Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Ergonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in-depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA-TLX) are ready to use in certain applications. Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.     

Precipitous weakening of quartz at the α–β phase inversion

Crystalline quartz has long been identified as among the weakest of abundant crustal minerals. This weakness is particularly evident around the α–β phase inversion at 573°C, in which Si–O bonds undergo a displacive structural transformation from trigonal to hexagonal symmetry. Here we present data using indentation testing methodologies that highlight the precipitous extent of the transformational weakening. Although the indentations are localized over relatively small specimen contact areas, the data quantify the essential deformation and fracture properties of quartz in a predominantly (but not exclusively) compressive stress field, at temperatures and pressures pertinent to conditions in the earth's crust.     

Emerging applications of nanotechnologies to probiotics and prebiotics

Fervid interests on nanoparticles are increasing within the scientific and non-scientific communities, as they are utilised in food and non-food applications. The versatility of emerging applications of nanoparticles makes them potentially harmful to the food, healthcare and environment sectors, and thus necessitates the development of nanonutraceuticals from nutritional substances such as antioxidants, vitamins, fatty acids, fibres, probiotics and prebiotics. This review excavated state of the art on nanotechnology applications such as gold and selenium particles, nanolayers, nanobeads, nanoemulsions and nanofibers to probiotics and prebiotics for the synthesis of anticancer, antimicrobial, antioxidant and photo-reactive products among others, and finally delved into other noteworthy considerations like safety. It is concluded that available literature on the current status of nanoprobiotics and prebiotics are exhaustive, despite their huge potentials and applications.     

Steerable Microinvasive Probes for Localized Drug Delivery to Deep Tissue

Enhanced understanding of neuropathologies has created a need for more advanced tools. Current neural implants result in extensive glial scarring and are not able to highly localize drug delivery due to their size. Smaller implants reduce surgical trauma and improve spatial resolution, but such a reduction requires improvements in device design to enable accurate and chronic implantation in subcortical structures. Flexible needle steering techniques offer improved control over implant placement, but often require complex closed‐loop control for accurate implantation. This study reports the development of steerable microinvasive neural implants (S‐MINIs) constructed from borosilicate capillaries (OD = 60 µm, ID = 20 µm) that do not require closed‐loop guidance or guide tubes. S‐MINIs reduce glial scarring 3.5‐fold compared to prior implants. Bevel steered needles are utilized for open‐loop targeting of deep‐brain structures. This study demonstrates a sinusoidal relationship between implant bevel angle and the trajectory radius of curvature both in vitro and ex vivo. This relationship allows for bevel‐tipped capillaries to be steered to a target with an average error of 0.23 mm ± 0.19 without closed‐loop control. Polished microcapillaries present a new microinvasive tool for chronic, predictable targeting of pathophysiological structures without the need for closed‐loop feedback and complex imaging.     

Effect of Silicon Inclusion Carbonaceous Composite Particulate on the Thermal-Ageing Characteristics and Mechanical Performance of Low Carbon Steel

Silicon - This study focus on the effects of silicon inclusion carbonaceous particulate on the hardness and microstructural properties of carburized low carbon steel, at constant temperature of...     

Computer-based engineering of thermostabilized antibody fragments

We used the molecular modeling program Rosetta to identify clusters of amino acid substitutions in antibody fragments (scFvs and scAbs) that improve global protein stability and resistance to thermal deactivation. Using this methodology, we increased the melting temperature (T_m) and resistance to heat treatment of an antibody fragment that binds to the Clostridium botulinum hemagglutinin protein (anti-HA33). Two designed antibody fragment variants with two amino acid replacement clusters, designed to stabilize local regions, were shown to have both higher T_m compared to the parental scFv and importantly to retain full antigen binding activity after 2 hr of incubation at 70°C. The crystal structure of one thermostabilized scFv variants was solved at 1.6 Å and shown to be in close agreement with the RosettaAntibody model prediction.     

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient''s disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [¹⁸F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning.     

Mixed-Metal MOF-74 Templated Catalysts for Efficient Carbon Dioxide Capture and Methanation

The vast chemical and structural tunability of metal–organic frameworks (MOFs) are beginning to be harnessed as functional supports for catalytic nanoparticles spanning a range of applications. However, a lack of straightforward methods for producing nanoparticle-encapsulated MOFs as efficient heterogeneous catalysts limits their usage. Herein, a mixed-metal MOF, NiMg-MOF-74, is utilized as a template to disperse small Ni nanoclusters throughout the parent MOF. By exploiting the difference in Ni O and Mg O coordination bond strength, Ni²⁺ is selectively reduced to form highly dispersed Ni nanoclusters constrained by the parent MOF pore diameter, while Mg²⁺ remains coordinated in the framework. By varying the ratio of Ni to Mg in the parent MOF, accessible surface area and crystallinity can be tuned upon thermal treatment, influencing CO₂ adsorption capacity and hydrogenation selectivity. The resulting Ni nanoclusters prove to be an active catalyst for CO₂ methanation and are examined using extended X-ray absorption fine structure and X-ray photoelectron spectroscopy. By preserving a segment of the Mg²⁺-containing MOF framework, the composite system retains a portion of its CO₂ adsorption capacity while continuing to deliver catalytic activity. The approach is thus critical for designing materials that can bridge the gap between carbon capture and CO₂ utilization.