Experimental Setup Research Articles

Experimental and numerical analysis of 3D end effects in Naval Magnetohydrodynamic propulsion motors

This study explores the impact of end electric current on the performance of a marine magnetohydrodynamic (MHD) propulsion motor or thruster using a comprehensive 3D numerical simulation. The investigation focuses on various operating parameters, such as electromagnetic and drag forces, efficiency, losses, current, and different pressure components. To validate the numerical findings, a scaled-down experimental setup is utilised. The results demonstrate that certain operating parameters of MHD motors are not affected by the three-dimensional characteristics of their channels. These parameters, including fluid velocity, can be accurately calculated using the analytical model based on the effective electric current of the motor. Conversely, other operating parameters of MHD motors are significantly influenced by the end effects in their channels. For example, the overall efficiency, which depends on the total electric current of the motor, should be calculated using a more precise simulation method.

An Electrochemical Strip to Evaluate and to Discriminate Drug Encapsulation in Lipid Nanovectors.

Lipid nanovectors (LNVs) represent potent and versatile tools in the field of drug delivery for a wide range of medical applications including cancer therapy and vaccines. With this Technical Note, we introduce a novel "portable", easy-to-use, and low-cost strategy for double use: (1) it allows one to both quantify the amount of cargo in LNV formulation and (2) classify the nature of formulation with the aim of chemometrics. In particular, an electrochemical strip, based on a screen-printed electrode, was exploited to detect methylene blue (MB) as the model cargo encapsulated in various liposomes (used as model LNV). The experimental setup, including release of the MB content and its electrochemical quantification were optimized through a multivariate design of experiment (DoE), obtaining a satisfactory 88-95% accuracy in comparison to standard methods. In addition, the use of principal component analysis-linear discriminant analysis (PCA-LDA) highlighted the satisfactory differentiation of liposomes. The combination of portable electroanalysis and multivariate analysis is a potent tool for enhancing quality control in the field of pharmaceutical technologies, and also in the field of diagnostics, this approach might be useful for application toward naturally occurring lipid nanoparticles, i.e., exosomes.

CHF enhancements of flame-sprayed porous coatings on the outer surface of reactor pressure vessel bottom head

Considering the urgent need for enhancing critical heat flux (CHF) on the outer surface of the reactor pressure vessel (RPV) by in-vessel retention (IVR) on Generation III pressurized water reactors (PWRs), we prepare a porous coating of 316 L stainless steel on the surface of SA508 Grade 3 (SA508–3) steel by flame spraying in this study. Using a small-scale pool boiling experimental setup, we first investigate boiling heat transfer characteristics on bare surfaces and flame-sprayed porous coating surfaces of SA508–3 steel in deionized water at atmospheric pressure, and obtain pool boiling curves and CHFs at different inclination angles. Furthermore, we carry out the IVR engineering verification tests for a full-height RPV bottom head on the REPEC-II test facility built at Shanghai Jiao Tong University. Our experimental results demonstrate that the flame-sprayed porous coatings can significantly enhance the CHF by 21–50 % at different inclination angles of the RPV bottom head. Our full-height facility tests demonstrate that the CHF in the high-inclination angle region, which normally has very high heat flux due to the focusing effect, exceeds 2 MW/m2 on the flame-sprayed porous coating surface. Therefore, our flame-sprayed porous coating has the potential to improve the safety margin of RPV.

Investigating Key Volatile Compound Diffusion in Cocoa Beans during Yeast Fermentation-like Incubation.

An experimental setup was devised to investigate the permeability of cocoa bean seed coat and pulp to key volatile compounds during fermentation. Four labeled compounds (ethyl acetate-d3, ethyl octanoate-d15, 2-phenylethanol-d5, linalool-d5) and 2 unlabeled (beta-damascenone, delta-decalactone) were chosen for the investigation. The beans (cotyledons), depulped beans, or pulped beans were immersed separately in a concentrated solution of these volatile compounds at 36 or 46 °C for durations ranging from 3 to 120 h. The imbibed beans were dissected, and the cotyledons were analyzed by SPME-GC/MS. The diffusion of volatile compounds from the external solution to the seed was categorized into three groups: (1) not diffusible (ethyl octanoate-d15); (2) semidiffusible (ethyl acetate); and (3) totally diffusible (2-phenylethanol-d5, linalool-d5, beta-damascenone, delta-decalactone). The impact of the yeast on volatile compound diffusion was also investigated by immerging the pulped beans into the same concentrated solution with a yeast starter. Results highlighted the positive role of yeast in the diffusion of volatile compounds. The starter positively contributed to volatile compound diffusion after a transition phase occurring at approximately 48 h of fermentation, enriching the cocoa beans with key aromatic volatile compounds.

Experimental and Numerical Characterization of Screw Elements Used in Twin-Screw Extrusion

ABSTRACT Hot melt extrusion by a co-rotating twin screw extruder is an important process in the pharmaceutical industry. Especially for quality by design aspects, a comprehensive process understanding is indispensable. The performance of conveying elements was determined as critical process parameter, and therefore an experimental and numerical framework was developed to analyze and compare variations. A test rig capable of measuring volume flow, pressure and torque with high accuracy and precision was designed and built. The 3D simulation was performed using computational fluid dynamics (CFD). A stationary model with impulse transmission and an apparent motion of the screws was applied. The experimental data were fitted to the model of Pawlowski, and parameters for the pressure (A1, A2) and power characteristics (B1, B2) were determined. Good agreement between experimental data and the model was observed. The simulation was significantly faster compared to common methods, and the results were consistent with the literature. Systematic investigations of a native and worn screw were performed with CFD resulting in a transport capacity increase and a pressure build up decrease for all tested screw elements. An experimental and simulation setup was generated to assess the performance of co-rotating twin screw elements. The experiments provided high-quality data, and the simulations exhibited high flexibility with low computational effort.

Programmable Plasmonic Hydrogel Thermometers Actuated by DNA Breathing

AbstractNanothermometry explores the use of temperature‐dependent properties of materials for remote and sensitive thermal readout at the nanoscale. The currently established nanothermometers are largely limited by uncontrollable nanoparticle flocculation, complex experimental setup, and narrow working temperature range. Here it is shown that gold nanoparticles (e.g., spheres, rods) embedded in a hydrogel can afford sensitive, durable, and range‐tunable temperature sensing via the terminal breathing of the nanoparticle surface‐grafted DNA. The realization of the plasmonic hydrogel thermometer with a thermal sensitivity of ≤2 °C relies on the dynamically modulable interparticle spacing by thermo‐responsive terminal base pairing/unpairing of the surface DNA. By altering the alcoholic ratio of the hydrogel, the temperature‐response range can be continuously regulated based on solvent‐mediated DNA base pairing. Compared with the colloidal counterpart, importantly, the hydrogel thermometer exhibits greatly improved thermal sensing capability (e.g., repeatability ≥50 times) while possessing excellent durability. Given the excellent durability, high sensitivity, and programmable temperature response range, the thermometers actuated by DNA breathing for advanced uses in human sensing and optoelectronics are within reach.

Low Volume Gas-Flow Seeding For Highly Resolved Velocimetry Of The Boundary Layer

Ensuring fire safety in polymeric materials, which are inherently flammable but widely used in various industries, is of significant societal and economic importance. This study is part of a broader effort to understand polymer combustion and flame retardant effectiveness at a fundamental level. A major focus is the behavior of polymers burning along a vertical wall, a configuration chosen to study the release of flammable gases during pyrolysis, which contributes to the self-sustaining combustion reaction of a fire. This process occurs predominantly near the polymer surface within the boundary layer, requiring detailed analysis to evaluate flame retardant effectiveness. Our experimental setup replicates polymer pyrolysis using a flame-wall interaction burner with a vertical jet and a small inlet to mimic the release of flammable gases. The primary challenge in this setup is the introduction of seeding particles for Particle Image Velocimetry (PIV) measurements at low volume flow rates, which is complicated by reflections from the wall and the small flow scale relative to the main flow. To address this problem, we have developed a novel piezo-based ultrasonic seeder capable of controlled seeding at extremely low flow rates, thereby improving the accuracy of PIV measurements in non-reactive configurations. This seeder uses a piezo ring to excite a perforated metal membrane, forming uniform aerosol droplets. The design ensures a steady supply of particles, which is critical for evaluating boundary layer conditions. Our results demonstrate the seeder’s ability to maintain sufficient seeding density in the low volume flow region, facilitating detailed velocimetry analysis. The innovative seeder design proves effective in overcoming the limitations of conventional methods and provides new insights into polymer combustion processes and the role of flame retardants.

Transcriptomic responses of Mediterranean sponges upon encounter with symbiont microbial consortia

BackgroundSponges (phylum Porifera) constantly interact with microbes. They graze on microbes from the water column by filter-feeding and they harbor symbiotic partners within their bodies. In experimental setups, sponges take up symbionts at lower rates compared with seawater microbes. This suggests that sponges have the capacity to differentiate between microbes and preferentially graze in non-symbiotic microbes, although the underlying mechanisms of discrimination are still poorly understood. Genomic studies showed that, compared to other animal groups, sponges present an extended repertoire of immune receptors, in particular NLRs, SRCRs, and GPCRs, and a handful of experiments showed that sponges regulate the expression of these receptors upon encounter with microbial elicitors. We hypothesize that sponges may rely on differential expression of their diverse repertoire of poriferan immune receptors to sense different microbial consortia while filter-feeding. To test this, we characterized the transcriptomic response of two sponge species, Aplysina aerophoba and Dysidea avara, upon incubation with microbial consortia extracted from A. aerophoba in comparison with incubation with seawater microbes. The sponges were sampled after 1 h, 3 h, and 5 h for RNA-Seq differential gene expression analysis.ResultsD. avara incubated with A. aerophoba-symbionts regulated the expression of genes related to immunity, ubiquitination, and signaling. Within the set of differentially-expressed immune genes we identified different families of Nucleotide Oligomerization Domain (NOD)-Like Receptors (NLRs). These results represent the first experimental evidence that different types of NLRs are involved in microbial discrimination in a sponge. In contrast, the transcriptomic response of A. aerophoba to its own symbionts involved comparatively fewer genes and lacked genes encoding for immune receptors.ConclusionOur work suggests that: (i) the transcriptomic response of sponges upon microbial exposure may imply “fine-tuning” of baseline gene expression as a result of their interaction with microbes, (ii) the differential response of sponges to microbial encounters varied between the species, probably due to species-specific characteristics or related to host’s traits, and (iii) immune receptors belonging to different families of NLR-like genes played a role in the differential response to microbes, whether symbionts or food bacteria. The regulation of these receptors in sponges provides further evidence of the potential role of NLRs in invertebrate host-microbe interactions. The study of sponge responses to microbes exemplifies how investigating different animal groups broadens our knowledge of the evolution of immune specificity and symbiosis.

Effectiveness of Suspended Lead Dampers in Steel Building Structural Model Subjected to Impact Load

This paper delves into an in-depth experimental investigation focusing on the dynamic behavior of steel frame buildings employing passive damping through suspended lead dampers. The primary objective revolves around scrutinizing a three-story steel frame building model to elucidate the effects of integrating lead dampers into the outer tubular square-section columns. By strategically embedding these dampers, the study aims to showcase the resultant reductions in both acceleration and displacement. To execute this analysis, an impact load is precisely applied to the mid-center of the middle column along the x-axis of the first story of the steel frame. The experimental setup employs six wireless accelerometers strategically positioned across the frame to capture comprehensive data on its response at diverse locations. Various quantities of lead dampers are systematically incorporated into each testing scenario to gauge the extent of passive damping’s influence on the structural response of steel buildings to impact loads. Throughout the experiments, acceleration-time relations are meticulously recorded at each story, facilitating a comparative assessment of outcomes with and without the presence of lead dampers. The findings of the study underscore a marked decrease in vibration levels at higher floors of the steel model subsequent to the installation of lead dampers within the structure. Furthermore, a noteworthy trend emerges indicating that an augmented number of lead dampers within the building yields a commensurate decrease in vibration amplitude. This detailed investigation offers valuable insights into the efficacy of passive damping mechanisms, thereby contributing to the advancement of seismic-resistant structural design practices.

Raman Spectroscopy in Optical Non-Invasive Diagnostics of Skin Neoplasms

Introduction. Recent decades indicate a significant increase in the incidence of skin cancer. Aim. To upgrade the specialized device and to improve the quality of skin neoplasm diagnostics. Materials and methods. The study mainly involved the method of non-invasive differential diagnostics of skin neoplasms. The method relies upon optical research methods, including Raman spectroscopy, a spectroscopic technique. A 10-year study, conducted by the Department of Oncology, the Samara Regional Clinical Oncology Dispensary (SOKOD), included more than 500 observations. The study used samples of various skin neoplasms obtained during surgical treatment of patients. Experimental tests provided a certain spectrum of various benign and malignant human skin neoplasms, including melanoma. Results. A series of experimental tests resulted in an experimental setup that is absolutely safe to use. Discussion. The study involved comparison of individual characteristics of the Raman spectra, obtained in the examination of neoplasm and healthy skin for each patient, thereby individualizing the method. The study revealed a high accuracy rate of 92% (with sensitivity of 89%, specificity of 93%), thus minimizing risks of false negative results, which is essential for mass examination. Conclusion. Since the proposed device setup does not require consumable products and different reagents, the method is marked with lower time costs and maintenance burden. Raman spectroscopy obtains a significant potential, thus, can be widely used for skin neoplasms in various medical and preventive institutions.

Efficient PFAS removal from contaminated soils through combined washing and adsorption in soil effluents

This study investigates soil washing as a viable strategy to remove poly- and perfluoroalkyl substances (PFAS) from contaminated soils using various washing agents including water, methanol, ethanol, and cyclodextrin ((2-Hydroxypropyl)-β-cyclodextrin HPCD)). Water was less effective (removing only 30 % of PFAS), especially for long-chain hydrophobic PFAS. Methanol (50 % v/v) or HPCD (10 mg g–1 soil) achieved > 95 % PFAS removal regardless of PFAS type, soil size fraction (0–400 µm or 400–800 µm), or experimental setups (batch or column, at liquid/solid (L/S) = 1). Column optimization studies revealed improved efficiency at L/S = 10 with diluted washing solutions, where HPCD exhibited rapid PFAS mobilization even at lower concentrations (1 mg mL–1). We then applied a first-order decay model to effectively predict PFAS breakthrough curves and mobilization within soil columns. Subsequent treatment of wash effluents by activated carbon and biochar effectively reduced PFAS concentrations below detection limits. The performance of both soil washing and subsequent adsorption was found to depend strongly on the specific characteristics of PFAS compounds. These findings highlight the significant potential of methanol and HPCD in soil washing and the effectiveness of integrated soil washing and adsorption for optimizing PFAS removal.

Uncertainty quantification by direct propagation of shallow ensembles

Statistical learning algorithms provide a generally-applicable framework to sidestep time-consuming experiments, or accurate physics-based modeling, but they introduce a further source of error on top of the intrinsic limitations of the experimental or theoretical setup. Uncertainty estimation is essential to quantify this error, and to make application of data-centric approaches more trustworthy. To ensure that uncertainty quantification is used widely, one should aim for algorithms that are accurate, but also easy to implement and apply. In particular, including uncertainty quantification on top of an existing architecture should be straightforward, and add minimal computational overhead. Furthermore, it should be easy to manipulate or combine multiple machine-learning predictions, propagating uncertainty over further modeling steps. We compare several well-established uncertainty quantification frameworks against these requirements, and propose a practical approach, which we dub direct propagation of shallow ensembles, that provides a good compromise between ease of use and accuracy. We present benchmarks for generic datasets, and an in-depth study of applications to the field of atomistic machine learning for chemistry and materials. These examples underscore the importance of using a formulation that allows propagating errors without making strong assumptions on the correlations between different predictions of the model.

IQ-channel multiplexed DP-4ASK signal using power loading for downlink coherent PON system with access-span length difference

This study explores the integration of dual-polarized (DP) four-level amplitude shift keying (4ASK) signals within an intensity and quadrature division multiplexing framework, mainly focusing on coherent passive optical network (PON) systems. The primary objective is to address the challenges associated with distance disparities in downstream transmissions, which are prevalent in coherent PON architectures. We introduce a novel approach that significantly reduces the power consumption of digital-to-analog converters by implementing power loading strategies tailored explicitly for IQ channel division multiplexing (IQDM)-DP-4ASK signals. Our simulations confirm that ASK standard frequency offset compensation is adaptable to these signals, providing a robust method for managing frequency offsets in a dynamic network environment. Moreover, we propose and empirically validate an energy-efficient adaptive downlink solution capable of supporting 128 Gb/s per optical network unit (ONU), utilizing IQ-imbalanced DP-4ASK signals. This solution is particularly advantageous for systems where the transmission conditions include a 10 km variance in access span lengths between ONUs. Results from our experimental setup demonstrate that reducing the digital-to-analog converter output current for the Q channel by 137 mA is feasible without compromising signal integrity or system performance. Additionally, the research verifies the effectiveness of the automatic bias controller on the transmitter side, ensuring stable operation across varying conditions. Equally, the receiver-side digital signal processing effectively handles polarization separation, illustrating the system's capability to maintain high data integrity and reliability under diverse operational scenarios. These findings highlight the technical feasibility and operational benefits of using IQDM-DP-4ASK signals in coherent PON systems and underscore the potential for significant power savings and enhanced system efficiency in optical networks. The study paves the way for future research into scalable, energy-efficient solutions suitable for high-capacity optical access networks striving for increased sustainability and reduced operational costs.

Simple and Rapid Monolayer Self-Assembly of Nanoparticles at the Air/Water Interface.

Colloidal crystals and their two-dimensional (2D) monolayers, which have been commonly applied in nanosphere lithography, have the potential to revolutionize many engineering disciplines; however, current production techniques are hampered by a restricted preparation area, laborious procedures, and the need for advanced equipment. We propose a self-assembly-driven, simple, and low-cost method to prepare 2D colloidal nanosphere monolayers with excellent repeatability across wide regions. The self-assembly capability of colloidal polystyrene (PS) nanospheres at the air/water interface was utilized to transfer the assembled monolayers onto a substrate. This innovative method combines the advantages of methods that permit deposition at the air/water interface, such as Langmuir and drop coating, in order to deliver defect-free, simple-to-install, and simple-to-apply deposition across vast regions. Using field emission scanning electron microscopy and atomic force microscopy, the resultant coatings were characterized. The size of the nanospheres was reduced using an oxygen plasma etch process in an inductively coupled plasma reactive ion etching system, and the reflectance properties of the substrates for various nanosphere sizes were investigated. By evaporation of a thin gold capping layer on the templates, their optical properties were compared using surface-enhanced Raman scattering spectroscopy. This work has the potential to expand the use of nanosphere lithography by offering a simple and reproducible method that eliminates the need for complicated experimental setups and reduces the amount of material required for monolayer coating, thus lowering the cost.

Multi-qubit dynamical decoupling for enhanced crosstalk suppression

Dynamical decoupling (DD) is one of the simplest error suppression methods, aiming to enhance the coherence of qubits in open quantum systems. Moreover, DD has demonstrated effectiveness in reducing coherent crosstalk, one major error source in near-term quantum hardware, which manifests from two types of interactions. Static crosstalk exists in various hardware platforms, including superconductor and semiconductor qubits, by virtue of always-on qubit-qubit coupling. Additionally, driven crosstalk may occur as an unwanted drive term due to leakage from driven gates on other qubits. Here we explore a novel staggered DD protocol tailored for multi-qubit systems that suppresses the decoherence error and both types of coherent crosstalk. We develop two experimental setups—an ‘idle–idle’ experiment in which two pairs of qubits undergo free evolution simultaneously and a ‘driven-idle’ experiment in which one pair is continuously driven during the free evolution of the other pair. These experiments are performed on an IBM Quantum superconducting processor and demonstrate the significant impact of the staggered DD protocol in suppressing both types of coherent crosstalk. When compared to the standard DD sequences from state-of-the-art methodologies with the application of X2 sequences, our staggered DD protocol enhances circuit fidelity by 19.7% and 8.5%, respectively, in addressing these two crosstalk types.

Accurately Computing the Interacted Volume of Molecules over Their 3D Mesh Models.

For quickly predicting the rational arrangement of catalysts and substrates, we previously proposed a method to calculate the interacted volumes of molecules over their 3D point cloud models. However, the nonuniform density in molecular point clouds may lead to incomplete contours in some slices, reducing the accuracy of the previous method. In this paper, we propose a two-step method for more accurately computing molecular interacted volumes. First, by employing a prematched mesh slicing method, we layer the 3D triangular mesh models of the electrostatic potential isosurfaces of two molecules globally, transforming the volume calculation into finding the intersecting areas in each layer. Next, by subdividing polygonal edges, we accurately identify intersecting parts within each layer, ensuring precise calculation of interacted volumes. In addition, we present a concise overview for computing intersecting areas in cases of multiple contour intersections and for improving computational efficiency by incorporating bounding boxes at three stages. Experimental results demonstrate that our method maintains high accuracy in different experimental data sets, with an average relative error of 0.16%. On the same experimental setup, our average relative error is 0.07%, which is lower than the previous algorithm's 1.73%, improving the accuracy and stability in calculating interacted volumes.

Virological characteristics of the SARS-CoV-2 Omicron EG.5.1 variant.

In middle to late 2023, a sublineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron XBB, EG.5.1 (a progeny of XBB.1.9.2), is spreading rapidly around the world. We performed multiscale investigations, including phylogenetic analysis, epidemic dynamics modeling, infection experiments using pseudoviruses, clinical isolates, and recombinant viruses in cell cultures and experimental animals, and the use of human sera and antiviral compounds, to reveal the virological features of the newly emerging EG.5.1 variant. Our phylogenetic analysis and epidemic dynamics modeling suggested that two hallmark substitutions of EG.5.1, S:F456L and ORF9b:I5T are critical to its increased viral fitness. Experimental investigations on the growth kinetics, sensitivity to clinically available antivirals, fusogenicity, and pathogenicity of EG.5.1 suggested that the virological features of EG.5.1 are comparable to those of XBB.1.5. However, cryo-electron microscopy revealed structural differences between the spike proteins of EG.5.1 and XBB.1.5. We further assessed the impact of ORF9b:I5T on viral features, but it was almost negligible in our experimental setup. Our multiscale investigations provide knowledge for understanding the evolutionary traits of newly emerging pathogenic viruses, including EG.5.1, in the human population.

The 3d response of a large-scale masonry arch bridge - part I: Performance under low and medium loading levels

Masonry arch bridges are characterised by three-dimensional (3D) behaviour when subjected to external eccentric loading (e.g., vehicle loads). The arch ring, abutments, backfill and spandrel walls may interact with each other in a complex manner, leading to a 3D mode of response that can have a significant impact on the initiation and propagation of damage. However, there is a dearth of experimental data from tests designed to investigate the 3D behaviour of masonry arch bridges, particularly under loading levels below those required to cause failure. This paper presents results from tests on a large-scale brickwork masonry arch bridge subjected to low- and mid-level static loads under laboratory conditions. Point loads of increasing magnitude were applied at different locations on the top of the backfill in order to investigate 3D response and damage accumulation. Details of the experimental setup, material characterisation, and the results obtained from static and repeated load tests at low- and mid-level load magnitudes are presented herein. Results demonstrate that the bridge exhibited a 3D mode of response under eccentric point loads. Loading at the mid-span resulted in greater deformation of the arch barrel compared to loading at the quarter- and three-quarter-span points, due to the shallower backfill depth over the crown. Under the mid-level loading, stiffness degradation was observed during the testing regime, suggesting an accumulation of damage in the bridge. Moreover, when loading was applied close to a spandrel wall, measurable out-of-plane deformation of the spandrel wall was observed, with this deformation increasing significantly as the load was increased from 150 kN to 250 kN. This results from a combination of increased lateral soil pressure and decreased shear resistance at the arch-spandrel wall interface.

Economic Evaluation of Using Ultracapacitors in Electric Vehicles

The main challenge of hybridizing ultracapacitors (UCs) with batteries in electric vehicles is their uncertain economic viability, besides their complexity and weight, which should be fully addressed. Therefore, this article determines the general condition for achieving a justified economic system, which is held when the average annual cost (AAC) of a battery‐UC system over a vehicle's useful life is lower than the annual cost of a sole‐battery for a specific system design, energy management strategy, vehicle type, and driving style. As such, the energy storage system is designed in a case study vehicle, and the optimal current distribution is found by dynamic programming (DP) under UDDS, HWFET, and US06 driving cycles. Then, by economic analysis, it is indicated that although adding an UC incurs additional costs, it saves the AAC by improving the battery health and prolonging its lifespan up to a maximum of 15‐year calendar life, which proves its economic justification. Investing in UCs is more economically viable for vehicles with severe driving cycles and high current stress. Finally, the DP optimal trajectory is implemented into an experimental setup under the US06 driving cycle to verify the evaluated strategy.

Brainwaves in the Cloud: Cognitive Workload Monitoring Using Deep Gated Neural Network and Industrial Internet of Things

Monitoring and classifying cognitive workload in real time is vital for optimizing human–machine interactions and enhancing performance while ensuring safety, particularly in industrial scenarios. Considering this significance, the authors aim to formulate a cognitive workload monitoring system (CWMS) by leveraging the deep gated neural network (DGNN), a hybrid model integrating bi-directional long short-term memory (Bi-LSTM) and gated recurrent unit (GRU) networks. In our experimental setup, each of the four virtual users is equipped with a Raspberry Pi Zero W module to ensure efficient data transmission, thereby enhancing the reliability and efficacy of the monitoring process. This seamless monitoring framework utilizes the constrained application protocol (CoAP) and the Things Board platform to evaluate cognitive workload in real time. The most popular EEG benchmark dataset, the STEW is utilized for workload classification in this study. We employ the short-time Fourier transformation (STFT) to extract frequency bands corresponding to users in both high and low cognitive workload modes. The proposed DGNN models achieve a perfect accuracy of 99.45%, outperforming every previous state-of-the-art model. We meticulously monitored critical parameters, including latency, classification processing time, and cognitive workload levels. This research demonstrates the importance of continuous monitoring for increasing productivity and safety in industries by introducing a novel method of real-time cognitive workload monitoring. The implementation codes for each experiment are documented and made available for reproducibility.