k) showed no significant differences when comparing wild type, mutant, and combined expression groups (P = 0.98 and P = 0.65, respectively). Additionally, no significant disparities were evident in terms of the steady-state sodium channel inactivation parameters V1/2 and k (with P-values of 0.85 and 0.25, respectively), nor were there significant differences in the activation time constant τ (P = 0.59) and late sodium current density (P = 0.23) across the wild-type, mutant, and co-expressed groups. Confocal imaging and Western blot analysis demonstrated decreased plasma membrane localization of SCN3B and SCN5A in the P87l group. Computational simulations of cardiac action potentials suggested that SCN3B P87l can alter the morphology of the action potentials within the endocardium and epicardium while reducing the peak of depolarization. The pathogenic impact of the Scn3b P87l mutation predominantly originates from a reduction in peak INa activation current coupled with decreased cell surface expression of Nav1.5 and Navβ3. These alterations may influence cardiac action potential configurations and contribute to the risk of ventricular arrhythmias in individuals with BrS.

Anomalous phase diagram of the elastic interface with nonlocal hydrodynamic interactions in the presence of quenched disorder.

We investigate the influence of quenched disorder on the steady states of driven systems of the elastic interface with nonlocal hydrodynamic interactions. The generalized elastic model (GEM), which has been used to characterize numerous physical systems such as polymers, membranes, single-file systems, rough interfaces, and fluctuating surfaces, is a standard approach to studying the dynamics of elastic interfaces with nonlocal hydrodynamic interactions. The criticality and phase transition of the quenched generalized elastic model are investigated numerically and the results are presented in a phase diagram spanned by two tuning parameters. We demonstrate that in the one-dimensional disordered driven GEM, three qualitatively different behavior regimes are possible with a proper specification of the order parameter (mean velocity) for this system. In the vanishing order parameter regime, the steady-state order parameter approaches zero in the thermodynamic limit. A system with a nonzero mean velocity can be in either the continuous regime, which is characterized by a second-order phase transition, or the discontinuous regime, which is characterized by a first-order phase transition. The focus of this research is to investigate the critical scaling features near the pinning-depinning threshold. The behavior of the quenched generalized elastic model at the critical depinning force is explored. Near the depinning threshold, the critical exponent is obtained numerically.

Modeling and Analysis of Caputo–Fabrizio Definition-Based Fractional-Order Boost Converter with Inductive Loads

This paper proposes a modeling and analysis method for a Caputo–Fabrizio (C-F) definition-based fractional-order Boost converter with fractional-order inductive loads. The proposed method analyzes the system characteristics of a fractional-order circuit with three state variables. Firstly, this paper constructs a large signal model of a fractional-order Boost converter by taking advantage of the state space averaging method, providing accurate analytical solutions for the quiescent operating point and the ripple parameters of the circuit with three state variables. Secondly, this paper constructs a small signal model of the C-F definition-based fractional-order Boost converter by small signal linearization, providing the transfer function of the fractional-order system with three state variables. Finally, this paper conducts circuit-oriented simulation experiments where the steady-state parameters and the transfer function of the circuit are obtained, and then the effect of the order of capacitor, induced inductor, and load inductor on the quiescent operating point and ripple parameters is analyzed. The experimental results show that the simulation results are consistent with those obtained by the proposed mathematical model and that the three fractional orders in the fractional model with three state variables have a significant impact on the DC component and steady-state characteristics of the fractional-order Boost converter. In conclusion, the proposed mathematical model can more comprehensively analyze the system characteristics of the C-F definition-based fractional-order Boost converter with fractional-order inductive loads, benefiting the circuit design of Boost converters.

Predicting Model of Dual-Mode Shield Tunneling Parameters in Complex Ground Using Recurrent Neural Networks and Multiple Optimization Algorithms

Based on the left tunnel of the Liuxiandong Station to Baimang Station section of Shenzhen Metro Line 13 (China), a prediction model for the advanced rate of dual-mode shield tunneling in complex strata was established to explore intelligent tunneling technology in complex ground. Firstly, geological parameters of the complex strata and on-site monitoring parameters of EPB/TBM dual-mode shield tunneling were collected, with tunneling parameters, shield tunneling mode, and strata parameters selected as input features. Subsequently, the Isolation Forest algorithm was employed to remove outliers from the original advance parameters, and an improved mean filtering algorithm was applied to eliminate data noise, resulting in the steady-state phase parameters of the shield tunneling process. The base model was chosen as the Long-Short Term Memory (LSTM) recurrent neural network. During the model training process, particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), and Bayesian optimization (BO) algorithms were, respectively, combined to optimize the model’s hyperparameters. Via rank analysis based on evaluation metrics, the BO-LSTM model was found to have the shortest runtime and highest accuracy. Finally, the dropout algorithm and five-fold time series cross-validation were incorporated into the BO-LSTM model, creating a multi-algorithm-optimized recurrent neural network model for predicting tunneling speed. The results indicate that (1) the Isolation Forest algorithm can conveniently identify outliers while considering the relationship between tunneling speed and other parameters; (2) the improved mean filtering algorithm exhibits better denoising effects on cutterhead speed and tunneling speed; and (3) the multi-algorithm optimized LSTM model exhibits high prediction accuracy and operational efficiency under various geological parameters and different excavation modes. The minimum Mean Absolute Percentage Error (MAPE) prediction result is 8.3%, with an average MAPE prediction result below 15%.

Compatible co-administration of BioThrax® vaccine and ciprofloxacin—Results of a randomized open-label drug-vaccine interaction trial

The recommended treatment for post-exposure prophylaxis (PEP) following known/suspected exposure to Bacillus anthracis involves immunization with anthrax vaccine adsorbed (AVA, i.e., BioThrax® vaccine) and a course of antimicrobial therapy. A drug-vaccine interaction clinical trial was conducted to determine whether this combined treatment might modify antimicrobial exposure or vaccine immunogenicity.A Phase 2, randomized, open-label, multi-center trial involving 154 healthy adult participants was completed to evaluate the effect of AVA immunization (three doses administered subcutaneously (SC) at weeks 0, 2 and 4) on the pharmacokinetics (PK) of ciprofloxacin, as well as the effect of ciprofloxacin administration (500 mg po bid) on the immunogenicity of AVA. PK parameters were derived using noncompartmental analysis of ciprofloxacin serum concentrations. Immunogenicity was assessed using a toxin neutralizing antibody (TNA) assay resulting in 50 % neutralization factor (NF50) values. Safety was assessed via reports of adverse events (AEs), clinically significant changes in laboratory parameters and vital signs, and collection of solicited local and systemic reactogenicity reactions.Statistical analyses of the steady state (SS) and single dose PK parameters Cmax and AUC0-–12h indicated that the AVA PEP regimen did not significantly modify ciprofloxacin exposure. Comparison of the geometric mean TNA NF50 values between participants receiving AVA + ciprofloxacin and those receiving AVA alone showed that the combined treatment was non-inferior to AVA alone. The trial met all prospectively defined success criteria for the primary PK endpoint and for the secondary PK and immunogenicity endpoints. There were no deaths, SAEs or AEs leading to drug discontinuation or study withdrawal during the trial.Overall, concomitant administration of ciprofloxacin and AVA produced no significant changes in the PK profile of ciprofloxacin nor in the immunogenicity of AVA. Furthermore, this trial demonstrated that the co-administration of ciprofloxacin and AVA was well tolerated in healthy adult participants.

Truxene-to-Fluorenone Energy Transfer in a Robust Mesoporous Zn-MOF.

A new metal-organic framework (MOF; [Zn4O(hett)4/3(fluo)1/2(bdc)1/2]n; TFT-MOF) constructed on chromophoric ligands 5,5',10,10',15,15'-hexaethyltruxene-2,7,12-triacetate (hett), 9-fluorenone-2,7-dicarboxylate (fluo), terephthalate (bdc), and the Zn4O node has been prepared and identified by powder X-ray diffraction. This luminescent MOF exhibits large mesoporous pores of 2.7 nm based on computer modeling using density functional theory (DFT) calculations. The steady-state and time-resolved fluorescence spectra and photophysical parameters of TFT-MOF have been investigated and compared with those of the free ligands and their basic chromophores. All in all, TFT-MOF exhibits particularly efficient singlet-singlet energy-transfer processes described as 1(hett)* → (fluo) and 1(bdc)* → (fluo), leading to fluorescence arising for the fluo lumophore operating only through Förster resonance energy transfer (FRET) with an efficiency of transfer of up to >95%. This experimental conclusion was corroborated by DFT and time-dependent DFT (TDDFT). For the 1(hett)* → (fluo) process, the approximated overall rate constant of energy transfer was evaluated to be at most 2.04 × 1010 s-1 (using a Stern-Volmer approach of solution data and the relationship between distance and concentration). This process was analyzed using the Förster theory, where two intrapore energy transfer paths of center-to-center distances of 13 and 25 Å have been identified. TFT-MOF photosensitizes the formation of singlet oxygen (1O2 (1Σg)) as detected by its phosphorescence signal at 1275 nm.