Comparative Analysis of Power Consumption between MQTT and HTTP Protocols in an IoT Platform Designed and Implemented for Remote Real-Time Monitoring of Long-Term Cold Chain Transport Operations.

IoT platforms for the transportation industry are portable with limited battery life and need real-time and long-term monitoring operations. Since MQTT and HTTP are widely used as the main communication protocols in the IoT, it is imperative to analyze their power consumption to provide quantitative results that help maximize battery life in IoT transportation systems. Although is well known that MQTT consumes less power than HTTP, a comparative analysis of their power consumption with long-time tests and different conditions has not yet been conducted. In this sense, a design and validation of an electronic cost-efficient platform system for remote real-time monitoring is proposed using a NodeMCU module, in which experimentation is carried out for HTTP and MQTT with different QoS levels to make a comparison and demonstrate the differences in power consumption. Furthermore, we characterize the behavior of the batteries in the systems and compare the theoretical analysis with real long-time test results. The experimentation using the MQTT protocol with QoS 0 and 1 was successful, resulting in power savings of 6.03% and 8.33%, respectively, compared with HTTP, demonstrating many more hours in the duration of the batteries, which could be very useful in technological solutions for the transport industry.

Comparative Evaluation of Artificial Neural Networks and Data Analysis in Predicting Liposome Size in a Periodic Disturbance Micromixer.

Artificial neural networks (ANN) and data analysis (DA) are powerful tools for supporting decision-making. They are employed in diverse fields, and one of them is nanotechnology; for example, in predicting silver nanoparticles size. To our knowledge, we are the first to use ANN to predict liposome size (LZ). Liposomes are lipid nanoparticles used in different biomedical applications that can be produced in Dean-Forces-based microdevices such as the Periodic Disturbance Micromixer (PDM). In this work, ANN and DA techniques are used to build a LZ prediction model by using the most relevant variables in a PDM, the Flow Rate Radio (FRR), and the Total Flow Rate (TFR), and the temperature, solvents, and concentrations were kept constant. The ANN was designed in MATLAB and fed data from 60 experiments with 70% training, 15% validation, and 15% testing. For DA, a regression analysis was used. The model was evaluated; it showed a 0.98147 correlation coefficient for training and 0.97247 in total data compared with 0.882 obtained by DA.

Rapid Lipid Content Screening in Neochloris oleoabundans Utilizing Carbon-Based Dielectrophoresis.

In this study, we carried out a heterogeneous cytoplasmic lipid content screening of Neochloris oleoabundans microalgae by dielectrophoresis (DEP), using castellated glassy carbon microelectrodes in a PDMS microchannel. For this purpose, microalgae were cultured in nitrogen-replete (N+) and nitrogen-deplete (N-) suspensions to promote low and high cytoplasmic lipid production in cells, respectively. Experiments were carried out over a wide frequency window (100 kHz-30 MHz) at a fixed amplitude of 7 VPP. The results showed a statistically significant difference between the dielectrophoretic behavior of N+ and N- cells at low frequencies (100-800 kHz), whereas a weak response was observed for mid- and high frequencies (1-30 MHz). Additionally, a finite element analysis using a 3D model was conducted to determine the dielectrophoretic trapping zones across the electrode gaps. These results suggest that low-cost glassy carbon is a reliable material for microalgae classification-between low and high cytoplasmic lipid content-through DEP, providing a fast and straightforward mechanism.

Sensitivity Analysis of a Portable Wireless PCB-MEMS Permittivity Sensor Node for Non-Invasive Liquid Recognition.

Dielectric characteristics are useful to determine crucial properties of liquids and to differentiate between liquid samples with similar physical characteristics. Liquid recognition has found applications in a broad variety of fields, including healthcare, food science, and quality inspection, among others. This work demonstrates the fabrication, instrumentation, and functionality of a portable wireless sensor node for the permittivity measurement of liquids that require characterization and differentiation. The node incorporates an interdigitated microelectrode array as a transducer and a microcontroller unit with radio communication electronics for data processing and transmission, which enable a wide variety of stand-alone applications. A laser-ablation-based microfabrication technique is applied to fabricate the microelectromechanical systems (MEMS) transducer on a printed circuit board (PCB) substrate. The surface of the transducer is covered with a thin layer of SU-8 polymer by spin coating, which prevents it from direct contact with the Cu electrodes and the liquid sample. This helps to enhance durability, avoid electrode corrosion and contamination of the liquid sample, and to prevent undesirable electrochemical reactions to arise. The transducer's impedance was modeled as a Randles cell, having resistive and reactive components determined analytically using a square wave as stimuli, and a resistor as a current-to-voltage converter. To characterize the node sensitivity under different conditions, three different transducer designs were fabricated and tested for four different fluids, i.e., air, isopropanol, glycerin, and distilled water-achieving a sensitivity of 1.6965 +/- 0.2028 εr/pF. The use of laser ablation allowed the reduction of the transducer footprint while maintaining its sensitivity within an adequate value for the targeted applications.

Parametric Study of the Factors Influencing Liposome Physicochemical Characteristics in a Periodic Disturbance Mixer.

Liposomes encapsulate different substances ranging from drugs to genes. Control over the average size and size distribution of these nanoparticles is vital for biomedical applications since these characteristics determine to a high degree where liposomes will accumulate in the human body. Micromixers enable the continuous flow synthesis of liposomes, improving size control and reproducibility. Recently, Dean flow dynamics-based micromixers, such as the periodic disturbance mixer (PDM), have been shown to produce controlled-size liposomes in a scalable and reproducible way. However, contrary to micromixers based on molecular diffusion or chaotic advection, their production factors and their influence over liposome properties have not yet been addressed thoroughly. In this work, we present a comprehensive parametric study of the effects of flow conditions and molecular changing factors such as concentration, lipid type, and temperature on the physicochemical characteristics of liposomes. Numerical models and confocal images are used to quantitatively and qualitatively evaluate mixing performance under different liposome production conditions and their relationship with vesicle properties. The total flow rate (TFR) and, to a lesser extent, the flow rate ratio (FRR) control the liposome size and size distribution. Effects on liposome size are also observed by changing the molecular factors. Moreover, the liposome ζ potential is independent of the factors studied here. The micromixer presented in this work enables the production of liposomes as small as 24 nm, with monodispersed to low or close to low polydispersed liposome populations as well as a production rate as high as 41 mg/h.

Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer.

Liposomes nanoparticles (LNPs) are vesicles that encapsulate drugs, genes, and imaging labels for advanced delivery applications. Control and tuning liposome physicochemical characteristics such as size, size distribution, and zeta potential are crucial for their functionality. Liposome production using micromixers has shown better control over liposome characteristics compared with classical approaches. In this work, we used our own designed and fabricated Periodic Disturbance Micromixer (PDM). We used Design of Experiments (DoE) and Response Surface Methodology (RSM) to statistically model the relationship between the Total Flow Rate (TFR) and Flow Rate Ratio (FRR) and the resulting liposomes physicochemical characteristics. TFR and FRR effectively control liposome size in the range from 52 nm to 200 nm. In contrast, no significant effect was observed for the TFR on the liposomes Polydispersity Index (PDI); conversely, FRR around 2.6 was found to be a threshold between highly monodisperse and low polydispersed populations. Moreover, it was shown that the zeta potential is independent of TFR and FRR. The developed model presented on the paper enables to pre-establish the experimental conditions under which LNPs would likely be produced within a specified size range. Hence, the model utility was demonstrated by showing that LNPs were produced under such conditions.

Sequentially multiplexed amperometry for electrochemical biosensors.

Multiplexed electrochemical biosensors are intriguing due to their capability to permit high-throughput and low-cost assays. While commercial single-chip potentiostats are one promising approach for rapidly prototyping portable and low-cost electrochemical biosensors, it is still challenging to utilize them to achieve parallel multiplexing due to the limited resources integrated onto the chips. In this paper, we provide a methodology for incorporating multiplexing into commercial single-chip potentiostats by using a sequential architecture. In the sequential architecture, the multiplexed biosensors are interfaced to the single-chip potentiostat via single-pole single-throw switches, and the measurements alternate across the sensors. We build analytical and finite element models to investigate the behavior of the sensors, particularly when they are disconnected from the potentiostat, and find that we can take advantage of the dynamics of the sensors to achieve improved sensitivity over conventional chronoamperometry. We also investigate and compare different strategies to interface the multiplexed sensors to the single-chip potentiostat. Using the proposed multiplexing architecture, we demonstrate the implementation of 16-fold multiplexed amperometry, which is validated using ferricyanide measurement. Finally, the sequential multiplexing methodology is applied to a multiplexed bead-based electronic enzyme-linked immunosorbent assays of human interleukin-6.

Emerging microfluidic devices for cancer cells/biomarkers manipulation and detection.

Circulating tumour cells (CTCs) are active participants in the metastasis process and account for ∼90% of all cancer deaths. As CTCs are admixed with a very large amount of erythrocytes, leukocytes, and platelets in blood, CTCs are very rare, making their isolation, capture, and detection a major technological challenge. Microfluidic technologies have opened-up new opportunities for the screening of blood samples and the detection of CTCs or other important cancer biomarker-proteins. In this study, the authors have reviewed the most recent developments in microfluidic devices for cells/biomarkers manipulation and detection, focusing their attention on immunomagnetic-affinity-based devices, dielectrophoresis-based devices, surface-plasmon-resonance microfluidic sensors, and quantum-dots-based sensors.

Continuous flow micro-bioreactors for the production of biopharmaceuticals: the effect of geometry, surface texture, and flow rate.

We used continuous flow micro-devices as bioreactors for the production of a glycosylated pharmaceutical product (a monoclonal antibody). We cultured CHO cells on the surface of PMMA/PDMS micro-channels that had been textured by micromachining and coated with fibronectin. Three different micro-channel geometries (a wavy channel, a zigzag channel, and a series of donut-shape reservoirs) were tested in a continuous flow regime in the range of 3 to 6 µL min(-1). Both the geometry of the micro-device and the flow rate had a significant effect on cell adhesion, cell proliferation, and monoclonal antibody production. The most efficient configuration was a series of donut-shaped reservoirs, which yielded mAb concentrations of 7.2 mg L(-1) at residence times lower than one minute and steady-state productivities above 9 mg mL(-1) min(-1). These rates are at about 3 orders of magnitude higher than those observed in suspended-cell stirred tank fed-batch bioreactors.

A biopharmaceutical plant on a chip: continuous micro-devices for the production of monoclonal antibodies.

We report a proof-of-principle for the use of micro-devices as continuous bioreactors for the production of monoclonal antibodies. We culture CHO cells on the surface of PMMA "zigzag" channels textured with semi-spherical cavities coated with fibronectin, observing steady-state productivities 100 times higher than those observed in full scale systems.