The role of channel height and actuation method on particle manipulation in surface acoustic wave (SAW)-driven microfluidic devices

Surface acoustic wave (SAW) micromanipulation offers modularity, easy integration into microfluidic devices and a high degree of flexibility. A major challenge for acoustic manipulation, however, is the existence of a lower limit on the minimum particle size that can be manipulated. As particle size reduces, the drag force resulting from acoustic streaming dominates over acoustic radiation forces; reducing this threshold is key to manipulating smaller specimens. To address this, we investigate a novel excitation configuration based on diffractive-acoustic SAW (DASAW) actuation and demonstrate a reduction in the critical minimum particle size which can be manipulated. DASAW exploits the inherent diffractive effects arising from a limited transducer area in a microchannel, requiring only a travelling SAW (TSAW) to generate time-averaged pressure gradients. We show that these acoustic fields focus particles at the channel walls, and further compare this excitation mode with more typical standing SAW (SSAW) actuation. Compared to SSAW, DASAW reduces acoustic streaming effects whilst generating a comparable pressure field. The result of these factors is a critical particle size with DASAW (1 $$\upmu$$ μ m) that is significantly smaller than that for SSAW actuation (1.85 $$\upmu$$ μ m), for polystyrene particles and a given $$\lambda _{\text {SAW}}$$ λ SAW = 200 $$\upmu$$ μ m. We further find that streaming magnitude can be tuned in a DASAW system by changing the channel height, noting optimum channel heights for particle collection as a function of the fluid wavelength at which streaming velocities are minimised in both DASAW and SSAW devices.

Polarization-Insensitive Beam Splitter with Variable Split Angles and Ratios Based on Phase Gradient Metasurfaces

The beam splitter is a common and critical element in optical systems. Traditional beam splitters composed of prisms or wave plates are difficult to be applied to miniaturized optical systems because they are bulky and heavy. The realization of the nanoscale beam splitter with a flexible function has attracted much attention from researchers. Here, we proposed a polarization-insensitive beam splitter with a variable split angle and ratio based on the phase gradient metasurface, which is composed of two types of nanorod arrays with opposite phase gradients. Different split angles are achieved by changing the magnitude of the phase gradient based on the principle of Snell’s law of refraction, and different split ratios are achieved by adding a phase buffer with different areas. In the designed four types of beam splitters for different functions, the split angle is variable in the range of 12–29°, and the split ratio is variable in the range of 0.1–1. The beam splitter has a high beam splitting efficiency above 0.3 at the wavelength of 480–600 nm and a weak polarization dependence. The proposed beam splitter has the advantages of a small size and easy integration, and it can be applied to various optical systems such as multiplexers and interferometers for integrated optical circuits.

Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution

Current Internet of Things (IoT) stacks are frequently focused on handling an increasing volume of data that require a sophisticated interpretation through analytics to improve decision making and thus generate business value. In this paper, a cognitive IoT architecture based on FIWARE IoT principles is presented. The architecture incorporates a new cognitive component that enables the incorporation of intelligent services to the FIWARE framework, allowing to modernize IoT infrastructures with Artificial Intelligence (AI) technologies. This allows to extend the effective life of the legacy system, using existing assets and reducing costs. Using the architecture, a cognitive service capable of predicting with high accuracy the vessel port arrival is developed and integrated in a legacy sea traffic management solution. The cognitive service uses automatic identification system (AIS) and maritime oceanographic data to predict time of arrival of ships. The validation has been carried out using the port of Valencia. The results indicate that the incorporation of AI into the legacy system allows to predict the arrival time with higher accuracy, thus improving the efficiency of port operations. Moreover, the architecture is generic, allowing an easy integration of the cognitive services in other domains.

Optical Fiber Sensors for Monitoring Railway Infrastructures: A Review towards Smart Concept

Railway infrastructures have played a critical role to ensure the continuity of goods and passenger transportation in China. Under extreme loading and environmental conditions, railway structures are vulnerable to deterioration and failure, leading to the interruption of the whole transportation system. Several techniques have been used for the health monitoring of railway structures. Optical fiber sensors are the widely recognized technique due to their inherent advantages such as high sensitivity, anti-electromagnetic interference, light weight, tiny size, corrosion resistance, and easy integration and network configuration. This paper provides a state-of-the-art of optical fiber sensing technologies and their practical application in railway infrastructures. In addition, the strain transfer analysis of optical fiber sensors is described for parameter reflection. A smart concept for artificial intelligence contribution is also declared. Finally, existing and future prospects on smart concept-based optical fiber sensors for railway infrastructure are discussed. The study can provide useful guidance to understand the problems in artificial intelligence which contributed to the Structural Health Monitoring system of railway structures.

Modular Model Composition for Rapid Implementations of Embedded Economic Model Predictive Control in Microgrids

Economic model predictive control in microgrids combined with dynamic pricing of grid electricity is a promising technique to make the power system more flexible. However, to date, each individual microgrid requires major efforts for the mathematical modelling, the implementation on embedded devices, and the qualification of the control. In this work, a field-suitable generalised linear microgrid model is presented. This scalable model is instantiated on field-typical hardware and in a modular way, so that a class of various microgrids can be easily controlled. This significantly reduces the modelling effort during commissioning, decreases the necessary qualification of commissioning staff, and allows for the easy integration of additional microgrid devices during operation. An exemplary model, derived from an existing production facility microgrid, is instantiated, and the characteristics of the results are analysed.

Designing Virtual Reality Environments through an Authoring System Based on CAD Floor Plans: A Methodology and Case Study Applied to Electric Power Substations for Supervision

The adoption of Virtual Reality (RV) technologies in prototype design and process revision has contributed to multiple industry areas. Nonetheless, the development of VR systems for engineering is a complex task, as it involves specialized teams handling low-level code development. Given these problems, the goal of this study is presenting a methodology for designing VR, through an Authoring System based on Computer-Aided Design (CAD). The presented methodology provides an easy integration of electric power substation floor plans and Virtual Reality software (VRS), as well as three-dimensional and symbol modeling conventions. Centralized software architecture was developed, composed of the CAD Editor, input manager and VRS. The methodology was evaluated through a case study applied to the conception (elaboration) of electric power substations (EPS) as part of a Research and Development (R&D) project for training and field assets supervision. The results demonstrated visual precision and high integrity in elaboration of a VR environment from the CAD floor plan. This work also presents a comparative analysis between manual conception and the Authoring System.

Real-Time Data Acquisition and Processing System for MHz Repetition Rate Image Sensors

An electro-optic detector is one of the diagnostic setups used in particle accelerators. It employs an electro-optic crystal to encode the longitudinal beam charge profile in the spectrum of a light pulse. The charge distribution is then reconstructed using data captured by a fast spectrometer. The measurement repetition rate should match or exceed the machine bunching frequency, which is often in the range of several MHz. A high-speed optical line detector (HOLD) is a linear camera designed for easy integration with scientific experiments. The use of modern FPGA circuits helps in the efficient collection and processing of data. The solution is based on Xilinx 7-Series FPGA circuits and implements a custom latency-optimized architecture utilizing the AXI4 family of interfaces. HOLD is one of the fastest line cameras in the world. Thanks to its hardware architecture and a powerful KALYPSO sensor from KIT, it outperforms the fastest comparable commercial devices.

Design of a compact reconfigurable bandpass filter using interdigital capacitor, DMS slots and varactor diode for wireless RF systems

This paper proposes a new design of a reconfigurable bandpass filter based on an interdigital capacitor and varactor diode for wireless and mobile applications. The designed reconfigurable bandpass filter has been implemented on an RT 6010 substrate with a relative dielectric constant of 10.2, thickness of 1.27 mm, and loss tangent of 0.0023. In order to reduce the filter size, the defected microstrip structure (DMS) is used due to its easy design, high compactness, high quality factor and easy integration with other RF devices. The suggested reconfigurable filter has a simple structure with a very attractive compact size of 4.7 × 8.4 mm2, low insertion loss than -1 dB, and tuning range (2–2.6 GHz).

Gait Analysis Platform for Measuring Surgery Recovery

Gait analysis has evolved significantly during last years due to the great development of the Medical Internet of Things (MIoT) platforms that allow an easy integration of sensors (inertial, magnetic and pressure in our case) to the complex analytics required to compute, not only relevant parameters, but also meaningful indexes. In this paper, we extend a previous development based on a fully wireless pair of insoles by implementing an updated version with more reliable and user-friendly devices, smartphone app and web front-end and back-end. We also extend previous work focused on fall analysis (with the corresponding fall risk index or FRI) with the proposal of a new surgery recovery index (SRI) to account for the individual speed recovery speed that can be measured either at clinical facilities or at home in a telemedicine environment or while doing daily life activities. This new index can be personalized for different types of surgeries that affect gait such as hip, knee, etc. This paper presents the case of hip recovery and is built on top of the clinical standard SPPB test and allows obtaining quantitative parameters directly from the sensors.