Air pollution has been associated with several health problems. Detecting and measuring the concentration of harmful pollutants present in complex air mixtures has been a long-standing challenge, due to the intrinsic difficulty of distinguishing among these substances from interferent species and environmental conditions, both indoor and outdoor. Despite all efforts devoted by the scientific and industrial communities to tackling this challenge, the availability of suitable device technologies able to selectively discriminate these pollutants present in the air at minute, yet dangerous, concentrations and provide a quantitative measure of their concentrations is still an unmet need. Thermal conductivity detectors (TCDs) show promising characteristics that make them ideal gas sensing tools capable of recognising different gas analytes based on their physical fingerprint characteristics at the molecular level, such as their density, thermal conductivity, dynamic viscosity, and others. In this paper, the operation of TCD gas sensors is presented and explored using a finite element simulation of Joule heating in a sensing electrode placed in a gas volume. The results obtained show that the temperature, and hence, the resistance of the individual suspended microbridge sensor device, depends on the surrounding gas and its thermal conductivity, while the sensitivity and power consumption depend on the properties of the constitutive metal. Moreover, the electrode resistance is proven to be linearly dependent on the applied voltage.

The fallopian tubes play an important role in human fertility by facilitating the spermatozoa passage to the oocyte as well as later actively facilitating the fertilized oocyte transportation to the uterus cavity. The fallopian tubes undergo changes involving biological, physical, and morphological processes due to women aging, which may impair fertility. Here, we have modelled fallopian tubes of women at different ages and evaluated the chances of normal and pathological sperm cells reaching the fertilization site, the ampulla. By utilizing a unique combination of simulative tools, we implemented dynamic three-dimensional (3D) detailed geometrical models of many normal and pathological sperm cells swimming together in 3D geometrical models of three fallopian tubes associated with different women\'s age groups. By tracking the sperm cell swim, we found that for all age groups, the number of normal sperm cells in the ampulla is the largest, compared with the pathological sperm cells. On the other hand, the number of normal sperm cells in the fertilization site decreases due to the morphological and mechanical changes that occur in the fallopian tube with age. Moreover, in older ages, the normal sperm cells swim with lower velocities and for shorter distances inside the ampulla toward the ovary. Thus, the changes that the human fallopian tube undergoes due to women\'s aging have a significant influence on the human sperm cell motility. Our model of sperm cell motility through the fallopian tube in relation to the woman\'s age morphological changes provides a new scope for the investigation and treatment of diseases and infertility cases associated with aging, as well as a potential personalized medicine tool for evaluating the chances of a natural fertilization per specific features of a man\'s sperm and a woman\'s reproductive system.

BACKGROUND: In dermatology, inflammatory skin conditions impose a substantial burden worldwide, with existing therapies showing limited efficacy and side effects. This report aims to compare a novel immunological activation induced by hyperthermic 20 MHz high intensity focused ultrasound (HIFU) with conventional cryotherapy. The bioeffects from the two methods are initially investigated by numerical models, and subsequently compared to clinical observations after treatment of a patient with the inflammatory disease granuloma annulare (GA).
METHODS: Clinical responses to moderate energy HIFU and cryotherapy were analysed using numerical models. HIFU-induced pressure and heat transfer were calculated, and a three-layer finite element model simulated temperature distribution and necrotic volume in the skin. Model output was compared to 22 lesions treated with HIFU and 10 with cryotherapy in a patient with GA.
RESULTS: Cryotherapy produced a necrotic volume of 138.5 mm3 at - 92.7 °C. HIFU at 0.3-0.6 J/exposure and focal depths of 0.8 or 1.3 mm generated necrotic volumes up to only 15.99 mm3 at temperatures of 68.3-81.2 °C. HIFU achieved full or partial resolution in all treated areas, confirming its hyperthermic immunological activation effect, while cryotherapy also resolved lesions but led to scarring and dyspigmentation.
CONCLUSIONS: Hyperthermic immunological activation of 20 MHz HIFU shows promise for treating inflammatory skin conditions as exemplified by GA. Numerical models demonstrate minimal skin necrosis compared to cryotherapy. Suggested optimal HIFU parameters are 1.3 mm focal depth, 0.4-0.5 J/exposure, 1 mm spacing, and 1 mm margin. Further studies on GA and other inflammatory diseases are recommended.

This study aims to analyse, using a finite element analysis, the effects of Ti-base abutment height on the distribution and magnitude of transferred load and the resulting bone microstrain in the bone-implant system. A three-dimensional bone model of the mandibular premolar section was created with an implant placed in a juxta-osseous position. Three prosthetic models were designed: a 1 mm-high titanium-base (Ti-base) abutment with an 8 mm-high cemented monolithic zirconia crown was designed for model A, a 2 mm-high Ti-base abutment with a 7 mm-high crown for model B, and a 3 mm-high abutment with a 6 mm-high crown for model C. A static load of 150 N was applied to the central fossa at a six-degree angle with respect to the axial axis of the implant to evaluate the magnitude and distribution of load transfer and microstrain. The results showed a trend towards a direct linear association between the increase in the height of the Ti-base abutments and the increase in the transferred stress and the resulting microstrain to both the prosthetic elements and the bone/implant system. An increase in transferred stress and deformation of all elements of the system, within physiological ranges, was observed as the size of the Ti-base abutment increased.

Electrical impedance spectroscopy (EIS) has been proposed as a promising noninvasive method to differentiate healthy thyroid from parathyroid tissues during thyroidectomy. However, previously reported similarities in the in vivo measured spectra of these tissues during a pilot study suggest that this separation may not be straightforward. We utilise computational modelling as a method to elucidate the distinguishing characteristics in the EIS signal and explore the features of the tissue that contribute to the observed electrical behaviour. Firstly, multiscale finite element models (or \'virtual tissue constructs\') of thyroid and parathyroid tissues were developed and verified against in vivo tissue measurements. A global sensitivity analysis was performed to investigate the impact of physiological micro-, meso- and macroscale tissue morphological features of both tissue types on the computed macroscale EIS spectra and explore the separability of the two tissue types. Our results suggest that the presence of a surface fascia layer could obstruct tissue differentiation, but an analysis of the separability of simulated spectra without the surface fascia layer suggests that differentiation of the two tissue types should be possible if this layer is completely removed by the surgeon. Comprehensive in vivo measurements are required to fully determine the potential for EIS as a method in distinguishing between thyroid and parathyroid tissues.

Self-healing cementitious materials containing microcapsules filled with healing agents can autonomously seal cracks and restore structural integrity. However, optimising the microcapsule mechanical properties to survive concrete mixing whilst still rupturing at the cracked interface to release the healing agent remains challenging. This study develops an integrated numerical modelling and machine learning approach for tailoring acrylate-based microcapsules for triggering within cementitious matrices. Microfluidics is first utilised to produce microcapsules with systematically varied shell thickness, strength, and cement compatibility. The capsules are characterised and simulated using a continuum damage mechanics model that is able to simulate cracking. A parametric study investigates the key microcapsule and interfacial properties governing shell rupture versus matrix failure. The simulation results are used to train an artificial neural network to rapidly predict the triggering behaviour based on capsule properties. The machine learning model produces design curves relating the microcapsule strength, toughness, and interfacial bond to its propensity for fracture. By combining advanced simulations and data science, the framework connects tailored microcapsule properties to their intended performance in complex cementitious environments for more robust self-healing concrete systems.

This paper reports results of laboratory and 3D numerical modeled pull-out tests with steel ladders and polymeric strip reinforcements. These types of reinforcement are commonly used in reinforced soil walls constructed with concrete facing elements. Laboratory pull-out tests are required to determine accurate and realistic pull-out strength values considering the interaction of specific reinforcement and backfill materials under different confining pressures (i.e., trying to simulate the different reinforcement layer arrangements and load conditions in actual reinforced soil walls). International design Codes for reinforced soil walls provide default values for pull-out strength. However, in many cases, default values are too conservative and/or are not strictly specified for particular reinforcement types. Pull-out tests can be difficult and expensive to perform, thus not being common nor worth for the vast majority of reinforced soil wall projects. Consequently, calibrated numerical models can be useful to predict pull-out response under site-specific conditions, and provide further understanding of the mechanisms involved in the soil-reinforcement interaction. Details of the numerical approach, including relevant aspects of the soil-reinforcement interfaces, are described. Examples of calibrated numerical predictions for pull-out loads, displacements, and soil-dilatancy effects are presented. The influence of reinforcement, soil and interface stiffnesses is shown. Numerical results provide useful insight for future modelling works of the complex interaction between type-specific backfill materials and reinforcement element, relevant for investigation and/or practical design of reinforced soil walls.

The process of lens shape change in the eye to alter focussing (accommodation) is still not fully understood. Modelling approaches have been used to complement experimental findings in order to determine how constituents in the accommodative process influence the shape change of the lens. An unexplored factor in modelling is the role of the modelling software on the results of simulated shape change. Finite element models were constructed in both Abaqus and Ansys software using biological parameters from measurements of shape and refractive index of two 35-year-old lenses. The effect of zonular insertion on simulated shape change was tested on both 35-year-old lens models and with both types of software. Comparative analysis of shape change, optical power, and stress distributions showed that lens shape and zonular insertion positions affect the results of simulated shape change and that Abaqus and Ansys show differences in their respective models. The effect of the software package used needs to be taken into account when constructing finite element models and deriving conclusions.

Carbon fiber-reinforced composites are popular due to their high strength and light weight; thus, the structures demonstrate high performance and specific strength. However, these composites are susceptible to impact damage. The objective of this research was to study the behavior of carbon fiber-reinforced laminates based on a polyetheretherketone (PEEK) matrix with six stacking sequences under static and impact loading. Four-point bending, short-beam bending, drop weight impact, and compression after impact tests were carried out. The results were complemented with digital shearography to estimate the damaged areas. Finite element modeling served to assess the failure mechanisms, such as fiber and matrix failure, in different layers due to tension of compression. Three behavior pattern of layups under drop-weight impact were found: (i)-energy redistribution due to mostly linear behavior (like a trampoline) and thus lower kinetic energy absorption for damage initiation, (ii)-moderate absorption of energy with initiation and propagation of concentrated damage with depressed redistribution of energy in the material, (iii)-moderate energy absorption with good redistribution due to initiation of small, dispersed damage. The results can be used to predict the mechanical behavior of composites with different stacking sequences in materials for proper structural design.

Lightweight component design is effectively achievable through sandwich structures; many past research studies in the aerospace and racing sectors (since the 1920s) have proven it. To extend their application into the automotive and other transport industries, manufacturing cycle times must be reduced. This can be achieved by sandwich materials made of continuous fibre-reinforced thermoplastic (CFRTP) cover layers and thermoplastic honeycomb cores. To widen the application of flat thermoplastic-based sandwich panels into complex parts, a novel forming technology was developed by the Fraunhofer Institute of Microstructure of Materials and Systems (IMWS). Manufacturing defects like wrinkling and surface waviness should be minimised to achieve high reproducibility of the sandwich components. Studying different manufacturing parameters and their influence on the final part is complex and challenging to analyse through experiments, as it is time-consuming. Therefore, a finite element (FE) modelling approach is implemented to reduce such efforts. Initially, a thermoforming model is developed and validated with experimental results to check its reliability. Further, different simulations are performed to optimise the novel sandwich-forming process. In this study, a thermoplastic sandwich made of polypropylene (PP) honeycomb core and polypropylene glass fibre (PP/GF) cross-ply as cover layers was used, and its numerical model was executed in LS-DYNA software release R11.2.1.