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This research investigated the impacts of model prediction on the optimization of hybrid energy systems using a system consisting of solar panels, batteries, a proton exchange membrane fuel cell (PEMFC), and a chemical hydrogen generation system. A PEMFC has several advantages, such as low operating temperatures, fast response times, high power density, and environmental friendliness, and it can convert hydrogen into electricity. However, because hydrogen costs are an important consideration, the PEMFC is usually integrated with hybrid energy systems to guarantee system sustainability. Therefore, in this study, a whole-year household load and solar radiation data were applied to optimize the system components and power management, thereby reducing the system cost by 42.43% and improving system sustainability by 7.05%. The system responses showed that some hydrogen consumption might be saved if the solar and load profiles could be foreseen. Two prediction models were developed that could accurately forecast the radiation and load profiles. Next, a second-year dataset was employed to verify the effectiveness of the model prediction. The results showed that the system cost was reduced by 40.20% without model prediction and by 44.06% with model prediction compared to the original system settings. Finally, experiments to illustrate the feasibility of the hybrid energy system were conducted using prediction models. Based on the results, the model prediction was deemed effective in improving the performance of hybrid energy systems. [ABSTRACT FROM AUTHOR]

This paper proposes a multiple switching control method for a long-stroke precision stage to improve its performance. The stage consists of a motor stage with a travel of 10 cm and a piezoelectric transducer (PZT) stage with a resolution of 1 nm, which allows a simultaneously large travel length and precision positioning. The developed switching algorithms can select the optimal control sequence that minimizes the system cost by predicting of the future responses. We obtain the stage models through experiments. For the PZT stage, we design two robust loop-shaping controllers: the fast controller provides rapid transient responses and the smooth controller give smooth responses. We then derive corresponding robust proportional–integral-derivative controllers and develop a control switching mechanism that can simultaneously accomplish fast and smooth responses. The switching mechanism predicts future system responses by all possible control sequences and selects the optimal one to minimize specified costs. For the motor stage, we apply gain scheduling control, where the gain adjustment is larger than previously because the PZT stage can quickly compensate for the position errors of the combined stage. The designed control structures are then implemented for simulation and experimental verification. The results indicate that the proposed control is effective in improving system responses. [ABSTRACT FROM AUTHOR]

This paper develops an automatic control switching mechanism for a long-stroke precision stage intended to improve micro-lens fabrication. The stage consists of a piezoelectric transducer (PZT) stage and a motor stage that achieves centimeter-length travel distances with nanometer precision. We obtained the PZT stage model by experiments and then applied robust loop-shaping techniques to design two controllers: one gave fast responses and the other gave smooth responses. The two controllers were further simplified as robust proportional-integral-derivative (PID) controllers for hardware implementation. We then developed a control switching mechanism, based on model response prediction, to combine the merits of these two controllers. For the motor stage, we derived the stage model by experiments and designed a gain-scheduling controller that regulated the stage to move at the fastest speed for long travel distances until it was within the stroke of the PZT stage. The two stages were then combined with a double-loop control structure to provide a travel range of 10 cm with a precision of 1.23 nm. We implemented the designed control mechanisms and structures for experimental verification. The combined stage was also integrated with a two-photon polymerization (TPP) system to fabricate micro-lenses. The optical properties of the micro-lenses were evaluated to demonstrate the effectiveness of the proposed control in precision positioning for long travel distances. [ABSTRACT FROM AUTHOR]

This paper investigates the benefits of distributed hybrid power systems employing multiple fuel-cell vehicles. In earlier work, our optimization of hybrid power systems showed that a single fuel cell acting as backup power to guarantee energy sustainability operates for less than 3% of the time but incurs more than 16% of the system costs. Therefore, the system cost could be reduced when applying a fuel-cell vehicle to dynamically support twelve power stations. Here, we extend this idea by employing multiple fuel-cell vehicles to support more power stations. We develop a power management strategy and optimize the management parameters by the genetic algorithm. The results show a reduction of more than 21% by applying multiple fuel-cell vehicles in the distributed systems. Experiments also confirm the feasibility of using multiple fuel-cell vehicles. Based on the results, the proposed systems are deemed effective for reducing system costs while maintaining system sustainability. [Display omitted] • We develop distributed hybrid power systems employing multiple FCVs. • We propose the power management strategies to schedule the FCVs. • The genetic algorithm is applied to optimize the management parameters. • The system costs were reduced by more than 21% when sharing multiple FCVs. • Experiments confirm the feasibility of using multiple FCVs. [ABSTRACT FROM AUTHOR]

This paper investigates the benefits of sharing a proton exchange membrane fuel cell (PEMFC) in a distributed hybrid power system. The PEMFC is usually used as backup power in stationary hybrid power systems; however, in that scenario, it might be working only 2% of the time while incurring 20% of the system expenses. Therefore, this paper examines the potential of sharing a PEMFC among multiple power systems. We develop a distributed hybrid power system that comprises several immovable power stations and a fuel-cell vehicle (FCV). Each power station is equipped with solar panels and batteries, while the FCV contains a PEMFC module and can move among the stations to provide sustainable power as needed. We propose power management strategies and show that the total system costs can be significantly reduced by 10.83% and 17.89% when sharing one FCV between three and twelve power stations, respectively. We also design experiments to demonstrate the feasibility of the proposed distributed hybrid power system. In the future, the developed model can be extended to provide further cost reductions by optimizing distributed hybrid power systems with multiple FCVs. Image 1 • We develop a distributed hybrid power system. • The system consists of several immovable power stations and a fuel-cell vehicle. • The fuel-cell vehicle can provide sustainable power to different stations. • A simulation model shows that sharing the PEMFC can reduce system costs. • Experiments demonstrate the feasibility of the distributed hybrid power system. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal design procedure for a green building equipped with renewable energy, energy storages, and proton exchange membrane fuel cells (PEMFCs). First, we introduce the hybrid power system of the green building and construct a simulation model using Matlab/SimPowerSystem™. The model parameters are tuned so that the system responses can be estimated without extensive experiments in the optimization processes. Second, we define the cost and reliability indexes to optimize the system design using three steps: component selection, component sizing, and power management (PM) adjustment. We further define the safety index to evaluate the system's sustainability under extreme conditions when no renewable energy is available. Last, we apply the proposed procedures to the green building and demonstrate the benefits of the optimal design. The proposed method can be directly applied to develop customized hybrid power systems in the future. [ABSTRACT FROM AUTHOR]

This paper describes the development of a hybrid Proton Exchange Membrane Fuel Cell (PEMFC) electric vehicle consisting of a 3 kW PEMFC, PV arrays, secondary battery sets, and a chemical hydrogen generation system. We first integrate a hybrid PEMFC electric vehicle and design power management strategies. The on-board hydrogen generation system can provide sufficient hydrogen for continuous operation of the PEMFC, and the performance tests demonstrate the effectiveness of the integrated system in providing sustainable power for driving. We then use Matlab/SimPowerSystem™ to develop a simulation model and adjust the model parameters using experimental data. The results indicated that the model can effectively predict system responses and can be used for performance evaluation. We also use the simulation model to estimate the mileage and costs of the developed electric vehicle, and we discuss the impacts of component sizes on system costs and travelling ranges. [ABSTRACT FROM AUTHOR]

This paper develops a hybrid power model that can be used to optimize customized systems. We build the hybrid model in Matlab/SimPowerSystem™, which consists of a proton exchange membrane fuel cell, a Li–Fe secondary battery set, photovoltaic (PV) arrays, and a chemical hydrogen production system. Based on experimental data, we adjust the model parameters and show that the simulation model can correctly predict the experimental responses, with a root-mean-square error of 0.6% in state-of-charge. Therefore, we can apply the model to optimize the design of customized power systems. We consider three load profiles: the lab, the department office, and the household, and modify the sizes of the PV arrays and battery capacities to optimize the system cost for each load. In addition, we analyze the impacts of power management on the system cost. The findings indicate that the developed hybrid power model is effective at estimating system responses, and can significantly reduce the time and cost for developing customized power systems. [ABSTRACT FROM AUTHOR]

This paper develops an on-demand hydrogen generation system, which can produce hydrogen from sodium borohydride (NaBH 4 ) solution, to operate proton exchange membrane fuel cell (PEMFC). We first build the hydrogen generation system, which hydrolyzes NaBH 4 in a batch reactor to provide a continuous supply of hydrogen to drive the PEMFC. We also discuss the impacts of solution concentration and batch volume. In addition, we develop a simulation model that evaluates the hydrogen generation and temperature responses of the system. Furthermore, we design a control strategy to adjust the batch intervals of NaBH 4 solution according to the PEMFC loads. We then implement the designed control on a microcontroller and integrate it with a PEMFC for experimental verification. The results confirm that the developed on-demand hydrogen generation system can hydrolyze NaBH 4 with a conversion rate of more than 90% so that it to continuously supplies hydrogen to drive a 3 kW PEMFC. [ABSTRACT FROM AUTHOR]

This paper proposes the use of inverse disturbance response decoupling (DRD) for an optical table to suppress vibration in precision machinery. Optical tables are normally adopted in precision engineering to repress two vibration sources: ground disturbances from the environment and load disturbances from machines. The suspension settings for restraining these disturbances are conflicting; therefore, in previous studies, we developed a DRD structure that could independently control the disturbance responses: using soft passive elements to isolate the ground disturbances and improving the load responses by active control. This paper extends these ideas by proposing an inverse DRD structure that uses stiff passive elements to suppress load disturbances and improve ground responses by active control employing robust loop shaping techniques. The designed inverse DRD structure and controllers are implemented and verified by experiments. Based on the results, the proposed inverse DRD structure and robust control are deemed effective in improving the performance of an optical table. [ABSTRACT FROM AUTHOR]

This paper applies a newly developed mechatronic inerter network to suppress vibrations of a full optical table. Optical tables are normally applied to insulate precision machines from two types of disturbances: ground disturbances from the environment and load disturbances from the equipment. These two disturbances can be independently controlled by disturbance response decoupling (DRD) techniques. For example, we can isolate the ground disturbances by soft passive suspensions and improve the load responses by active control. However, the passive elements cannot be easily adjusted according to the operating conditions. Therefore, this paper applies mechatronic inerter networks to a full optical table, and optimizes the ground responses by connecting the networks to suitable electric circuits. We then apply DRD techniques to improve the load responses without influencing the ground responses. The designed mechatronic inerter networks and active controllers are implemented to a full optical table for experimental verification. Based on the results, the proposed mechatronic inerter networks and DRD structures are deemed effective in improving system responses. [ABSTRACT FROM AUTHOR]

This paper discusses the impacts of different power management strategies on a fuel-cell vehicle. The study was carried out in three steps: fuel-cell control, power management, and system integration and verification. First, we identified the models of a proton exchange membrane fuel-cell (PEMFC) and designed robust controllers to improve the PEMFC's performance and efficiency. Second, we developed two power management structures—a serial power train and a parallel power train—which consisted of the PEMFC and secondary batteries to provide sustainable power for an electric mobility scooter. Lastly, we used the scooter's driving cycles to compare the performance and efficiency of these two power trains. Then we implemented the power trains on a microprocessor for road test. Based on the results, both power trains are deemed effective in providing continuous power for driving the scooter. In addition, the serial power train, although it uses an extra battery set, is shown to be more efficient than the parallel one. [ABSTRACT FROM AUTHOR]

This paper proposes robust loop-shaping techniques for a two-axis nano-positioning piezoelectric stage. Piezoelectric transducers are usually used to drive precision mechanisms because of their favorable properties, such as high resolution, high accuracy, and large driving force. However, the nonlinear characteristics of piezoelectric materials can degrade system performance. Therefore, we model a piezoelectric stage as a linear system, and regard its nonlinear factors as system uncertainties. Because robust control can guarantee stability and performance for systems with uncertainties and disturbances, we apply loop-shaping techniques and design standard robust controllers for the stage. In addition, we consider fixed-order robust control for the system in that controllers with lower orders are preferred for hardware implementation. Lastly, the designed controllers are implemented for experimental verification. The results demonstrate the effectiveness of these robust controllers in tracking reference signals and suppressing high-frequency vibrations. [ABSTRACT FROM PUBLISHER]

Abstract: This paper develops an exchangeable fuel-cell power module that is replaceable on different light electric vehicles (LEVs). The module consists of a proton exchange membrane fuel-cell (PEMFC) and two battery sets, which provide continuous power for LEVs. The study includes three topics: fuel-cell control, power management, and system modularization and vehicle integration. First, we design robust controllers for the PEMFC to provide a steady voltage or current for charging the battery sets. Second, we develop a serial power train that can provide continuous power for driving the vehicle motors. Third, we modularize a power system that can be easily implemented on different LEVs. We build the system on Matlab™ SimPowerSystem for simulation before road tests, and integrate the power module onto a mobility car and an electric motorbike for experimental verification. Based on the results, the proposed systems are deemed effective. [Copyright &y& Elsevier]

In this paper we propose the design and control of a novel two-layer optical table. An optical table normally needs to isolate two main vibration sources: the ground disturbances and the load disturbances. Because the suspension settings for suppressing these two disturbances conflict with each other, we applied disturbance response decoupling (DRD) techniques to treat them independently. First, we used passive elements to insulate the ground disturbances. Second, we employed DRD methods to design active robust controllers that would drive piezoelectric transducers to improve the load responses without influencing the ground responses. Finally, the designed controllers were implemented for experimental verification. The DRD theorem and robust controllers were confirmed to be effective at suppressing system vibrations. [ABSTRACT FROM AUTHOR]

Balance control, a complex sensorimotor skill, declines with age. Assessing balance is crucial for identifying fall risk and implementing interventions in the older population. This study aimed to measure age-dependent changes in static and dynamic balance using inertial measurement units in a clinical setting. This study included 82 healthy participants aged 20–85 years. For the dynamic balance test, participants stood on a horizontally swaying balance board. For the static balance test, they stood on one leg. Inertial measurement units attached to their bodies recorded kinematic data, with average absolute angular velocities assessing balance capabilities. In the dynamic test, the younger participants had smaller average absolute angular velocities in most body parts than those of the middle-aged and older groups, with no significant differences between the middle-aged and older groups. Conversely, in the single-leg stance tests, the young and middle-aged groups outperformed the older group, with no significant differences between the young and middle-aged groups. Thus, dynamic and static balance decline at different stages with age. These results highlight the complementary role of inertial measurement unit-based evaluation in understanding the effect of age on postural control mechanisms, offering valuable insights for tailoring rehabilitation protocols in clinical settings. [ABSTRACT FROM AUTHOR]

Abstract: This paper develops robust control and power management strategies for a 6 kW stationary proton exchange membrane fuel cell (PEMFC) hybrid power system. The system consists of two 3 kW PEMFC modules, a Li–Fe battery set, and electrical components to form a parallel hybrid power system that is designed to supply uninterruptible power to telecom base stations during power outages. The study comprises three parts: PEMFC control, power management, and system integration. First, we apply robust control to regulate the hydrogen flow rates of the PEMFC modules in order to improve system stability, performance, and efficiency. Second, we design a parallel power train that consists of two PEMFC modules and one Li–Fe battery set for the uninterruptible power supply (UPS) requirement. Lastly, we integrate the system for experimental verification. Based on the results, the proposed robust control and power management are deemed effective at improving the stability, performance, and efficiency of the stationary power system. [Copyright &y& Elsevier]

This paper discusses the use of inerters to improve the stability and performance of a full-train system. First, we construct a 28 degree-of-freedom train model in AutoSim, and obtain a linearised model for analysis in Matlab. Then, the benefits of inerters are investigated by the critical speed, settling time and passenger comfort. In addition, we apply a new mechatronic network for further performance improvement, and synthesise the optimal electrical circuit for experimental verification. From the results, inerters are shown to be effective in improving the stability and performance of train systems. [ABSTRACT FROM AUTHOR]

This paper applies a novel mechatronic network strut to vehicle suspensions and discusses the benefits of system performance. The proposed mechatronic strut consists of a ball-screw inerter and permanent magnet electric machinery, such that the system impedance can be realised through a combination of mechanical and electrical networks. Applying the mechatronic strut to vehicle suspensions, we evaluate the improvement of system performance using passive electrical networks. Furthermore, a prototype mechatronic strut is constructed for properties verification. Finally, nonlinearities of the mechatronic strut are taken into account to modify the suspension design. From the simulation and experimental results, the proposed mechatronic network strut is shown to be effective. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes robust proportional-integral-derivative (PID) control for a proton exchange membrane fuel cell (PEMFC) system. We model a PEMFC as a multivariable system, and apply identification techniques to obtain the system’s transfer function matrices, where system variations and disturbances are regarded as uncertainties. Because robust control can cope with system uncertainties and disturbances, it has been successfully applied to improve the stability, performance, and efficiency of PEMFC systems in previous studies. However, the resulting robust controllers might be too complicated for hardware implementation. On the other hand, PID control has been widely applicable to engineering practices because of its simple structure, but it lacks stability analysis for systems with uncertainties. Therefore, by combining the merits of robust control and PID control, we design robust PID controllers for the PEMFC system. Based on evaluation of stability, performance, and efficiencies, the proposed robust PID controllers are shown to be effective. [ABSTRACT FROM AUTHOR]

Abstract: This paper applies fixed-order multivariable robust control strategies to a proton exchange membrane fuel cell (PEMFC) system, and implements the designed controllers on a microchip for system miniaturization. In previous studies, robust control was applied to guarantee system stability and to reduce hydrogen consumption for a PEMFC system. It was noted that for standard robust control design, the order of resulting controllers is dictated by the plants and weighting functions. However, for hardware implementation, controllers with lower orders are preferable in terms of computing efforts and cost. Therefore, in this paper the PEMFC is modeled as multivariable transfer matrices, then three fixed-order robust control algorithms are applied to design controllers with specified orders for a PEMFC. Finally, the designed controllers are implemented on a microchip to regulate the air and hydrogen flow rates. From the experimental results, fixed-order robust control is deemed effective in supplying steady power and reducing fuel consumption. [Copyright &y& Elsevier]

Abstract: This paper applies multivariable robust control strategies to a proton exchange membrane fuel cell (PEMFC) system. From the system point of view, a PEMFC can be modeled as a two-input-two-output system, where the inputs are air and hydrogen flow rates and the outputs are cell voltage and current. By fixing the output resistance, we aimed to control the cell voltage output by regulating the air and hydrogen flow rates. Due to the nonlinear characteristics of this system, multivariable robust controllers were designed to provide robust performance and to reduce the hydrogen consumption of this system. The study was carried out in three parts. Firstly, the PEMFC system was modeled as multivariable transfer function matrices using identification techniques, with the un-modeled dynamics treated as system uncertainties and disturbances. Secondly, robust control algorithms were utilized to design multivariable H ∞ controllers to deal with system uncertainty and performance requirements. Finally, the designed robust controllers were implemented to control the air and hydrogen flow rates. From the experimental results, multivariable robust control is shown to provide steady output responses and significantly reduce hydrogen consumption. [Copyright &y& Elsevier]

Abstract: This paper proposes a systematic method of system identification and control of a proton exchange membrane (PEM) fuel cell. This fuel cell can be used for low-power communication devices involving complex electrochemical reactions of nonlinear and time-varying dynamic properties. From a system point of view, the dynamic model of PEM fuel cell is reduced to a configuration of two inputs, hydrogen and air flow rates, and two outputs, cell voltage and current. The corresponding transfer functions describe linearized subsystem dynamics with finite orders and time-varying parameters, which are expressed as discrete-time auto-regression moving-average with auxiliary input models for system identification by the recursive least square algorithm. In the experiments, a pseudo-random binary sequence of hydrogen or air flow rate is fed to a single fuel cell device to excite its dynamics. By measuring the corresponding output signals, each subsystem transfer function of reduced order is identified, while the unmodeled, higher-order dynamics and disturbances are described by the auxiliary input term. This provides a basis of adaptive control strategy to improve the fuel cell performance in terms of efficiency, as well as transient and steady state specifications. Simulation shows that adaptive controller is robust to the variation of fuel cell system dynamics, and it has proved promising from the experimental results. [Copyright &y& Elsevier]

Abstract: This paper will discuss the application of system identification techniques and robust control strategies to a proton exchange membrane fuel-cell system. The fuel-cell system''s dynamic behaviour is influenced by many factors, such as the reaction mechanism, pressure, flow-rate, composition and temperature change, and is inherently non-linear and time varying. From a system point of view, however, the system can be modelled as a two-input, two-output linear time-invariant system whose inputs are hydrogen and air flow rates, and whose outputs are cell voltage and current. On the other hand, the system''s non-linearities and time-varying characteristics can be regarded as system uncertainties and disturbances that are treated by the designed robust controllers. This paper is comprised of three parts. First, system identification techniques were adopted to model the system''s transfer functions. Second, the H ∞ robust control strategies were applied to stabilise the system. Finally, the system''s stability and performance were compromised by introducing weighting functions to the controller''s design. From the experimental results, the designed H ∞ robust controllers were deemed effective. [Copyright &y& Elsevier]

This paper derives a structural condition on the controller for a given (stable) plant which guarantees that some prespecified closed-loop transfer function is the same as in the open loop. We also present conditions to test whether the achievable dynamic response of other transmission paths remains effectively the same if the controller is so restricted. The results are applied to simple quarter- and half-car vehicle models, and illustrated numerically for a double-wishbone halfcar model. [ABSTRACT FROM AUTHOR]

Features a proposal for a tunneling field-effect transistor (FET). Device structure and operating principle; Modeling; Scaling properties.

This paper develops Deep Neural Network (DNN) models that can recognize stroke gaits. Stroke patients usually suffer from partial disability and develop abnormal gaits that can vary widely and need targeted treatments. Evaluation of gait patterns is crucial for clinical experts to make decisions about the medication and rehabilitation strategies for the stroke patients. However, the evaluation is often subjective, and different clinicians might have different diagnoses of stroke gait patterns. In addition, some patients may present with mixed neurological gaits. Therefore, we apply artificial intelligence techniques to detect stroke gaits and to classify abnormal gait patterns. First, we collect clinical gait data from eight stroke patients and seven healthy subjects. We then apply these data to develop DNN models that can detect stroke gaits. Finally, we classify four common gait abnormalities seen in stroke patients. The developed models achieve an average accuracy of 99.35% in detecting the stroke gaits and an average accuracy of 97.31% in classifying the gait abnormality. Based on the results, the developed DNN models could help therapists or physicians to diagnose different abnormal gaits and to apply suitable rehabilitation strategies for stroke patients. [ABSTRACT FROM AUTHOR]

This paper demonstrates the development of an automatic mobile trainer employing inertial movement units (IMUs). The device is inspired by Neuro-Developmental Treatment (NDT), which is an effective rehabilitation method for stroke patients that promotes the relearning of motor skills by repeated training. However, traditional NDT training is very labor intensive and time consuming for therapists, thus, stroke patients usually cannot receive sufficient rehabilitation training. Therefore, we developed a mobile assisted device that can automatically repeat the therapists' intervention and help increase patient training time. The proposed mobile trainer, which allows the users to move at their preferred speeds, consists of three systems: the gait detection system, the motor control system, and the movable mechanism. The gait detection system applies IMUs to detect the user's gait events and triggers the motor control system accordingly. The motor control system receives the triggering signals and imitates the therapist's intervention patterns by robust control. The movable mechanism integrates these first two systems to form a mobile gait-training device. Finally, we conducted preliminary tests and defined two performance indexes to evaluate the effectiveness of the proposed trainer. Based on the results, the mobile trainer is deemed successful at improving the testing subjects' walking ability. [ABSTRACT FROM AUTHOR]

• Chalcone analogues containing a thieno[2,3- d ]pyrimidin-2-yl group were synthesized and evaluated as anti-tumor agents. • Compound 8d was the most potent analogue, with IC 50 values ranging between 2.65 and 11.44 μM in seven cancer cell lines. • Compound 8d induced an accumulation of HCT-116 cells in the sub-G1 phase. • 8d -induced apoptosis was confirmed by Annexin-V, JC-1, H2DCFDA and MitoSox™ Red staining assays. • The mitochondrial death pathway might be involved in 8d -induced apoptosis in HCT-116 cells. Many natural or synthetic chalcones have potential anti-tumor activity. Here, we synthesized two series of chalcone analogues containing a thieno[2,3- d ]pyrimidin-2-yl group and evaluated for their cytotoxic activity towards cultured human lung cancer A549 and colorectal HCT-116 cells. Among them, compound 8d was the most cytotoxic against HCT-116 cells, with an IC 50 value of 2.65 μM. Analyses of the phenotypic changes induced by this compound found a dose-dependent accumulation of HCT-116 cells in sub-G1 phase, indicating that compound 8d might induce apoptosis. Furthermore, we found that 8d triggered mitochondrial membrane potential depolarization, promoted reactive oxygen species formation in HCT-116 cells, and increased the percentage of early and late apoptotic cells. Finally, immunoblotting indicated that 8d increased PARP-1 and caspases 3, 7 and 9 cleavage. These data suggest that compound 8d induces apoptosis via the mitochondrial death pathway. [ABSTRACT FROM AUTHOR]

• The world's first machine-vision-based method for valve leakage measurement. • The method satisfies the global standards for valve leakage inspection. • Intensity responses were normalized and applied to detect bubbles. • A user interface was designed to quickly check the testing information. • The proposed system can reduce the workload by two-thirds for valve inspection. Valve leakage is a serious safety issue in petroleum and petrochemical production processes. Traditional valve manufacturers examine valve leakage by manual visual inspection, but this method is inefficient and prone to errors. Hence, this paper applies machine vision techniques to develop a measurement method that can detect valve leakage according to the global standards of the petroleum industry, such as those recommended by the American Petroleum Institute. A collection device and machine vision techniques were applied to count leaked bubbles. The results were then compared with traditional human visual counting. The proposed machine vision method can achieve a mean absolute error of less than 1% while also reducing two-thirds of the workload of traditional human visual counting. Experimental results confirmed the effectiveness of this method. This study is the first to adapt machine-vision technology to industrial valve leakage measurement and opens up new possibilities for further exploration of valve leakage. [ABSTRACT FROM AUTHOR]

The mechanism of the negative persistent photoconductivity (NPPC) in InAs/AlSb single quantum wells is discussed. The molecular beam epitaxy grown single InAs quantum well sample is made into Hall bars with the substrate as the backgate. Using the newly designed buffer, the gate bias can deplete or enhance the two-dimensional electrons in the InAs quantum well without substantial gate leakage current. Based on the 4.2 K magnetoresistance data, and the fact that the trapped electrons can be redistributed by gate bias, we conclude that the NPPC effect at low temperatures is a result of the capture of photoexcited electrons by ordinary, deep donors in AlSb. Numerical modeling using physical assumptions can quantitatively explain our experimental observation, and the calculated AlSb donor energy is 0.41±0.05 eV above the AlSb valence band maximum, with 4×1016/cm3 to 1017/cm3 in concentration. The previously discussed DX-center-like characteristic of deep levels in AlSb, i.e., lattice-relaxation with a relatively high activation energy, is not evidenced in this work. © 1996 American Institute of Physics. [ABSTRACT FROM AUTHOR]

We have investigated the transport properties of a field-effect transistor (FET) with a composite quantum well, which consists of two adjacent semiconductor quantum wells, GaSb and InAs, sandwiched by AlSb barriers. This FET shows a novel V-shaped transfer characteristic, which is a direct result of the switching between electron and hole channels. [ABSTRACT FROM AUTHOR]

This paper discusses the optimization of hybrid power systems, which consist of solar cells, wind turbines, fuel cells, hydrogen electrolysis, chemical hydrogen generation, and batteries. Because hybrid power systems have multiple energy sources and utilize different types of storage, we first developed a general hybrid power model using the Matlab/SimPowerSystemTM, and then tuned model parameters based on the experimental results. This model was subsequently applied to predict the responses of four different hybrid power systems for three typical loads, without conducting individual experiments. Furthermore, cost and reliability indexes were defined to evaluate system performance and to derive optimal system layouts. Finally, the impacts of hydrogen costs on system optimization was discussed. In the future, the developed method could be applied to design customized hybrid power systems. [ABSTRACT FROM AUTHOR]

Silicon carbide (SiC) nanowires were synthesized using lignin-phenolic resin (LPR) and silicon powder as raw materials. The morphology and structures of the nanowires were characterized by scanning electron microscopy, transmission electron microscopy and X-ray diffraction. The influence of reaction conditions on the growth of the nanowires was investigated by thermodynamic analysis. It was revealed that the growth of the nanowires starts at around 1100 °C by a vapor–liquid–solid (VLS) mechanism and the growth temperature is lower than that for the formation of SiC nanowires from commercial phenolic resin and silicon powder. The nanowires have diameters of 30–100 nm and lengths of several microns. It was revealed that the inorganic salts are formed in-situ from LPR in the lignin segment as liquid catalyst droplets during pyrolysis. These dissolve SiC and become supersaturated, from which SiC nanowires grow along the [1 1 1] direction by the stacking of (1 1 1) planes. [New Carbon Materials 2015, 30(3): 222–229] [ABSTRACT FROM AUTHOR]

As human–robot interaction becomes more prevalent in industrial and clinical settings, detecting changes in human posture has become increasingly crucial. While recognizing human actions has been extensively studied, the transition between different postures or movements has been largely overlooked. This study explores using two deep-learning methods, the linear Feedforward Neural Network (FNN) and Long Short-Term Memory (LSTM), to detect changes in human posture among three different movements: standing, walking, and sitting. To explore the possibility of rapid posture-change detection upon human intention, the authors introduced transition stages as distinct features for the identification. During the experiment, the subject wore an inertial measurement unit (IMU) on their right leg to measure joint parameters. The measurement data were used to train the two machine learning networks, and their performances were tested. This study also examined the effect of the sampling rates on the LSTM network. The results indicate that both methods achieved high detection accuracies. Still, the LSTM model outperformed the FNN in terms of speed and accuracy, achieving 91% and 95% accuracy for data sampled at 25 Hz and 100 Hz, respectively. Additionally, the network trained for one test subject was able to detect posture changes in other subjects, demonstrating the feasibility of personalized or generalized deep learning models for detecting human intentions. The accuracies for posture transition time and identification at a sampling rate of 100 Hz were 0.17 s and 94.44%, respectively. In summary, this study achieved some good outcomes and laid a crucial foundation for the engineering application of digital twins, exoskeletons, and human intention control. [ABSTRACT FROM AUTHOR]

The gait pattern of exoskeleton control conflicting with the human operator's (the pilot) intention may cause awkward maneuvering or even injury. Therefore, it has been the focus of many studies to help decide the proper gait operation. However, the timing for the recognization plays a crucial role in the operation. The delayed detection of the pilot's intent can be equally undesirable to the exoskeleton operation. Instead of recognizing the motion, this study examines the possibility of identifying the transition between gaits to achieve in-time detection. This study used the data from IMU sensors for future mobile applications. Furthermore, we tested using two machine learning networks: a linearfFeedforward neural network and a long short-term memory network. The gait data are from five subjects for training and testing. The study results show that: 1. The network can successfully separate the transition period from the motion periods. 2. The detection of gait change from walking to sitting can be as fast as 0.17 s, which is adequate for future control applications. However, detecting the transition from standing to walking can take as long as 1.2 s. 3. This study also find that the network trained for one person can also detect movement changes for different persons without deteriorating the performance. [ABSTRACT FROM AUTHOR]

This paper investigates the clinical efficacy of an automatic mobile trainer for gait training in stroke patients. Neuro-Developmental Treatment (NDT) is a rehabilitation method for stroke patients that enhances motor learning through repeated practice. Despite the proven effectiveness of therapist-assisted NDT, it is labor-intensive and demands health resources. Therefore, we developed automatic trainers based on NDT principles to perform gait training. This paper modifies the mobile trainer's intervention patterns to improve the subject's longitudinal gait symmetry, lateral pelvic displacement symmetry, and pelvic rotation. We first invited ten healthy subjects to test the modified trainer and then recruited 26 stroke patients to undergo the same gait training. Longitudinal symmetry, lateral symmetry, and pelvic rotation were assessed before, during, and after the intervention. Most subjects show improvements in longitudinal symmetry, lateral symmetry, and pelvic rotation after using the trainer. These results confirm the trainer's effectiveness of the modified intervention schemes in helping clinical gait rehabilitation for stroke patients. [ABSTRACT FROM AUTHOR]

This study investigates gait symmetry and single-leg stance balance of professional yoga instructors versus age-matched typically developed controls using inertial measurement unit (IMU)-based evaluation. We recruited twenty-five yoga instructors and twenty-five healthy control subjects to conduct the walking experiments and single-leg stance tests. Kinematic data were measured by attaching IMUs to the lower limbs and trunk. We assessed the asymmetry of swing phases during the normal-walk and tandem-walk tests with eyes open and closed, respectively. The subjects subsequently conducted four single-leg stance tests, including a single-leg stance on both legs with eyes open and closed. Two balance indexes regarding the angular velocities of the waist and chest were defined to assess postural stability. The gait asymmetry indexes of yoga instructors were significantly lower than those of the typically developed controls. Similarly, the yoga instructors had better body balance in all four single-leg stance tests. This study's findings suggest that yoga improves gait asymmetry and balance ability in healthy adults. In the future, further intervention studies could be conducted to confirm the effect of yoga training. [ABSTRACT FROM AUTHOR]

This paper describes the development of a stationary hybrid power system consisting of a 3 kW proton exchange membrane fuel cell (PEMFC) module, a battery set, and solar cells. We design PEMFC control and power managements for the hybrid system, and construct a simulation model based on experimental data. The simulation model is then used to analyze performance and efficiency of the system, employing different power management strategies. The study comprises three parts: PEMFC control, power management, and the simulation model. First, we apply robust control to regulate the PEMFC temperature and current, and achieve root mean square errors of 0.06 °C and 0.07 A, respectively. Second, we integrate the hybrid power system and design power management strategies for sustainable operation. Third, we develop a Matlab™ SimPowerSystem model based on experimental data. The simulation results are shown to match the experiments with a deviation of 0.21%. Last, we apply the simulation model to discuss the impacts of different power management strategies on system efficiency. Based on the results, the designed controllers and power management strategies are deemed effective at improving system performance and efficiency. In addition, the developed simulation model can be applied in the future to develop customized hybrid power system. [ABSTRACT FROM AUTHOR]

Spatial information analysis has gained increasing attention in recent years due to its wide range of applications, from disaster prevention and human behavioral patterns to commercial value. This study proposes a novel application to help businesses identify optimal locations for new stores. Optimal store locations are close to other stores with similar customer groups. However, they are also a suitable distance from stores that might represent competition. The style of a new store also exerts a significant effect. In this paper, we utilized check-in data and user profiles from location-based social networks to calculate the degree of influence of each store in a road network on the query user to identify optimal new store locations. As calculating the degree of influence of every store in a road network is time-consuming, we added two accelerating algorithms to the proposed baseline. The experiment results verified the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

Abstract: Nonlinearity and the time-varying dynamics of fuel cell systems make it complex to design a controller for improving output performance. This paper introduces an application of a model reference adaptive control to a low-power proton exchange membrane (PEM) fuel cell system, which consists of three main components: a fuel cell stack, an air pump to supply air, and a solenoid valve to adjust hydrogen flow. From the system perspective, the dynamic model of the PEM fuel cell stack can be expressed as a multivariable configuration of two inputs, hydrogen and air-flow rates, and two outputs, cell voltage and current. The corresponding transfer functions can be identified off-line to describe the linearized dynamics with a finite order at a certain operating point, and are written in a discrete-time auto-regressive moving-average model for on-line estimation of parameters. This provides a strategy of regulating the voltage and current of the fuel cell by adaptively adjusting the flow rates of air and hydrogen. Experiments show that the proposed adaptive controller is robust to the variation of fuel cell system dynamics and power request. Additionally, it helps decrease fuel consumption and relieves the DC/DC converter in regulating the fluctuating cell voltage. [Copyright &y& Elsevier]

Nerve sheath ganglion is a relatively rare clinical entity commonly found in the peroneal nerve in the lower limb or the ulnar nerve in the upper extremity. It is rarely found in the tibial nerve. The occurrence of a nerve sheath ganglion in a patient's tibial nerve has been identified. The initial presentation of the tumor mass has been very similar to that of a Baker's cyst, namely a soft undulating popliteal mass. Yet, the case also presented symptoms and signs of tibial nerve compressive neuropathy. We present here a rare case of nerve sheath ganglion of the tibial nerve. Clinical courses of the patient were reviewed, and relevant issues were discussed with a thorough literature review. [ABSTRACT FROM AUTHOR]

This note addresses the high-speed, high-precision point-to-point motion control of an air-bearing planar stage. The custom-designed stage uses four air-bearings to levitate the stage for the high-speed frictionless operation. Because of the floating nature, the controller for the system needs to overcome the nonlinear free-moving dynamics of the stage and achieve the required performance. To fulfill this purpose, we propose a unique integrated control structure that allows both velocity and reference position inputs. With the proposed structure and the weighting design, it is possible to use the H ∞ chain scattering description (H ∞ -CSD) synthesis for the control parameters. The single structure is used for both the point-to-point movement and the high precision positioning. The reference velocity input enables the long-stroke time-optimal velocity profile injection. The controller converges to the popular PDF control when the stage comes close to the target position. The H ∞ specifications enable a robust performance against the load uncertainty. The control undergoes no switching and is thus free from the undesirable chattering. The experimental results show that the proposed control achieves an ultrahigh precision control of 20 nm within 200 ms for a 9-kg stage with 20-mm x , y motion ranges. • Fast point-to-point motion control of a free-floating dual-axis air-bearing stage. • A control design algorithm that fits into the commercial servo control structure while achieving the robust H ∞ -control criteria. • The control structure achieves a unified architecture for a smooth transaction from point-to-point motion to the precision positioning control. • For the 9-kg stage with a ± 200 mm travel, the research achieved ± 20 nm of position resolution. [ABSTRACT FROM AUTHOR]

This note addresses the transient behavior of the different point-to-point motion control strategies. The transition between the high-speed velocity control and the high-precision position feedback often leads to undesirable overshoot and residual oscillation. This study first introduces the use of an integrated H∞-chain scattering description (CSD) synthesized controller for a unified point-to-point motion to a high-precision positioning control without switching. This study then compares the control effects with the s-curve trajectory control and an augmented Luenberger observer (ALO)-based control. The s-curve control is a position-dependent implementation and has to be converted into a time-domain trajectory for practical implementation. It is desirable to examine if the trajectory error would accumulate into a large overshoot. The ALO uses an auxiliary system to suppress the thrust ripple but is slower compared with the acceleration-based H∞-CSD and s-curve control. It is interesting to see that the H∞-CSD controller automatically reaches a similar performance as the s-curve trajectory. Both the s-curve and the H∞-CSD control algorithms achieve access time in the range of 200 ms for a 10-mm travel. It is also interesting to notice that the time-domain error for the s-curve trajectory does not accumulate, and the overshoot is < 0.08%. As a comparison, the access time for the integrated H∞-CSD controller is 195 ms with an overshoot of 0.097%, and the access time for the s-curve trajectory control is 212 ms with an overshoot of 0.016%. [ABSTRACT FROM AUTHOR]

Abstract The chalcone motif can be found in many molecules that contribute to essential biological processes, and many chalcone-containing compounds exhibit potent anti-cancer activity. Here, we synthesized two series of chalcone analogues (3a−s and 6a−s) based on substituting the chalcone B-ring or A-ring with a 4-oxoquinazolin-2-yl group, and then evaluated them for cytotoxic activity in human colorectal HCT-116 and breast cancer MCF-7 cell lines. Compounds 3a−s (in which a 4-oxoquinazolin-2-yl group functioned as the B-ring) were markedly more cytotoxic than compounds 6a−s (in which 4-oxoquinazolin-2-yl group functioned as the A-ring), based on their IC 50 values to inhibit proliferation. Compound 3f was found as the most potent among 38 analogues and the mechanism of its cytotoxicity was investigated. Flow cytometry indicated that HCT-116 cells treated with compound 3f resulted in a dose-dependent accumulation of cells in the sub-G1 phase, which is representative of apoptotic cells. Subsequent assays (including Annexin V-FITC/PI, AO-EB, MitoSOX™ Red and JC-1 staining) confirmed that 3f exposure induced apoptosis in HCT-116 cells. Immunoblotting analysis indicated that cellular exposure to 3f increased the cleavage of PARP1 and caspases 3, 7, and 9. Taken together, this novel chalcone analogue has a cytotoxic effect on cultured cancer cell-lines that is likely mediated by inducing apoptosis via the mitochondrial death pathway. Graphical abstract Image 1 Highlights • Two series of chalcone analogues containing a 4-oxoquinazolin-2-yl group were synthesized. • Compound 3f is the most cytotoxic one with IC 50 s of 3.56 and 4.08 μM in HCT-116 and MCF-7 cells. • HCT-116 cells treated with 3f accumulated in the sub-G1 phase of the cell cycle. • 3f -induced apoptosis was confirmed by Annexin V, AO-EB, MitoSOX™ Red and JC-1 staining assays. • 3f increased the levels of cleaved PARP1, caspases 3, 7 and 9, activating the mitochondrial death pathway. [ABSTRACT FROM AUTHOR]

Two series of thieno[2,3- d ]pyrimidine derivatives bearing a dithiocarbamate side chain at the C2 position were synthesized and evaluated for cytotoxic activity in human lung cancer A549 and colon cancer HCT-116 cell lines. Compound 3n exhibited the most cytotoxic effect on A549 cells with an IC 50 value of 4.87 μM, inducing a cell cycle arrest at G2/M phase and activating the spindle assembly checkpoint (SAC). To identify the target protein(s) of 3n , we incorporated biotin with 3n through a three-carbon chain and an amide bond to synthesize probe 10 . The targeted proteins were pulled down from the A549 total cell lysate by biotin-streptavidin affinity purification and analyzed by mass spectrometry. Tubulin was the only protein identified, which is related to the SAC and directly binds to probe 10 both in vivo and in vitro . Furthermore, compound 3n inhibited tubulin polymerization in vitro in a dose-dependent manner, competed with taxol in binding to tubulin, exerting cytotoxic activity toward taxol-resistant A549 cells. These results demonstrate that thieno[2,3- d ]pyrimidine derivative 3n exhibits cytotoxicity in cancer cells by targeting tubulin to activate the SAC and potentially acts as a therapeutic lead compound for taxol-resistant cancers. [ABSTRACT FROM AUTHOR]

We fabricated vertical standing carbon nanosheets (CNSs) on various substrates by a radio-frequency sputter system. This 3D nanomaterial demonstrated the benefits of a large surface area and laminated nanostructure for heat dissipation in high-power light emitting diodes (LEDs). Experimental measurements of thermal resistance from the CNS assembly confirmed the enhancement of heat transfer. The efficiency of heat transfer depends on the spacing density per unit area of the CNS array and the ambient pressure. Optimizing in the CNS density gives a large surface area with good porosity that enhances the air molecules exchanging heat in high efficiency. In addition, an extra coating on the CNS can further improve the efficiency of thermal conductivity and the best performance discovered in this work was a decrease in thermal resistance of over 18%. A model based on one-dimensional heat conduction was proposed which solving the system's heat conductivity and heat transfer coefficient. Such model explains the reasons for thermal resistance deduction of different CNS densities and coatings. We therefore tested the use of CNSs as heat sinks for high-power LEDs, which suffer from declining light power output and shifts in the output wavelength when temperatures rise. When assisted by cooling from the CNS, the enhancement of light output and a 3.7 nm wavelength shift were achieved. [ABSTRACT FROM AUTHOR]

We discuss the observation, analysis, and results of the first-year science operation of AMiBA, an interferometric experiment designed to study cosmology via the measurement of Cosmic Microwave Background (CMB). In 2007, we successfully observed 6 galaxy clusters (z < 0.33) through the Sunyaev-Zel'dovich effect. AMiBA is the first CMB interferometer operating at 86–102 GHz, currently with 7 close-packed antennas of 60 cm in diameter giving a synthesized resolution of around 6 arcminutes. An observing strategy with on-off-source modulation is used to remove the effects from electronic offset and ground pickup. Formalism of the analysis is given and preliminary science results are summarized. Tests for systematic effects are also addressed. We also discuss the expansion plan. [ABSTRACT FROM AUTHOR]