Analytical treatment of stabilization

We present a summarizing account of a series of investigations whose central topic is to address the question whether atomic stabilization exists in an analytical way. We provide new aspects on several issues of the matter in the theoretical context when the dynamics is described by the Stark Hamiltonian. The main outcome of these studies is that the governing parameters for this phenomenon are the total classical momentum transfer and the total classical displacement. Whenever these two quantities vanish, asymptotically weak stabilization does exist. For all other situations we did not find any evidence for stabilization. We found no evidence that strong stabilization might occur. Our results agree qualitatively with the existing experimental findings

Towards the development of affective facial expression recognition for human-robot interaction

Affective facial expression is a key feature of non-verbal behavior and is considered as a symptom of an internal emotional state. Emotion recognition plays an important role in social communication: human-human and also for human-robot interaction. This work aims at the development of a framework able to recognise human emotions through facial expression for human-robot interaction. Simple features based on facial landmarks distances and angles are extracted to feed a dynamic probabilistic classification framework. The public online dataset Karolinska Directed Emotional Faces (KDEF) [12] is used to learn seven different emotions (e.g. Angry, fearful, disgusted, happy, sad, surprised, and neutral) performed by seventy subjects. Offline and on-the-fly tests were carried out: leave-one-out cross validation tests using the dataset and on-the-fly tests during human-robot interactions. Preliminary results show that the proposed framework can correctly recognise human facial expressions with potential to be used in human-robot interaction scenarios

Finding Out The Neurological Consequences Of Covid-19

t- Introduction: Since the first official case of COVID-19 in China in December 2019, researchers have been trying to uncover the mechanism of action of the severe acute respiratory syndrome Coronavirus 2 (Sars-CoV-2), which attacks several organs in addition to the lungs and causes circulatory changes that can lead to death not only from lung failure but also due to commitment of other organs. Objective: The aim of this study is to find out the neurological consequences of COVID-19. Material and methods: A systematic review of the literature was concretised by mobilizing the descriptors: "Sars-Cov-2", "coronavirus infections" and "Neurological Consequences". Databases were selected and seven articles were included for analysis. Results and discussion: Although the effects of Sars-CoV-2 on the lung are exemplary and frightening, the long-term effects on the nervous system may be greater and even more overwhelming, as the regeneration of nerve tissue is difficult and can lead to general disability, as the nervous system coordinates the functions of the entire body. All studies show the presence of any kind of injury (mild or severe) to Central Nervous System, but some of them highlight the need for further studies to have great certainty. Conclusion: It can be said that the studies all agree on the possibility of existing neurological sequelae and a majority agree on the need for other studies.info:eu-repo/semantics/publishedVersio

Runoff at the micro-plot and slope scale following wildfire, central Portugal

Through their effects on soil properties and vegetation/litter cover, wildfires can strongly enhance overland flow generation and accelerate soil erosion [1] and, thereby, negatively affect land-use sustainability as well as downstream aquatic and flood zones. Wildfires are a common phenomenon in present-day Portugal, devastating in an average year some 100.000 ha of forest and woodlands and in an exceptional year like 2003 over 400.000 ha. There therefore exists a clear need in Portugal for a tool that can provide guidance to post-fire land management by predicting soil erosion risk, on the one hand, and, on the other, the mitigation effectiveness of soil conservation measures. Such a tool has recently been developed for the Western U.S.A. [3: ERMiT] but its suitability for Portuguese forests will need to be corroborated by field observations. Testing the suitability of existing erosion models in recently burned forest areas in Portugal is, in a nutshell, the aim of the EROSFIRE projects. In the first EROSFIRE project the emphasis was on the prediction of erosion at the scale of individual hill slopes. In the ongoing EROSFIRE-II project the spatial scope is extended to include the catchment scale, so that also the connectivity between hill slopes as well as channel and road processes are being addressed. Besides ERMiT, the principal models under evaluation for slope-scale erosion prediction are: (i) the variant of USLE [4] applied by the Portuguese Water Institute after the wildfires of 2003; (ii) the Morgan–Morgan–Finney model (MMF) [5]; (iii) MEFIDIS [6]. From these models, MEFIDIS and perhaps MMF will, after successful calibration at the slope scale, also be applied for predicting catchment-scale sediment yields of extreme events

Human Activity Recognition using Max-Min Skeleton-based Features and Key Poses

Human activity recognition is still a very challenging research area, due to the inherently complex temporal and spatial patterns that characterize most human activities. This paper proposes a human activity recognition framework based on random forests, where each activity is classified requiring few training examples (i.e. no frame-by-frame activity classification). In a first approach, a simple mechanism that divides each action sequence into a fixed-size window is employed, where max-min skeleton-based features are extracted. In the second approach, each window is delimited by a pair of automatically detected key poses, where static and max-min dynamic features are extracted, based on the determined activity example. Both approaches are evaluated using the Cornell Activity Dataset [1], obtaining relevant overall average results, considering that these approaches are fast to train and require just a few training examples. These characteristics suggest that the proposed framework can beuseful for real-time applications, where the activities are typicallywell distinctive and little training time is required, or to be integrated in larger and sophisticated systems, for a first quick impression/learning of certain activitie

Runoff and erosion at the micro-plot and slope scale in a small burnt catchment, central Portugal

Wildfires can have important impacts on hydrological processes and soil erosion in forest catchments, due to the destruction of vegetation cover and changes to soil properties. However, the processes involved are non-linear and not fully understood. This has severely limited the understanding on the impacts of wildfires, especially in the up-scaling from hillslopes to catchments; in consequence, current models are poorly adapted for burnt forest conditions. The objective of this presentation is to give an overview of the hydrological response and sediment yield from the micro-plot to slope scale, in the first year following a wildfire (2008/2009) that burnt an entire catchment nearby the Colmeal village, central Portugal. The overview will focus on three slopes inside the catchment, with samples including: • Runoff at micro-plot scale (12 bounded plots) and slope scale (12 open plots); • Sediments and Organic Matter loss at micro-plot scale (12 bounded plots) and slope scale (12 open plots plus 3 Sediment fences); • Rainfall and Soil moisture data; • Soil Water Repellency and Ground Cover data. The analysis of the first year following the wildfire clearly shows the complexity of runoff generation and the associated sediment transport in recently burnt areas, with pronounced differences between hillslopes and across spatial scales as well as with marked variations through time. This work was performed in the framework of the EROSFIRE-II project (PTDC/AGR-CFL/70968/2006) which has as overall aim to predict soil erosion risk in recently burnt forest areas, including common post-fire forest management practices; the project focuses on the simultaneous measurement of runoff and soil erosion at multiple spatial scales.The results to be presented in this session are expected to show how sediment is generated, transported and exported in the Colmeal watershed; and contribute to understand and simulate erosion processes in burnt catchments, including for model development and evaluation