Development and validation of a behavioural video coding scheme for detecting mental workload in manual assembly

Abstract

Manual assembly in the future Industry 4.0 workplace will put high demands on operators’ cognitive processing. The development of mental workload (MWL) measures therefore looms large. Physiological gauges such as electroencephalography (EEG) show promising possibilities, but still lack sufficient reliability when applied in the field. This study presents an alternative measure with a substantial ecological validity. First, we developed a behavioural video coding scheme identifying 11 assembly behaviours potentially revealing MWL being too high. Subsequently, we explored its validity by analysing videos of 24 participants performing a high and a low complexity assembly. Results showed that five of the behaviours identified, such as freezing and the amount of part rotations, significantly differed in occurrence and/or duration between the two conditions. The study hereby proposes a novel and naturalistic method that could help practitioners to map and redesign critical assembly phases, and researchers to enrich validation of MWL-measures through measurement triangulation.

Practitioner summary: Current physiological mental workload (MWL) measures still lack sufficient reliability when applied in the field. Therefore, we identified several observable assembly behaviours that could reveal MWL being too high. The results propose a method to map MWL by observing specific assembly behaviours such as freezing and rotating parts.

Abbreviations: MWL: mental workload; EEG: electroencephalography; fNIRS: functional near infrared spectroscopy; AOI: area of interest; SMI: SensoMotoric Instruments, ETG: Eye-Tracking Glasses; FPS: frames per second; BORIS: Behavioral Observation Research Interactive Software; IRR: inter-rater reliability; SWAT: Subjective Workload Assessment Technique; NASA-TLX: National Aeronautics and Space Administration Task Load Index; EL: emotional load; DSSQ: Dundee Stress State Questionnaire; PHL: physical load; SBO: Strategisch Basis Onderzoek     

Characterization of the Lipid Fraction of Wild Sea Urchin from the Sardinian Sea (Western Mediterranean)

The fatty acid (FA) composition of Spatangus purpureus, Echinus melo, Sphaerechinus granularis, and Paracentrotus lividus, sea urchins, has been studied. Sea urchins were collected at different depth along Sardinia coast in the Mediterranean sea, and their gonad was measured, separated, and analyzed for FA composition by gas chromatography‐mass spectrometry. A total of 53 FAs were detected, 16 saturated (SFA), 10 monounsaturated (MUFA), 9 polyunsaturated (PUFA), and 13 highly unsaturated (HUFA). Moreover, 5 furan FAs (FFAs) were revealed for the first time in sea urchin. The HUFA and PUFA classes were the most represented accounting for almost 80% of total FAs. Among these compounds, C20:4 n6 (19.64, 20.52, 23.37, and 8.48 mg/g, respectively) and C22:6 n3 (19.68, 20.05, 3.83, and 1.78 mg/g, respectively) were the most abundant. The results of principal component analysis indicated that the sea urchin samples could be clearly discriminated with respect to their FAs composition.     

Effect of layout parasitics on the current distribution of power MOSFETs operated at high switching frequency

The internal electrical characteristics of an 800-V 9-A 0.7-Ω silicon power MOSFET are investigated using a distributed modelling approach. A cad tool has been developed to automatically extract layout parasitics and create an equivalent spice-like netlist of the device under investigation. The distributed model is employed to investigate the performance of the device during a turn-off switching at different values of the gate fall time. Simulations show that reducing the gate fall time contributes to increase the internal current imbalance leading to current density overshoots, referred to as hot spots. Moreover, faster switching operation forces current density to crowd towards the slowest parts of the device which in turn degrades the overall device ruggedness. These results demonstrate that the proposed modelling approach allows accurate simulation of the internal current distribution identifying the regions where hot spots are more likely to occur.     

Gas Chromatographic Mass Spectrometry Determination of Geosmin and 2-methylisoborneol Off-Flavor in <Emphasis Type="Italic">Mugil cephalus</Emphasis> Roe

Botargo is the product of the industrial management of fresh roe of the grey mullet (Mugil cephalus). This food product is actually obtained from wild fish caught in different marine areas around the word. The increasing commercial demand of botargo has brought to carry out different fishing systems, gathering the wild mullet in restricted areas, lagoons, to be caught if necessary. This operating mode has caused the appearance of new problems related to the organoleptic approval by the consumers of fish and derived products, following off-flavor contamination derived from different microorganisms present in the lagoons. The most important off-flavor compounds are represented by 2-methylisoborneol (2-MIB) and geosmin (GSM) which give a muddy/musty smell and flavor to the fish. A simple and easy-to-use GC/MS method for the determination of 2-MIB and GSM has been developed. The method has been validated with the following parameters: instrument limit of detection (LOD) and of quantification (LOQ), precision, recovery, and linearity. The method carried out showed good LOD of 1.0 μg/kg and LOQ 2.0 and 5.0 μg/kg for GSM and 2-MIB, respectively. Validation parameters were in close agreement with those reported in the EC SANCO/12571/2013. Recoveries ranged from 80.2 to 121.4 %, with percent relative standard deviation (RSD%) ranging from 0.6 to 18.6 % in the most unfavorable case. Real sample analysis showed the presence of residues of both off-flavor in all botargo samples analyzed, except for sample S0, while in fresh roe samples, only S7 showed important residues of 2-MIB.     

Monitoring roughness and edge shape on semiconductors through multiresolution and multivariate image analysis

Photolithography is one of the most important processes in the production of integrated circuits. Usually, attentive inspections are required after this process, but are limited to the measurement of some physical parameters such as the critical dimension and the line edge roughness. In this paper, a novel multiresolution multivariate technique is presented to identify the abnormalities on the surface of a photolithographed device and the location of defects in a sensitive fashion by comparing it to a reference optimum, and generating fast, meaningful and reliable information. After analyzing the semiconductor surface image in different levels of resolutions via wavelet decomposition, the application of multivariate statistical monitoring tools allows the in‐depth examination of the imprinted features of the product. A two level nested PCA model is used for surface roughness monitoring, while a new strategy based on “spatial moving window” PCA is proposed to analyze the shape of the patterned surface. The effectiveness of the proposed approach is tested in the case of semiconductor surface SEM images after the photolithography process. The approach is general and can be applied also to inspect a product through different types of images, different phases of the same production systems, or different processes. © 2009 American Institute of Chemical Engineers AIChE J, 2009     

Moving average PLS soft sensor for online product quality estimation in an industrial batch polymerization process

This paper considers the development of multivariate statistical soft sensors for the online estimation of product quality in a real-world industrial batch polymerization process. The batches are characterized by uneven length, non-reproducible sequence of processing steps, and scarce number of measurements for the quality indicators with uneven sampling of (and lag on) these variables. It is shown that, for the purpose of quality estimation, the complex series of operating steps characterizing a batch can be simplified to a sequence of three estimation phases. The switching from one phase to the other one can be triggered by easily detectable events occurring in the batch. For each estimation phase, PLS software sensors are designed, and their performance is evaluated against plant data. The estimation accuracy can be substantially improved if some form of dynamic information is included into the models, either by augmenting the process data matrix with lagged measurements, or by averaging the process measurements values on a moving window of fixed length. In particular, the moving average three-phase PLS estimator shows the best overall performance, providing accurate estimations also during estimation Phase 2, which is characterized by a very large variability between batches.     

A Chemically Orthogonal Hole Transport Layer for Efficient Colloidal Quantum Dot Solar Cells

Colloidal quantum dots (CQDs) are of interest in light of their solution-processing and bandgap tuning. Advances in the performance of CQD optoelectronic devices require fine control over the properties of each layer in the device materials stack. This is particularly challenging in the present best CQD solar cells, since these employ a p-type hole-transport layer (HTL) implemented using 1,2-ethanedithiol (EDT) ligand exchange on top of the CQD active layer. It is established that the high reactivity of EDT causes a severe chemical modification to the active layer that deteriorates charge extraction. By combining elemental mapping with the spatial charge collection efficiency in CQD solar cells, the key materials interface dominating the subpar performance of prior CQD PV devices is demonstrated. This motivates to develop a chemically orthogonal HTL that consists of malonic-acid-crosslinked CQDs. The new crosslinking strategy preserves the surface chemistry of the active layer beneath, and at the same time provides the needed efficient charge extraction. The new HTL enables a 1.4× increase in charge carrier diffusion length in the active layer; and as a result leads to an improvement in power conversion efficiency to 13.0% compared to EDT standard cells (12.2%).     

Mathematical modelling of the evolution of protein distribution within single PLGA microspheres: prediction of local concentration profiles and release kinetics

Protein release from poly(D,L-lactide-co-glycolide) (PLGA) microspheres in an aqueous environment is governed by the diffusion of the protein through an autocatalytically degrading polymeric matrix. Many attempts have been made to model the release rate of proteins from biodegrading matrices, but the transport parameters involved in the process are not fully established at the microscale level. The aim of this work was to develop a new mathematical model taking into account the temporal evolution of the radial protein distribution during release, and to provide physical insight into the relation between local transport features and microsphere degradation. The model was validated by comparing its predictions with the experimentally determined protein concentration profiles in PLGA microspheres loaded with tetramethylrhodamine-labelled bovine serum albumin (BSA-Rhod) as a model protein. Morphological studies were carried out by scanning electron microscopy (SEM), while release kinetics and time-dependent BSA-Rhod concentration profiles within the microspheres were studied by a confocal laser scanning microscopy (CLSM)-assisted technique. The model, based on a modification of Fick's second law of diffusion, could closely fit the experimental protein radial distribution profiles in the microspheres as a function of time. It is also a useful tool to ab initio design protein release devices using degrading matrices.     

Random insertion of GFP into the cAMP-dependent protein kinase regulatory subunit from Dictyostelium discoideum

The green fluorescent protein (GFP) is currently being used for diverse cellular biology approaches, mainly as a protein tag or to monitor gene expression. Recently it has been shown that GFP can also be used to monitor the activation of second messenger pathways by the use of fluorescence resonance energy transfer (FRET) between two different GFP mutants fused to a Ca2+sensor. We show here that GFP fusions can also be used to obtain information on regions essential for protein function. As FRET requires the two GFPs to be very close, N- or C-terminal fusion proteins will not generally produce FRET between two interacting proteins. In order to increase the probability of FRET, we decided to study the effect of random insertion of two GFP mutants into a protein of interest. We describe here a methodology for random insertion of GFP into the cAMP-dependent protein kinase regulatory subunit using a bacterial expression vector. The selection and analysis of 120 green fluorescent colonies revealed that the insertions were distributed throughout the R coding region. 14 R/GFP fusion proteins were partially purified and characterized for cAMP binding, fluorescence and ability to inhibit PKA catalytic activity. This study reveals that GFP insertion only moderately disturbed the overall folding of the protein or the proper folding of another domain of the protein, as tested by cAMP binding capacity. Furthermore, three R subunits out of 14, which harbour a GFP inserted in the cAMP binding site B, inhibit PKA catalytic subunit in a cAMP-dependent manner. Random insertion of GFP within the R subunit sets the path to develop two-component FRET with the C subunit.     

Are the brains of monozygotic twins similar? A three-dimensional MR study

PURPOSE: The role of genetic mechanisms and the influence of environmental events in human brain development have been difficult to evaluate. The purpose of this study was to compare the cerebral cortical morphology and midline structures of monozygotic twin pairs using MR imaging. METHODS: Six observers, blinded to twin pairings, evaluated the 3-D renderings of the cortical surface and midline structures from MR images of seven monozygotic twin pairs. A morphometric analysis of the corpus callosum and of the distance between the anterior and posterior commissures was also performed. RESULTS: Despite surprising anatomic differences, the brains of the twin pairs were similar enough to enable the observers to distinguish twin pairs from unrelated subjects. Five of six observers correctly identified the brains of all seven twin pairs; the remaining observer failed to make a correct match in only one of seven pairs. Three of six observers identified the midline sagittal images of the related twins in all seven pairs, and the other three identified the related midline sagittal images in five of seven pairs. The results were statistically significant. CONCLUSION: Although the observed differences in morphologic characteristics between twins necessarily reflect nongenetic influences, the cortical patterns and midline structures of monozygotic twins probably are genetically similar.