Functional and Kinetic Comparison of Alanine Cysteine Serine Transporters ASCT1 and ASCT2

Neutral amino acid transporters ASCT1 and ASCT2 are two SLC1 (solute carrier 1) family subtypes, which are specific for neutral amino acids. The other members of the SLC1 family are acidic amino acid transporters (EAATs 1–5). While the functional similarities and differences between the EAATs have been well studied, less is known about how the subtypes ASCT1 and 2 differ in kinetics and function. Here, by performing comprehensive electrophysiological analysis, we identified similarities and differences between these subtypes, as well as novel functional properties, such as apparent substrate affinities of the inward-facing conformation (in the range of 70 μM for L-serine as the substrate). Key findings were: ASCT1 has a higher apparent affinity for Na+, as well as a larger [Na+] dependence of substrate affinity compared to ASCT2. However, the general sequential Na+/substrate binding mechanism with at least one Na+ binding first, followed by amino acid substrate, followed by at least one more Na+ ion, appears to be conserved between the two subtypes. In addition, the first Na+ binding step, presumably to the Na3 site, occurs with high apparent affinity (<1 mM) in both transporters. In addition, ASCT1 and 2 show different substrate selectivities, where ASCT1 does not respond to extracellular glutamine. Finally, in both transporters, we measured rapid, capacitive charge movements upon application and removal of amino acid, due to rearrangement of the translocation equilibrium. This charge movement decays rapidly, with a time constant of 4–5 ms and recovers with a time constant in the 15 ms range after substrate removal. This places a lower limit on the turnover rate of amino acid exchange by these two transporters of 60–80 s−1.

Optimal System for Improved Internal Model Control of Argon-Oxygen Decarburization Process Based on the Piecewise Linear Model and Time Constant of Filter Optimization

This paper presents an improved internal model control system to raise the efficiency of refining low-carbon ferrochrome. This control system comprises of a piecewise linearized transfer function and an improved internal model controller based on optimized time constant of the filter. The control system is mainly used to control the oxygen supply rate during the argon-oxygen refining for controlling the smelting temperature. The regulatory performance and servo of two closed-loop control schemes are compared between the improved internal model controller based on the optimized filter time 0000-0002-7606-6546and the internal model controller based on the fixed filter time constant. The simulation analysis shows that the piecewise linearized model and the optimization of the time constant of the filter improves the response time, stability, and anti-interference ability of the controller. Then, the proposed improved internal model controller is used to adjust the gas supply flow in 5 ton AOD furnace to control the smelting temperature. Ten production tests performed the effectiveness of the controlling refining optimal system. The analysis of the experimental data shows that the improved internal model control system can shorten the melting time and improve the melting efficiency. Thus, the application of the improved internal model control system in low-carbon ferrochrome refining is an interesting potential direction for future research.

Cascade position- torque control strategy based on function approximation technique (FAT) for flexible joint robots

This work deals with control of rigid link robotic manipulators provided with flexible joints. Due to presence of flexible joint dynamics, additional degrees of freedom and underactuation are developed that would complicate the control design. Besides, model uncertainties, unmodeled dynamics and disturbances should be considered in robot modeling and control. Therefore, this paper proposes a cascade position-torque control strategy based on function approximation technique (FAT). The key idea is to design two nested loops: 1) an outer position control loop for tracking reference trajectory, and 2) an inner joint torque control loop to track the desired joint torque resulted from the outer position loop. The torque control loop makes the robot system more adaptable and compliant for sudden disturbances. It increases the perception capability for the target robot mechanisms. Adaptive approximation control (AAC) is used as a strong tool for dealing with time-varying uncertain parameters and disturbances. A sliding mode term is easily integrated with control law structure; however, a constraint on feedback gains are established for compensating modeling (approximation) error. The proposed control architecture can be easily used for high degrees of freedom robotic system due to the decentralized behavior of the AAC. A two-link manipulator is used for simulation experiments.The simulated robot is commanded to move from rest to desired step references considering three cases depending on the selected value of the sliding mode time constant. It is shown that selection of a large time constant parameter related to the position loop leads to slow response. Besides, one of the inherent issues associated with the inner torque control is the presence of derivative of desired joint torque that makes the input control abruptly jumping at the beginning of the dynamic response. To end this, an approximation for derivative term of the desired joint torque is established using a low-pass filter with a time constant selected carefully such that a feasible dynamic response is ensured.The results show the effectiveness of the proposed controller.

Cascade position- torque control strategy based on function approximation technique (FAT) for flexible joint robots

This work deals with control of rigid link robotic manipulators provided with flexible joints. Due to presence of flexible joint dynamics, additional degrees of freedom and underactuation are developed that would complicate the control design. Besides, model uncertainties, unmodeled dynamics and disturbances should be considered in robot modeling and control. Therefore, this paper proposes a cascade position-torque control strategy based on function approximation technique (FAT). The key idea is to design two nested loops: 1) an outer position control loop for tracking reference trajectory, and 2) an inner joint torque control loop to track the desired joint torque resulted from the outer position loop. The torque control loop makes the robot system more adaptable and compliant for sudden disturbances. It increases the perception capability for the target robot mechanisms. Adaptive approximation control (AAC) is used as a strong tool for dealing with time-varying uncertain parameters and disturbances. A sliding mode term is easily integrated with control law structure; however, a constraint on feedback gains are established for compensating modeling (approximation) error. The proposed control architecture can be easily used for high degrees of freedom robotic system due to the decentralized behavior of the AAC. A two-link manipulator is used for simulation experiments.The simulated robot is commanded to move from rest to desired step references considering three cases depending on the selected value of the sliding mode time constant. It is shown that selection of a large time constant parameter related to the position loop leads to slow response. Besides, one of the inherent issues associated with the inner torque control is the presence of derivative of desired joint torque that makes the input control abruptly jumping at the beginning of the dynamic response. To end this, an approximation for derivative term of the desired joint torque is established using a low-pass filter with a time constant selected carefully such that a feasible dynamic response is ensured.The results show the effectiveness of the proposed controller.

Trabecular Meshwork Motion Profile from Pulsatile Pressure Transients: A New Platform to Simulate Transitory Responses in Humans and Nonhuman Primates

Trabecular meshwork (TM) motion abnormality is the leading cause of glaucoma. With technique limitations, how TM moves is still an enigma. This study describes a new laboratory platform to investigate TM motion responses to ocular transients in ex vivo eyes. The anterior segments of human cadaver and primate eyes were mounted in a perfusion system fitting. Perfusion needles were placed to establish mean baseline pressure. A perfusion pump was connected to the posterior chamber and generated an immediate transient pressure elevation. A phase-sensitive optical coherent tomography system imaged and quantified the TM motion. The peak-to-peak TM displacements (ppTMD) were determined, a tissue relaxation curve derived, and a time constant obtained. This study showed that the ppTMD increased with a rise in the pulse amplitude. The ppTMD was highest for the lowest mean pressure of 16 mmHg and decreased with mean pressure increase. The pulse frequency did not significantly change ppTMD. With a fixed pulse amplitude, an increase in mean pressure significantly reduced the time constant of recoil from maximum distension. Our research platform permitted quantitation of TM motion responses to designed pulse transients. Our findings may improve the interpretation of new TM motion measurements in clinic, aiding in understanding mechanisms and management.

Bi-exponential modelling of $$W^{^{\prime}}$$ reconstitution kinetics in trained cyclists

Purpose The aim of this study was to investigate the individual $$W^{^{\prime}}$$ W ′ reconstitution kinetics of trained cyclists following repeated bouts of incremental ramp exercise, and to determine an optimal mathematical model to describe $$W^{^{\prime}}$$ W ′ reconstitution. Methods Ten trained cyclists (age 41 ± 10 years; mass 73.4 ± 9.9 kg; $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max 58.6 ± 7.1 mL kg min−1) completed three incremental ramps (20 W min−1) to the limit of tolerance with varying recovery durations (15–360 s) on 5–9 occasions. $$W^{^{\prime}}$$ W ′ reconstitution was measured following the first and second recovery periods against which mono-exponential and bi-exponential models were compared with adjusted R2 and bias-corrected Akaike information criterion (AICc). Results A bi-exponential model outperformed the mono-exponential model of $$W^{^{\prime}}$$ W ′ reconstitution (AICc 30.2 versus 72.2), fitting group mean data well (adjR2 = 0.999) for the first recovery when optimised with parameters of fast component (FC) amplitude = 50.67%; slow component (SC) amplitude = 49.33%; time constant (τ)FC = 21.5 s; τSC = 388 s. Following the second recovery, W′ reconstitution reduced by 9.1 ± 7.3%, at 180 s and 8.2 ± 9.8% at 240 s resulting in an increase in the modelled τSC to 716 s with τFC unchanged. Individual bi-exponential models also fit well (adjR2 = 0.978 ± 0.017) with large individual parameter variations (FC amplitude 47.7 ± 17.8%; first recovery: (τ)FC = 22.0 ± 11.8 s; (τ)SC = 377 ± 100 s; second recovery: (τ)FC = 16.3.0 ± 6.6 s; (τ)SC = 549 ± 226 s). Conclusions W′ reconstitution kinetics were best described by a bi-exponential model consisting of distinct fast and slow phases. The amplitudes of the FC and SC remained unchanged with repeated bouts, with a slowing of W′ reconstitution confined to an increase in the time constant of the slow component.

Using mathematical models to evaluate germination rate and seedlings length of chickpea seed (Cicer arietinum L.) to osmotic stress at cardinal temperatures

Cicer arietinum is the 3rd most important cool season legume crop growing in vast arid and semi-arid regions of the world. A lab experiment was designed using hydrothermal time model (HTT) to investigate the chickpea seed germination (SG) behavior, cardinal temperatures and germination responses across fluctuating temperatures (Ts) and water potentials (Ψs). Seeds of chickpea var. NIFA 1995 were germinated at six constant Ts (7, 14, 21, 28, 35 and 42°C) each having the following five water potentials: 0, -0.2, -0.4–0.6 and -0.8 MPa. Germination percentage (G%) decreased significantly at (*P ≤ 0.05) from 86.7% at 28°C in -0.2 MPa to 10% in -0.2 MPa at 7°C. The germination rate (GR = 1/t50) against different T percentiles exhibited that linear increase was observed in the GR pattern above and below the To. Based on the confidence intervals of the model coefficients and (R2: 0.96), the average cardinal temperatures were 4.7, 23 and 44.2°C for the base (Tb), optimal (To) and ceiling (Tc) temperatures respectively. θT1 value was observed maximum at 28°C in -0.2 MPa and decreases with decreasing Ψ (-0.8 MPa). In comparison with control, the θT2 value was also highest in -0.2 MPa at 28°C. The thermal time (TT) concept is well fitted to germination fraction data in distilled water with an R2 value increasing 0.972. The hydro time constant (θH) increased with an increase in T to To and then decreased when T>To. The ѱb(50) irregularly varied with increasing T, σΨb was also recorded lowest (0.166 MPa) at 28°C and highest (0.457 MPa) at 7°C. Based on the statistical analysis, cardinal temperatures, hydrothermal time constant (θHTT) and germination findings the HTT gives an insight into the interactive effect of T and Ψ on seed germination time courses under varying environmental conditions.

An ultra-compact leaky integrate-and-fire neuron with long and tunable time constant utilizing pseudo resistors for spiking neural networks

Spiking neural networks (SNNs) inspired by biological neurons enable a more realistic mimicry of the human brain. To realize SNNs similar to large-scale biological networks, neuron circuits with high area efficiency are essential. In this paper, we propose a compact leaky integrate-and-fire (LIF) neuron circuit with a long and tunable time constant, which consists of a capacitor and two pseudo resistors (PRs). The prototype chip was fabricated with TSMC 65 nm CMOS technology, and it occupies a die area of 1392 m2. The fabricated LIF neuron has a power consumption of 6 W and a leak time constant of up to 1.2 ms (the resistance of PR is up to 600 MΩ). In addition, the time constants are tunable by changing the bias voltage of PRs. Overall, this proposed neuron circuit facilitates the very-large-scale integration (VLSI) of adaptive SNNs, which is crucial for the implementation of bio-scale brain-inspired computing.

The mathematics of the reproduction number R for Covid-19: A primer for demographers

The reproduction number R is a key indicator used to monitor the dynamics of Covid-19 and to assess the effects of infection control strategies that frequently have high social and economic costs. Despite having an analog in demography’s “net reproduction rate” that has been routinely computed for a century, demographers may not be familiar with the concept and measurement of R in the context of Covid-19. This article is intended to be a primer for understanding and estimating R in demography. We show that R can be estimated as a ratio between the numbers of new cases today divided by the weighted average of cases in previous days. We present two alternative derivations for these weights based on how risks have changed over time: constant vs. exponential decay. We then provide estimates of these weights, and demonstrate their use in calculating R to trace the course of the first pandemic year in 53 countries.