On-off Strategy Research Articles

SERS detection of Hg2+ and aflatoxin B1 through on-off strategy of oxidase-like Au@HgNPs/carbon dots.

In this work, cerium-doped carbon dots (Ce-CDs) both as a reducing agent and template hybrid gold nanoparticles (AuNPs) with weak oxidase-like (OXD) activity was synthesized for the detection of Hg2+ and aflatoxin B1 (AFB1). The AuNPs can catalyze efficiently mercury ion (Hg2+) reduction to the metallic (Hg0) to form Au-Hg amalgam (Au@HgNPs). The obtained Au@HgNPs with strong OXD-like activity oxidize without Raman-active leucomalachite green (LMG) into the Raman-active malachite green (MG) and simultaneously as the SERS substrates by the formed Raman "hot spot" through MG-induced Au@HgNPs aggregation. While AFB1 was introduced resulting in the SERS intensity decreasing due to Hg2+ with AFB1 via carbonyl group to inhibit the aggregation of Au@HgNPs. The work paves a new path for the design of a nanozyme-based SERS protocol for tracing Hg2+ and AFB1 residues in foodstuff analysis.

A Physics-Based Modelling and Control of Greenhouse System Air Temperature Aided by IoT Technology

The need to reduce energy consumption in greenhouse production has grown. Thermal heating demand alone accounts for 80% of conventional greenhouse energy consumption; this significantly reduces production profit. Since microclimate affects crop metabolic processes and output, it is essential to monitor and control it to achieve both quantity and quality production with minimum energy consumption for maximum profit. The Internet of Things (IoT) is an evolving technology for monitoring and controlling environments that have recently been adopted to boost greenhouse efficiency in many applications by integrating hardware and software solutions; therefore, its adoption is thus critical in enabling greenhouse energy consumption minimisation. The first objective of this study is to improve and validate a greenhouse dynamic air temperature model required to simulate or predict indoor temperature. To achieve the first objective, therefore, an existing model was enhanced and a closed loop test experimental data from the IoT cloud-based control system platform deployed in the prototype greenhouse built in Cranfield University was used to validate the model using an optimisation-based model fitting approach. The second goal is to control the greenhouse air temperature in simulation using relatively simple PI and on-off control strategies to maintain the grower’s desired setpoint irrespective of the inevitable disturbances and to verify the potential of the controllers in minimising the total energy input to the greenhouse. For the second objective, the simulation results showed that the two controllers maintained the desired setpoint; however, the on-off strategy retained a sustainable oscillation, and the tuned PI effectively maintained the desired temperature, although the average energy used by the controllers is the same.

A frequency-dependent variable-damping control based variable-orifice damper for smart base-isolation system

Damping devices are commonly used in the isolation layer of base-isolated structures to provide additional damping to control the structural responses. Normally, large damping for the isolation layer is useful to minimize the resonance effect under low-frequency ground motions, and small damping is preferred to reduce the structural responses under high-frequency ground motions. Traditional passive dampers are widely adopted in engineering practice. Due to the fixed damping characteristic, however, the performance of base-isolated structures with passive dampers cannot stay optimal under ground motions with different frequency characteristics. To realize an optimal control of base-isolated structures, semi-active control has been increasingly valued for its efficiency and intelligence to adjust the damping characteristics based on feedback information from the structure and ground motion. However, a large number of sensors and hardware components are required for semi-active control, which makes the system complex and costly. In this paper, a variable-orifice damper (VOD) for smart base-isolation system is proposed. The VOD can adaptably adjust its damping according to the frequency of the ground motion without additional power or sensors. Theoretical analysis and sinusoidal excitation tests were carried out to investigate the behavior of VOD. A series of numerical simulations of a base‐isolated structure equipped with the proposed VOD and subjected to ground motions are also conducted. A semi-active control with ON-OFF strategy, and two passive controls (passive-on and passive-off) are conducted for comparison. The simulation results show that the VOD can result in an optimal control under ground motions with different frequency characteristics.

Demand response strategy applied to planning the operation of an air conditioning system. Application to a medical center

Large air conditioning systems, such as those used in shopping and health centers, typically demand high amounts of energy. Several air conditioning technologies and energy management strategies seek to minimize consumption to reduce billing expenses and improve system efficiency. This work proposes a demand response framework to plan the daily operation of an air conditioning system with the aim of minimizing the energy cost and guaranteeing thermal comfort. The framework includes an electrical-analogous thermal model, the formulation of the energy optimization problem with thermal and electrical constraints. The ISO 7730 standard is used to evaluate thermal comfort. The approach is applied to the air conditioning system of a radiotherapy and medical imaging center in Argentina. The optimization problem is solved through a genetic algorithm. To evaluate the strategy, two scenarios with different power demands are proposed: Case 1 (with demands lower than 300 kW) and Case 2 (with a peak demand greater than 300 kW). The results are compared with those obtained from an on-off strategy control with hysteresis. Penalties for large demands are avoided in Case 2, and therefore an economic saving of ≅ 16.8% is achieved. The thermal comfort is improved in both cases, with thermal cost reduction of 40.6% and 29.2% for Cases 1 and 2, respectively.

Adiponectin-targeted SERS immunoassay biosensing platform for early detection of gestational diabetes mellitus

The anisotropic gold nanotriangles (AuNTs) were synthesized by a fast seedless growth process. The high-yield monodispersed AuNT colloids were obtained through a purification process based on depletion-induced interactions. AuNTs were modulated with a localized surface plasmon resonance (LSPR) peak of 638 nm wavelength coherent with the Raman excitation light. However, from finite element computation results, the AuNT clusters showed better performance for the 785 nm laser source due to a red shift in their LSPR properties, hence it was selected for the surface-enhanced Raman scattering (SERS) immunoassay. A self-assembly strategy using a thiol group and ON-OFF strategy in the heat map was performed to ensure the stability of SERS immunoassay platform. The sandwich SERS immunoassay biosensor platform for adiponectin detection demonstrated a wide assay range (10–15–10–6 g/mL), good reliability (R2 = 0.994, clinically relevant range), femto-scale limit of detection (3.0 × 10–16 g/mL), and excellent selectivity without interference from other biomarkers. This showed the possibility of effectively detecting adiponectin levels in the biofluids of pregnant women. Therefore, our technology is the first to quantitatively detect adiponectin based on SERS technology for early detection of gestational diabetes mellitus and has the potential to be used as a clinical biosensor capable of diagnosing various obstetric diseases during early pregnancy.

Enhancing HSA-GCSFm fusion protein production by Pichia pastoris with an on-line model-based exponential and DO-stat control modes

HSA-GCSFm fusion protein production by recombinant Pichia. pastoris with traditional DO-stat or methanol ON-OFF feeding strategy often suffers problems such as a limited methanol consumption, severe intracellular methanol accumulation, low protein titer etc. To solve these questions, an on-line model-based exponential and DO-stat control modes by controlling the oscillation bandwidths of dissolved oxygen concentration (DO) at a narrower and stable level (~20%) was proposed. When using this strategy, 1) the accumulations of intracellular toxic methanol and formaldehyde were maintained at almost zero level by controlling DO at sufficient levels; 2) severe continuous oscillations in DO was effectively solved and thus methanol feeding/consumption rate could be increased from 0.0237-0.0281 g-MeOH/g-DCW/h to 0.0324 g-MeOH/g-DCW/h; 3) the lowest distribution of methanol to cells maintenance (0.0126 g-MeOH/g-DCW/h vs 0.0195 g-MeOH/g-DCW/h) was achieved and P. pastoris cells mortality decreased from 17.88% to 27.84–12.92% at the end of methanol induction phase; 4) the activities of the major enzymes involved in methanol metabolism, namely alcohol oxidase-AOX, formaldehyde dehydrogenase-FLD and formate dehydrogenase-FDH were largely activated; 5) maximum HSA-GCSFm concentration reached the highest level of 0.44 g/L, which was increased 46–238% compared to the control.

Assessing ventilation control strategies in underground parking garages

Enclosed parking garages require mechanical ventilation fans to dilute concentrations of pollutants emitted from vehicles, which contributes to energy use and peak electricity demand. This study develops and applies a simulation framework combining multi-zone airflow and contaminant transport modeling, fan affinity laws, and realistic assumptions for vehicle traffic patterns and carbon monoxide (CO) emissions to improve our ability to predict the impacts of various ventilation control strategies on indoor air quality and fan energy use in parking garages. The simulation approach is validated using measured data from a parking garage case study and then applied to investigate fan energy use, peak power demand, and resulting CO concentrations for four different ventilation control strategies in a model underground parking garage under a variety of assumptions for model inputs. The four ventilation control strategies evaluated include one simplistic schedule (i.e., Always-On) and three demand-based strategies in which fan speed is a function of CO concentrations in the spaces, including Linear-Demand Control Ventilation (DCV), Standardized Variable Flow (SVF), and a simple On-Off strategy. The estimated annual average fan energy consumption was consistently lowest with the Linear-DCV strategy, resulting in average (± standard deviation) energy savings across all modeled scenarios of 843%±0.4%, 72.8%±3.6%, and 97.9%±0.1% compared to SVF, On-Off, and Always-On strategies, respectively. The utility of the framework described herein is that it can be used to model energy and indoor air quality impacts of other parking garage configurations and control scenarios.

How and When to End the COVID-19 Lockdown: An Optimization Approach.

Countries around the world are in a state of lockdown to help limit the spread of SARS-CoV-2. However, as the number of new daily confirmed cases begins to decrease, governments must decide how to release their populations from quarantine as efficiently as possible without overwhelming their health services. We applied an optimal control framework to an adapted Susceptible-Exposure-Infection-Recovery (SEIR) model framework to investigate the efficacy of two potential lockdown release strategies, focusing on the UK population as a test case. To limit recurrent spread, we find that ending quarantine for the entire population simultaneously is a high-risk strategy, and that a gradual re-integration approach would be more reliable. Furthermore, to increase the number of people that can be first released, lockdown should not be ended until the number of new daily confirmed cases reaches a sufficiently low threshold. We model a gradual release strategy by allowing different fractions of those in lockdown to re-enter the working non-quarantined population. Mathematical optimization methods, combined with our adapted SEIR model, determine how to maximize those working while preventing the health service from being overwhelmed. The optimal strategy is broadly found to be to release approximately half the population 2–4 weeks from the end of an initial infection peak, then wait another 3–4 months to allow for a second peak before releasing everyone else. We also modeled an “on-off” strategy, of releasing everyone, but re-establishing lockdown if infections become too high. We conclude that the worst-case scenario of a gradual release is more manageable than the worst-case scenario of an on-off strategy, and caution against lockdown-release strategies based on a threshold-dependent on-off mechanism. The two quantities most critical in determining the optimal solution are transmission rate and the recovery rate, where the latter is defined as the fraction of infected people in any given day that then become classed as recovered. We suggest that the accurate identification of these values is of particular importance to the ongoing monitoring of the pandemic.

Electrochemical Synthesis of Carbodiimides via Metal/Oxidant-Free Oxidative Cross-Coupling of Amines and Isocyanides.

This work discloses an electrochemical oxidative cross-coupling of amines with aryl and aliphatic isocyanides. In an undivided cell, the reaction proceeds without involving any transition-metal catalyst, oxidant, or toxic reagents providing carbodiimides in good yields, thereby circumventing stoichiometric chemical oxidants, with H2 as the only byproduct. Moreover, carbodiimides were in situ converted into unsymmetrical ureas in moderate to good yields using an electricity ON-OFF strategy.

Displacement/velocity‐based control of a liquid spring—MR damper for vertical isolation

Seismic isolation is an effective technique used to mitigate effects of shaking and helps to achieve higher seismic performance. Recent researches have suggested that vertical excitation has significant effects on structures behavior during earthquake. In this study, three-dimensional (3D) isolation is proposed that combines an elastomeric bearing to resist horizontal ground shaking in series with a bilinear liquid spring (BLS)–controllable magnetorheological fluid damper (CMRD) to resist vertical shaking. A numerical model of a simplified rigid 2D block was developed to predict BLS-CMRD response under earthquake loading. The response of the BLS-CMRDs was simulated through a combination of nonlinear stiffness and viscous and hysteretic (semi-active) damping. A Disp/Vel-based control strategy was proposed that adjusts the input current according to the instantaneous vector combination of feedback displacement and velocity of the damper. Two variations of the control strategy were explored. First, with linear current variation, the current is activated when a threshold lower bound vector magnitude is reached, and maximum current is applied when threshold upper bound magnitude is exceeded. Second, the simplified ON–OFF strategy uses single threshold vector magnitude that triggers the maximum current to turn on when the instantaneous vector magnitude exceeds the threshold, and turn off otherwise. Results show that for ground motions that exceed the design level, Disp/Vel-based Control is effective to moderate the level of energy dissipation, keep the device vertical displacement within the design stroke limit, and attenuate vertical acceleration below PGA. In addition, Disp/Vel-based control reduces all responses relative to the well-known clipped optimal strategy used for structural control.

Fuel economy of hybrid electric flight

The present investigation addresses the problem of evaluating the endurance of hybrid electric aircraft and discusses the effect of battery specifications and the engine working points on fuel economy. In particular, the endurance per unit mass of fuel of a hybrid power system is calculated by assuming a constant power-level flight performed with alternate cycles of battery charging and discharging (ON-OFF strategy). The computation of the fuel economy requires accurate models for the time, the power and the energy associated with battery charging and discharge processes. In order to reach this goal, two approaches proposed in literature to evaluate electric endurance were discussed, amended and validated through comparison with experimental data. A model for constant-current/constant voltage battery charge was also presented and validated with literature experimental data. In order to explain how these models can be applied to real applications, a parallel hybrid power system was sized and analyzed for a medium-altitude long-endurance unmanned aerial vehicle. Lithium polymer batteries and two stroke diesel engines were considered and three different hybridization degrees were analyzed. The results showed a trade-off between electric flight time and overall endurance per unit mass of fuel and an improvement up to 12% in fuel consumption with respect to a non-hybrid case with the same engine.

Macro-assisted data-only carrier for 5G green cellular systems

As the commercial operation of 4G systems is speeding up worldwide to meet the increasingly explosive growth of mobile Internet in the 2020 era, a great many R&D efforts targeting the next generation wireless systems (5G) have been launched. With densely deployed small cells in a heterogeneous network, the excessive signaling overhead of conventional carrier design greatly degrades system performance. A new carrier designed for small cells in the next generation system will be highly beneficial toward a green communication network. In this article, we propose a macro-assisted data-only carrier for future 5G networks from a green prospective. With the help of macro base stations, control channel overhead, and cell-specific reference signals for small cells can be minimized to achieve a pure-data carrier. Under this architecture, key procedures are designed including small cell identification and access, synchronization, hand over, and small cell sleeping. Furthermore, to evaluate the potential of our proposed scheme, a complete system and link-level simulation platform according to the current 3GPP LTE standard is built. The simulation results show that our proposed systems, achieving significant performance enhancement of signaling overhead, can lead to more than 17 percent throughput improvement and 90 percent energy efficiency gain over the current LTE HetNet with on-off strategy implemented. The proposed scheme appears to be highly attractive as part of the future 5G green mobile networks.

A controllable on-off strategy for the reproductive containment of fish

A major impediment to the commercialization and cultivation of transgenic fish is the potential ecological risks they pose to natural environments: a problem that could be solved by the production of sterile transgenic fish. Here, we have developed an on-off reproductive containment strategy for fish that renders the offspring sterile but leaves their parents fertile. TG1 (Tol2-CMV-GFP-pA-CMV-gal4-pA-Tol2) and TG2 (Tol2-CMV-RFP-pA-5 × UAS-as/dnd-pA-Tol2) zebrafish lines were established using a GAL4/UAS system. While the parental lines remained fertile, in the hybrid offspring, GAL4 induced 5 × UAS to drive the transcription of antisense dnd, which significantly down-regulated endogenous dnd expression. This disrupted the migration of primordial germ cells (PGCs), led to their apoptosis, and resulted in few or no PGCs migrating to the genital ridge. This process induced sterility or reduced fertility in adult fish. This on-off strategy is a potentially effective means of generating sterile fish for commercialization while retaining fertility in brood stocks, and offers a novel method to mitigate the ecological risks of fish introductions.

Optimization of Watering for Minimizing the Inside Temperature of Zero Energy Cool Chamber for Storing Fruits and Vegetables

Abstract A zero energy cool chamber (ZECC) has been developed for storing fruits and vegetables from the viewpoints of low installation and operating cost. The inside temperature of the ZECC is cooled by adding water to a sand and zeolite based filler between the brick walls based on the principles of a natural evaporative cooling mechanism. The objective of this study was to minimize the inside temperature of the ZECC by controlling watering operation using an intelligent optimization technique combined with neural network and genetic algorithm. The objective function was given by the average value of the inside temperature for one day. For optimization, the control process (24 hours) was divided into 8 steps, and the optimal value (8-step ON-OFF intervals) of watering was obtained using neural networks and genetic algorithms. In this method, dynamic changes in the inside temperature of the ZECC, as affected by the watering strategy and outside temperature, were first identified using neural network, and then the optimal value, which minimized the objective function, was determined through simulation of the identified neural-network model using genetic algorithm. The average inside temperature for this optimal ON-OFF control was 5°C lower than that for the simple ON-OFF watering for 24 hours, and was also 8°C lower than that for no watering. The ZECC with the optimal ON-OFF watering strategy extended the shelf-life of untreated tomato from 7 to 16 days. Thus, it was concluded that a ZECC optimized by using neural networks and genetic algorithms is useful for storing tomato with no electric energy.

Driver Classification for Optimization of Energy Usage in a Vehicle

Real time monitoring of some key dynamical parameters of a vehicle provide critical information about the driving styles and expectations of vehicle drivers. Some of these key dynamical parameters include vehicle acceleration, braking, speeding index and throttle activity index. This paper presents a simple classifier that uses the estimated values of the above parameters to classify a driver into one of three categories, aggressive, moderate and conservative. The proposed classifier is computationally more efficient compared to other conventional classifiers, such as K-nearest neighbor algorithm, and hidden Markov model. Also, it filters the reference data set in an intelligent fashion. In a dual-power vehicle, such as a hybrid electric vehicle, this kind of classifier can be used to develop an optimum shift schedule, or an optimum engine on-off strategy, and estimate the available amount of regenerative energy.

Leaf-trait responses to irrigation of the endemic fog-oasis tree Myrcianthes ferreyrae: can a fog specialist benefit from regular watering?

Myrcianthes ferreyrae is an endemic, endangered species, with a small number of individuals located only in hyperarid, fog-oases known as lomas along the Peruvian desert in southern Peru, where fog is the main source of water. Following centuries of severe deforestation, reforestation with this native species was conducted in the Atiquipa lomas, Arequipa-Perú. On five slopes, five 2-year-old seedlings were irrigated monthly with water trapped by raschel-mesh fog collectors, supplementing natural rainfall with 0, 20, 40, 60 and 80 mm month(-1) from February to August 2008. We measured plant growth, increment in basal diameter, height and five leaf traits: leaf mass area (LMA), leaf carbon isotope composition (δ(13)C), nitrogen per leaf area, total leaf carbon and stomatal density; which are indicative of the physiological changes resulting from increased water supply. Plant growth rates, estimated from the variation of either shoot basal diameter or maximum height, were highly correlated with total biomass. Only LMA and δ(13)C were higher in irrigated than in control plants, but we found no further differences among irrigation treatments. This threshold response suggests an on-off strategy fitted to exploit pulses of fog water, which are always limited in magnitude in comparison with natural rain. The absence of a differential response to increased water supply is in agreement with the low phenotypic plasticity expected in plants from very stressful environments. Our results have practical implications for reforestation projects, since irrigating with 20 mm per month is sufficient to achieve the full growth capacity of this species.

A Novel ECMS and Combined Cost Map Approach for High-Efficiency Series Hybrid Electric Vehicles

The main aim in the control of a hybrid electric vehicle (HEV) is to decrease the fuel consumption and emissions without significant loss of driving performance. The performance of the vehicle in terms of fuel economy and emissions is very much dependent on the vehicle's supervisory control strategy. In this paper, the equivalent consumption minimization strategy (ECMS) is developed with a novel approach for the charge sustaining of the batteries to provide an overall improved optimization performance for series hybrid electric vehicles (SHEVs), considering the efficiencies of the internal combustion engine (ICE), generator, and battery. Another novelty is the development of a combined map, which simultaneously facilitates the optimization of the fuel consumption and multiple emission components, unlike most past studies that have concentrated on one component at a time. After the derivation of the cost map, the algorithm is divided into two main parts. The first part optimizes the engine-generator set (GENSET), and the second part determines how much power is needed from the GENSET according to the ECMS. The algorithm is implemented using generic emission and fuel consumption maps of an actual mid-sized series hybrid bus to reduce the desired emissions. The hybrid electric vehicle in consideration is converted from a conventional bus that is driven by an ICE. The performance of the novel ECMS strategy is compared with the conventional vehicle, as well as the SHEV version that is driven by an on-off strategy. In addition to reduced fuel consumption, the results of this paper demonstrate a significant reduction of 14.58% in CO2 production with ECMS, whereas the on-off control strategy achieves only 6.47% reduction over the conventional vehicle.

Throughput Scaling of Wireless Networks With Random Connections

This work studies the throughput scaling laws of ad hoc wireless networks in the limit of a large number of nodes. A random connections model is assumed in which the channel connections between the nodes are drawn independently from a common distribution. Transmitting nodes are subject to an on-off strategy, and receiving nodes employ conventional single-user decoding. The following results are proven: 1) for a class of connection models with finite mean and variance, the throughput scaling is upper-bounded by O(n1/3) for single-hop schemes, and O(n1/2) for two-hop (and multihop) schemes; 2) the Θ(n1/2) throughput scaling is achievable for a specific connection model by a two-hop opportunistic relaying scheme, which employs full, but only local channel state information (CSI) at the receivers, and partial CSI at the transmitters; 3) by relaxing the constraints of finite mean and variance of the connection model, linear throughput scaling Θ(n) is achievable with Pareto-type fading models.

Integration mechanisms of transgenes and population fitness of GH transgenic fish

It has been more than 20 years since the first batch of transgenic fish was produced. Five stable germ-line transmitted growth hormone (GH) transgenic fish lines have been generated. This paper reviews the mechanisms of integration and gene targeting of the transgene, as well as the viability, reproduction and transgenic approaches for the reproductive containment of GH-transgenic fish. Further, we propose that it should be necessary to do the following studies, in particularly, of the breeding of transgenic fish: to assess the fitness of transgenic fish in an aqueous environment with a large space and a complex structure; and to develop a controllable on-off strategy of reproduction in transgenic fish.

Hierarchical control of vehicular fuel cell / battery hybrid powertrain

In a proton exchange membrane (PEM) fuel cell/battery hybrid vehicle, a fuel cell system fulfills the stationary power demand, and a traction battery provides the accelerating power and recycles braking energy. The entire system is coordinated by a distributed control system, incorporating three key strategies: 1) vehicle control, 2) fuel cell control and 3) battery management. They make up a hierarchical control system. This paper introduces a hierarchical control strategy for a fuel cell / battery hybrid powertrain applied in a city bus. The vehicle control strategy comprises three parts: an energy management strategy, a brake regeneration strategy and an active tolerant control strategy. The entire powertrain power is split between the fuel cell system and the battery in such a way that the fuel cell system works in a quasi-steady state and the battery can keep charge sustaining. The braking energy is recycled on the basis of the pedal position and the rotational speed of the electric motor. An active tolerance control strategy is developed to guarantee the work of the entire system in case of malfunctions. A fuel cell system consists of a water and heat management system, an air system, a humidifier system and a hydrogen in-out let system. Control strategies are designed to regulate air supply and water cooling temperature. Primary tasks of a battery management system are to estimate the state of charge (SOC), and to keep the temperature in safety range. A real-time applicable strategy for SOC is developed. The temperature of the battery is controlled by some air fans with on-off strategy. The hierarchical control system was applied on a fuel cell city bus. Experimental results show the effectiveness of the proposed strategy.