Materialise (Belgium)

Edibles insects are considered as one of the promising future foods due to its environmental and nutritional sustainability. As like many western countries edible insects are not part of the traditional diet in Bangladesh. This research was conducted in Bangladesh to assess the knowledge and attitude of the citizens towards entomophagy. The data were obtained by a questionnaire through a pencil-paper and face to face interview method ( n = 1014). Results showed that the education level of the respondents was the most predominant factor determining knowledge, disgust sensitivity and willingness to eat insects or insects-based food. Disgust sensitivity is one of the predominant barriers to entomophagy and also halalness was an important factor for the Muslim population. However, respondents having knowledge of entomophagy were open to eat insects or insects-based foods, but from the cluster analysis there was no clustering by social-demographic characteristics observed. Food neophobia of the participants was significantly influenced by all the sociodemographic factors except for gender. Young adults with higher education had lower food neophobia compared to the older adult with lower education level. This survey also confirmed that higher food neophobia was associated with higher disgust sensitivity and lower willingness to eat insects or insects-based food. • First survey in Bangladesh on the consumer attitudes towards entomophagy. • Half of the participants are positive to edible insects if it is halal. • Education level is a key driver to willingness to eat insects or insects based food. • Food neophobia negatively influence willingness to eat insects or insects-based food.

PurposeComputer-aided navigation and patient-specific 3D printed guides have demonstrated superior outcomes in total shoulder arthroplasty (TSA). Nevertheless, few TSAs are inserted using these technologies. Head-worn augmented reality (AR) devices can provide intuitive 3D computer navigation to the surgeon. This study investigates AR navigation in conjunction with adaptive spatial drift correction toward TSA.MethodsA phantom study was performed to assess the performance of AR navigated pin placement in TSA. Two medical experts performed a total of 12 pin placements into phantom scapula; six were placed using an end-to-end AR-navigated technique, and six using a common freehand technique. Inside-out infrared (IR) tracking was designed and integrated into the AR headset to correct for device drift and provide tool tracking. Additionally, the impact of IR tool tracking, registration, and superposed/juxtaposed visualization techniques was investigated.ResultsThe AR-navigated pin placement resulted in a mean entry point error of 1.06 mm ± 0.64 mm and directional error of {1.66^circ pm 0.65^circ }. Compared with the freehand technique, AR navigation resulted in improved directional outcomes (p=0.03), while entry point accuracy was not significantly different (p=0.44). IR tool tracking error was 1.47 mm ± 0.69 mm and {0.92^circ pm 0.50^circ }, and registration error was 4.32 mm ± 1.75 mm and {2.56^circ pm 0.82^circ }. No statistical difference between AR visualization techniques was found in entry point (p=0.22) or directional (p=0.31) errors.ConclusionAR navigation allowed for comparable pin placement outcomes with those reported in the literature for patient-specific 3D printed guides; moreover, it complements the patient-specific planning without the need for the guides themselves.

This paper addresses the parameter estimation of single-input, single-output block-oriented models, namely Hammerstein, Wiener, and Wiener-Hammerstein (WH), using the Volterra series. These models inherently possess a structural prior on the parameters, which is used in the Volterra kernel estimation. The paper demonstrates how this prior-informed Volterra kernel plays a key role in estimating the block-model parameters, effectively serving as a comprehensive tensor encompassing the model parameters within various system configurations. These kernel estimates are further refined in the parameter space of the block models, facilitating the extraction of linear block parameters and enhancing interpretability. Simulation and experimental studies on electrical systems and real-world chemical processes validate the robustness of the method against noise and its ability to capture the dynamics of the system. Compared to the classical Volterra model, the proposed approach significantly reduces model complexity, particularly in Hammerstein and WH models, while maintaining or improving output prediction accuracy and parameter recovery, even under noise. On simulated data, the method reliably retrieves block parameters with performance comparable to black-box models. On measured data from block-oriented systems, including a WH benchmark, it achieves competitive accuracy using fewer parameters. For benchmark data from process industry systems without assumed structure, the Wiener model matches black-box prediction errors with fewer parameters and lower computation times.

A metal 3D-printed high performance multi-jet impingement cooling solution for enabling thermal management of power electronics is presented for integration in electric vehicles. In this paper, we describe the concept, metal additive manufacturing and assembling to demonstrate the proof-of-concept of direct liquid jet impingement cooling of mock-up power modules dissipating heat loss up to 400 W (~230 W/cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>).

Preoperative determination of implant size for total knee arthroplasty surgery has numerous clinical and logistical benefits. Currently, surgeons use X-ray-based templating to estimate implant size, but this method has low accuracy. Our study aims to improve accuracy by developing a machine learning approach that predicts the required implant size based on a 3D femoral bone mesh, the key factor in determining the correct implant size. A linear regression framework imposing group sparsity on the 3D bone mesh vertex coordinates was proposed based on a dataset of 446 MRI scans. The group sparse regression method was further regularized based on the connectivity of the bone mesh to enforce neighbouring vertices to have similar importance to the model. Our hypergraph regularized group lasso had an accuracy of 70.1% in predicting femoral implant size while the initial implant size prediction provided by the instrumentation manufacturer to the surgeon has an accuracy of 23.1%. Furthermore, our method was capable of predicting the implant size up to one size smaller or larger with an accuracy of 99.1%, thereby surpassing other state-of-the-art methods. The hypergraph regularized group lasso was able to obtain a significantly higher accuracy compared to the implant size prediction provided by the instrumentation manufacturer.

L’enjeu de cet article est d’examiner le thème du féminicide dans la littérature française au XIXe siècle. Dans La Fille aux yeux d’or et La Duchesse de Langeais, où Balzac projette son rêve de l’Orient, le héros dispose de la vie de son amante en tant que maître absolu de celle-ci. Les femmes sont censées admirer la force des hommes et accepter leur violence. Par contre, l’Indiana de George Sand dénonce la violence masculine comme un crime. Tandis que dans la littérature romantique le thème du féminicide est teinté d’exotisme, dans la littérature naturaliste ce thème devient plus proche de la réalité. Dans La Bête humaine, Zola met en scène plusieurs personnages criminels. Bien qu’il exploite des faits divers et des références scientifiques telles que les idées de Lombroso, Zola s’en différencie par ses propres notions sociales et esthétiques. Ainsi, cet article met en évidence le fait que ce thème du féminicide est imprégné du désir et de la peur des hommes envers les femmes, aussi bien que de leur appétit de domination.

The surgical management of proximal humeral fractures remains challenging. Anatomical reduction of the fracture has been reported as the keystone for a sufficient surgical fixation and successful outcome. However, mostly there is no example of its premorbid state. Literature suggests that the mirrored contralateral side can be used as a reconstruction template. But is this a correct technique to use? The purpose of this study is to define anatomical variation between humeri based on gender and side comparison. Two different statistical shape models of the humerus were created and their modes of variation were described. One model contained 110 unpaired humeri. The other model consisted of 65 left and corresponding right humeri. The compactness of the statistical shape model containing 110 humeri showed that two principal components explain more than 95% of the variation and the generalization showed that a random humerus can be described with an accuracy of 0.39mm. For only three parameters, statistically significant differences were observed between left and right. However, comparing the mean of the different metrics on the humeri of men and women, almost all were significant. Since there were only small differences between left and right humeri, using the mirrored contralateral side as a reconstruction template for fracture reduction can be defended. The variable anatomy between men and women could explain why locking plates not always fit to the bone.

ABSTRACT Mitral valve disease is a commonly occurring pathology and its incidence is expected to rise in the coming decades. This has led to an increase in the number and complexity of computational models developed to characterize the mitral valve behaviour, resulting in the need for automated segmentation methods. In this study, we evaluated the suitability of particle systems for segmenting the mitral valve leaflets from 3D TOE images, for both systolic and diastolic phases. With a mean error of 0.77 ± 0.4 mm, our approach results in accurate medial surface representations of the mitral valve. Additionally, we investigated the correlation between particle strength and leaflet thickness. Although a thorough analysis is still required to fully establish this relation, our preliminary results, with a mean RMS error of 0.99 ± 0.27 mm, show that leaflet thickness can be linked to particle strength. We anticipate that particle systems can be of high relevance for the generation of realistic patient-specific computational models, contributing to the development of adequate treatment strategies for mitral valve patients.

sponsorship: S.D. has received a postdoctoral fellowship (12Z8622N) from Research Foundation Flanders (FWO). (Research Foundation Flanders (FWO)|12Z8622N)