Evaluation of the auto surfacing methods to create a surface body of the mandible model

Designing an anatomical structure for a surgical procedure is not a simple task. It is especially true of the craniofacial area, which consists of bone tissues with very complex geometry. CAD modelers need appropriate knowledge and skills in medicine and technical sciences to fully use the currently available tools in related processes with the reconstruction of the craniofacial areas. The presented preliminary studies are based on four patients treated at the Department of Maxillofacial Surgery. The segmentation process of the mandible model was performed in the ITK SNAP software. The process of generating surface body models was performed in the Auto Surfacing module in Geomagic software using two different methods: organic and mechanical. Then compare both methods for the accuracy of generating a CAD model of the mandible based on a triangle mesh structure in the Focus Inspection and the GOM Inspect software.

Perspectives on manufacturing simulations of Li-S battery cathodes

Lithium-Sulfur Batteries (LSBs) are one of the main contenders for next generation post lithium-ion batteries. As the process of scientific discovery advances, many of the challenges that prevent the commercial deployment of LSBs, specially at the most fundamental materials level, are slowly being addressed. However, batteries are complex systems that require not only from identifying suitable materials, but also from knowing how to assemble and manufacture all the components together in order to obtain an optimally working battery. This is not a simple task, as battery manufacturing is a multi-stepped, multi-parameter, highly correlated process, where many parameters compete, and deep knowledge of the systems is required in order to achieve the optimal manufacturing conditions, which has already been shown in the case of Lithium-Ion Batteries (LIBs). In these regards, manufacturing simulations have proven to be invaluable in order to advance in the knowledge of this exciting and technologically relevant field. Thus, in this work, we aim at providing future perspectives and opportunities that we think are interesting in order to create digital twins for the LSB manufacturing process. We also provide comprehensive and realistic ways in which already existing models could be adapted to LSBs in the short-term, and which are the challenges that might be found in the way.

Humans optimally anticipate and compensate for an uneven step during walking

The simple task of walking up a sidewalk curb is actually a dynamic prediction task. The curb is a disturbance that could cause a loss of momentum if not anticipated and compensated for. It might be possible to adjust momentum sufficiently to ensure undisturbed time of arrival, but there are infinite possible ways to do so. Much of steady, level gait is determined by energy economy, which should be at least as important with terrain disturbances. It is, however, unknown whether economy also governs walking up a curb, and whether anticipation helps. Here we show that humans compensate with an anticipatory pattern of forward speed adjustments, predicted by a criterion of minimizing mechanical energy input. The strategy is mechanistically predicted by optimal control for a simple model of bipedal walking dynamics, with each leg's push-off work as input. Optimization predicts a tri-phasic trajectory of speed (and thus momentum) adjustments, including an anticipatory phase. In experiment, human subjects ascend an artificial curb with the predicted tri-phasic trajectory, which approximately conserves overall walking speed relative to undisturbed flat ground. The trajectory involves speeding up in a few steps before the curb, losing considerable momentum from ascending it, and then regaining speed in a few steps thereafter. Descending the curb entails a nearly opposite, but still anticipatory, speed fluctuation trajectory, in agreement with model predictions that speed fluctuation amplitudes should scale linearly with curb height. The fluctuation amplitudes also decrease slightly with faster average speeds, also as predicted by model. Humans can reason about the dynamics of walking to plan anticipatory and economical control, even with a sidewalk curb in the way.

Spanish L2 Chinese Learners’ Awareness of Morpho-Syntactic Structures in the Reading Comprehension of Splittable Compounds

Reading comprehension is never considered a simple task in linguists’ views as it requires a full set of linguistic knowledge, such as word decoding, understanding syntactic and morphological structures, and deriving proper meanings from these structures in a given context. Bearing the simple view of reading, the primary goal of this study is to explore whether the split presentation of Chinese splittable compounds influences the recognition of the compounds in second language (L2) Chinese reading comprehension, and how the reading skills, i.e., word decoding and linguistic comprehension, cooperate to complete this reading comprehension task. Splittable compounds (SCs) in Chinese are typically verbs composed of two constituents with limited separability. The separable property of SCs and their vague morpho-syntactic status are supposed to cause difficulties for L2 Chinese learners in recognizing the compounds. Especially for those whose native language manifests lexical integrity, the split presentation of the compounds may invite the L2 Chinese readers to process them with a mechanism different from that for their non-split forms. To the best of our knowledge, the efforts on investigating this issue are insufficient. In this study, 27 Spanish speaking L2 Chinese learners were invited to complete tasks including reading and interpreting 6 selected SCs in the split and non-split forms, rating their familiarities with each SC and reporting the syntactic category of the SCs based on their existing linguistic knowledge. The results, showed that the split presentation of SCs did cause challenges for L2 Chinese learners in recognizing the compounds in the reading process, regardless of their Chinese proficiencies. The L2 Chinese participants performed significantly worse in recognizing split SCs in salient Verb-Object structures than recognizing those in unsalient Verb-Object structures. These findings underscore the importance of linguistic comprehension in L2 Chinese in-text word reading comprehension and suggest words as the basic processing units.

Impact of Induced Moods, Sensation Seeking, and Emotional Contagion on Economic Decisions Under Risk

In addition to probabilities of monetary gains and losses, personality traits, socio-economic factors, and specific contexts such as emotions and framing influence financial risk taking. Here, we investigated the effects of joyful, neutral, and sad mood states on participants’ risk-taking behaviour in a simple task with safe and risky options. We also analysed the effect of framing on risk taking. In different trials, a safe option was framed in terms of either financial gains or losses. Moreover, we investigated the effects of emotional contagion and sensation-seeking personality traits on risk taking in this task. We did not observe a significant effect of induced moods on risk taking. Sad mood resulted in a slight non-significant trend of risk aversion compared to a neutral mood. Our results partially replicate previous findings regarding the presence of the framing effect. As a novel finding, we observed that participants with a low emotional contagion score demonstrated increased risk aversion during a sad mood and a similar trend at the edge of significance was present in high sensation seekers. Overall, our results highlight the importance of taking into account personality traits of experimental participants in financial risk-taking studies.

A New Biomedical Image Denoising Method Using an Adaptive Multi-resolution Technique

In the world of digital image processing, image denoising plays a vital role, where the primary objective was to distinguish between a clean and a noisy image. However, it was not a simple task. As a consequence of everyone's understanding of the practical challenge, a variety of methods have been presented during the last few years. Of those, wavelet transformer-based approaches were the most common. But wavelet-based methods have their own limitations in image processing applications like shift sensitivity, poor directionality, and lack of phase information, and they also face difficulties in defining the threshold parameters. As a result, this study provides an image de-noising approach based on Bi-dimensional Empirical Mode Decomposition (BEMD). This project's main purpose is to disintegrate noisy images based on their frequency and construct a hybrid algorithm that uses existing de-noising techniques. This approach decomposes the noisy picture into numerous IMFs with residue, which were subsequently filtered independently based on their specific properties. To quantify the success of the proposed technique, a comprehensive analysis of the experimental results of the benchmark test images was conducted using several performance measurement matrices. The reconstructed image was found to be more accurate and pleasant to the eye, outperforming state-of-the-art denoising approaches in terms of PSNR, MSE, and SSIM.

Effects of Daytime Electric Light Exposure on Human Alertness and Higher Cognitive Functions: A Systematic Review

This paper reports the results of a systematic review conducted on articles examining the effects of daytime electric light exposure on alertness and higher cognitive functions. For this, we selected 59 quantitative research articles from 11 online databases. The review protocol was registered with PROSPERO (CRD42020157603). The results showed that both short-wavelength dominant light exposure and higher intensity white light exposure induced alertness. However, those influences depended on factors like the participants’ homeostatic sleep drive and the time of day the participants received the light exposure. The relationship between light exposure and higher cognitive functions was not as straightforward as the alerting effect. The optimal light property for higher cognitive functions was reported dependent on other factors, such as task complexity and properties of control light. Among the studies with short-wavelength dominant light exposure, ten studies (morning: 3; afternoon: 7) reported beneficial effects on simple task performances (reaction time), and four studies (morning: 3; afternoon: 1) on complex task performances. Four studies with higher intensity white light exposure (morning: 3; afternoon: 1) reported beneficial effects on simple task performance and nine studies (morning: 5; afternoon: 4) on complex task performance. Short-wavelength dominant light exposure with higher light intensity induced a beneficial effect on alertness and simple task performances. However, those effects did not hold for complex task performances. The results indicate the need for further studies to understand the influence of short-wavelength dominant light exposure with higher illuminance on alertness and higher cognitive functions.

Effect of Proximity, Burden, and Position on the Power Quality Accuracy Performance of Rogowski Coils

Power quality evaluation is the process of assessing the actual power network parameters with respect to the ideal conditions. However, several new assets and devices among the grid include mining the voltage and current quality. For example, the power converters needed for renewable energy sources’ connection to the grid, electric vehicles, etc., are some of the main sources of disturbances that inject high-frequency components into the grid. Consequently, instrument transformers (ITs) should be capable of measuring distorted currents and voltages with the same level of accuracy guaranteed for the ideal frequency (50–60 Hz). This is not a simple task if one considers that several other influence quantities endlessly act on the ITs. To this purpose, considering the lack of a standard, this work presents a measurement setup and specific tests for testing a commonly used type of low-power current transformer, the Rogowski coil (RC). In particular, the accuracy performance (ratio error and phase displacement) of the RCs was evaluated when measuring distorted signals while other influence quantities affected the RCs. Such quantities included positioning, burden, and magnetic field. The results indicate which quantities (or combination of them) have the greatest effect on the RC’s accuracy performance.

Salutogenic Approaches to Dementia Care

In this chapter, the authors address salutogenic approaches in dementia care support, using a resident-centred model of care. Securing patients’ sense of coherence in care settings requires shifting the locus of decision-making power from only staff, to include residents. In this approach, patients manage more tasks themselves, they get not only what they need but also what they want and they engage meaningfully with others and with life in general. The authors explain that implementing salutogenic models of dementia care is not a simple task. It involves reimagining approaches to interpersonal communication, the thoughtful development of meaningful and enjoyable activities, and creative inclusion and engagement of friends and family. Supportive design of facilities includes spaces that provide choice, opportunities for social interaction, and memory-triggering cues that inform persons living with dementia about where they are, who they are, what there is to do to keep occupied, who other people are – in sum, environments that remind them that they are meaningfully engaged, safe and happy. The authors contend that replacing old-fashioned approaches to care with life-affirming environments is richly rewarding. They explain that success in making this switch requires professionals to pivot away from models that see dementia primarily as a disease to be cured, towards seeing living with dementia in terms of maximum health and well-being. They conclude that salutogenesis is a useful theory to guide this transition.

Measuring Interactions in Categorical Datasets Using Multivariate Symmetrical Uncertainty

Interaction between variables is often found in statistical models, and it is usually expressed in the model as an additional term when the variables are numeric. However, when the variables are categorical (also known as nominal or qualitative) or mixed numerical-categorical, defining, detecting, and measuring interactions is not a simple task. In this work, based on an entropy-based correlation measure for n nominal variables (named as Multivariate Symmetrical Uncertainty (MSU)), we propose a formal and broader definition for the interaction of the variables. Two series of experiments are presented. In the first series, we observe that datasets where some record types or combinations of categories are absent, forming patterns of records, which often display interactions among their attributes. In the second series, the interaction/non-interaction behavior of a regression model (entirely built on continuous variables) gets successfully replicated under a discretized version of the dataset. It is shown that there is an interaction-wise correspondence between the continuous and the discretized versions of the dataset. Hence, we demonstrate that the proposed definition of interaction enabled by the MSU is a valuable tool for detecting and measuring interactions within linear and non-linear models.