To review the dynamic analytical elements used in the functional assessment of the stomatognathic system, summarize the available scientific evidence, and consider interrelations with body posture and cognition.A thorough literature search was conducted using PubMed, the Cochrane Library database, and Google Scholar. Peer-reviewed articles and literature reviews provided up-to-date information addressing three topics: (a) the available knowledge and recent evidence on the relationship between the morphologic aspects of dental/craniofacial anatomy and oral function/dysfunction, (b) mandibular dynamics, considering mobility, functional activity, and existing methodologies of analysis, and (c) a possible correlation between the stomatognathic system, body posture, and cognition.Modern dentistry may be regarded as a human adaptation strategy, helping to conserve healthy teeth for much longer without risking overall health. It is futile to treat patients using a mechanistic, sectorial approach that misrepresents patient behavior and requests, just as it is to affirm the absence of any structure-function relationships. However, it is also evident that there is a lack of general consensus on the precise functional assessment of the stomatognathic system, mostly due to the methodologic heterogeneity employed and the high risk of bias. Despite the abundant evidence produced with the aim of providing solid arguments to define dynamic models of functional assessment of the stomatognathic system, it is yet to become highly empirical, based as it is on operator experience in daily clinical practice.Further efforts from the scientific and clinical community, with the help of progress in technology, remain should this gap be filled and should substantial data on differences between pathologic and physiologic dynamic models of function be provided. Dentistry needs to employ - on a larger scale - objective, dynamic methods of analysis for the functional evaluation of the stomatognathic system, embracing concepts of "personalized medicine" and "interprofessional collaborations."
This paper presents the second-place methodology in the Volvo Discovery Challenge at ECML-PKDD 2024, where we used Long Short-Term Memory networks and pseudo-labeling to predict maintenance needs for a component of Volvo trucks. We processed the training data to mirror the test set structure and applied a base LSTM model to label the test data iteratively. This approach refined our model's predictive capabilities and culminated in a macro-average F1-score of 0.879, demonstrating robust performance in predictive maintenance. This work provides valuable insights for applying machine learning techniques effectively in industrial settings.
The cranial portion of the vertebral segment together with the atlanto-occipital joint represents a very complex area. Since this system could be influenced by different atlas and mandibular position, the aim of this work was to assess atlanto-axial and mandibular rotation. Scanora 3-dimensional cone bean computed tomography images from 205 patients without signs or symptoms of temporomandibular disorder were evaluated. Using a digitalized images analyzer, the axial rotations of atlas and mandible rotation were calculated, measuring the angle with respect to the frontal plane. The same direction for the axial rotation of the mandible and for the atlanto-axial rotation (consistent group) was observed in 80.98% of the patients; opposite directions (inconsistent group) were observed in 19.02%. Among the consistent group, the left rotation was observed in 71.08% of the patients and the right rotation in 28.92%. Absolute values showed a more marked rotation for atlas than mandible and higher values for the left rotation were reported for both.Taking together these data represents important starting points for the knowledge of atlas and mandible relationship and its functional and clinical implication.
We introduce a novel computational unit for neural networks that features multiple biases, challenging the traditional perceptron structure. This unit emphasizes the importance of preserving uncorrupted information as it is passed from one unit to the next, applying activation functions later in the process with specialized biases for each unit. Through both empirical and theoretical analyses, we show that by focusing on increasing biases rather than weights, there is potential for significant enhancement in a neural network model's performance. This approach offers an alternative perspective on optimizing information flow within neural networks. See source code at https://github.com/CuriosAI/dac-dev.
Analysis of the relationship between taxes and self-employment should account for the interplay between responses in self-employment and wage employment. To this end, we estimate a two-state multi-spell duration model which accounts for both observed and unobserved heterogeneity using a large longitudinal administrative dataset for Norway for 1993 to 2011. Our findings confirm theoretical predictions, and are robust to various changes to definitions and sample selections. A policy experiment simulating a flatter tax schedule in the year 2000 is found to encourage self-employment, delivering a net increase of predicted inflow into self-employment from 2.8% to 5.3%.
We introduce a novel computational unit for neural networks that features multiple biases, challenging the traditional perceptron structure. This unit emphasizes the importance of preserving uncorrupted information as it is passed from one unit to the next, applying activation functions later in the process with specialized biases for each unit. Through both empirical and theoretical analyses, we show that by focusing on increasing biases rather than weights, there is potential for significant enhancement in a neural network model's performance. This approach offers an alternative perspective on optimizing information flow within neural networks. See source code [5].
Analysis of the relationship between taxes and self-employment should account for the interplay between responses in self-employment and wage employment. To this end, we estimate a two-state multi-spell duration model which accounts for both observed and unobserved heterogeneity using a large longitudinal administrative dataset for Norway for 1993 to 2011. Our findings confirm theoretical predictions, and are robust to various changes to definitions and sample selections. A policy experiment simulating a flatter tax schedule in the year 2000 is found to encourage self-employment, delivering a net increase of predicted inflow into self-employment from 2.8% to 5.3%.
A Smoluchowski type model of coagulation in a turbulent fluid is given, first expressed by means of a stochastic model, then in a suitable scaling limit as a deterministic model with enhanced diffusion in the velocity component. A precise link between mean intensity of the turbulent velocity field and coagulation enhancement is obtained by numerical simulations, and a formula for the mean velocity difference, in agreement with the gas-kinetic model, is proved by a new method.
Among novel technologies for producing electricity from renewable resources, a new class of wind energy converters has been conceived under the name of Airborne Wind Energy Systems (AWESs). This new generation of systems employs flying tethered wings or aircraft in order to reach winds blowing at atmosphere layers that are inaccessible by traditional wind turbines. Research on AWESs started in the mid seventies, with a rapid acceleration in the last decade. A number of systems based on radically different concepts have been analyzed and tested. Several prototypes have been developed all over the world and the results from early experiments are becoming available. This paper provides a review of the different technologies that have been conceived to harvest the energy of high-altitude winds, specifically including prototypes developed by universities and companies. A classification of such systems is proposed on the basis of their general layout and architecture. The focus is set on the hardware architecture of systems that have been demonstrated and tested in real scenarios. Promising solutions that are likely to be implemented in the close future are also considered.
A Smoluchowski type model of coagulation in a turbulent fluid is given, first expressed by means of a stochastic model, then in a suitable scaling limit as a deterministic model with enhanced diffusion in the velocity component. A precise link between mean intensity of the turbulent velocity field and coagulation enhancement is obtained by numerical simulations, and a formula for the mean velocity difference, in agreement with the gas-kinetic model, is proved by a new method.
