Learning probabilistic interaction models

We live in a multi-modal world; therefore it comes as no surprise that the human brain is tailored for the integration of multi-sensory input. Inspired by the human brain, the multi-sensory data is used in Artificial Intelligence (AI) for teaching different concepts to computers. Autonomous Agents (AAs) are AI systems that sense and act autonomously in complex dynamic environments. Such agents can build up Self-Awareness (SA) by describing their experiences through multi-sensorial information with appropriate models and correlating them incrementally with the currently perceived situation to continuously expand their knowledge. This thesis proposes methods to learn such awareness models for AAs. These models include SA and situational awareness models in order to perceive and understand itself (self variables) and its surrounding environment (external variables) at the same time. An agent is considered self-aware when it can dynamically observe and understand itself and its surrounding through different proprioceptive and exteroceptive sensors which facilitate learning and maintaining a contextual representation by processing the observed multi-sensorial data. We proposed a probabilistic framework for generative and descriptive dynamic models that can lead to a computationally efficient SA system. In general, generative models facilitate the prediction of future states while descriptive models enable to select the representation that best fits the current observation. The proposed framework employs a Probabilistic Graphical Models (PGMs) such as Dynamic Bayesian Networks (DBNs) that represent a set of variables and their conditional dependencies. Once we obtain this probabilistic representation, the latter allows the agent to model interactions between itself, as observed through proprioceptive sensors, and the environment, as observed through exteroceptive sensors. In order to develop an awareness system, not only an agent needs to recognize the normal states and perform predictions accordingly, but also it is necessary to detect the abnormal states with respect to its previously learned knowledge. Therefore, there is a need to measure anomalies or irregularities in an observed situation. In this case, the agent should be aware that an abnormality (i.e., a non-stationary condition) never experienced before, is currently present. Due to our specific way of representation, which makes it possible to model multi-sensorial data into a uniform interaction model, the proposed work not only improves predictions of future events but also can be potentially used to effectuate a transfer learning process where information related to the learned model can be moved and interpreted by another body

PRELIMINARY WATER QUALITY ASSESSMENT USING CANADIAN WATER QUALITY INDEX OF RAS EL-AIN PONDS, SOUTH LEBANON

Water quality deterioration in Lebanon is a pressing national issue and there is a high need for continuous water quality assessment and monitoring of water bodies in the country. This study aims at assessing water quality of Ras El-Ain Ponds, a major natural water resource for domestic use in Tyre district, South Lebanon by using the widely applied Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). Sampling was conducted during February-March, 2023 and physiochemical and microbiological water quality parameters were determined using standardized methods. Assessed parameters in our study are temperature, turbidity, electrical conductivity (EC), total dissolved solids (TDS), pH, ammonia, nitrite, nitrate, chloride, hardness, sulfate, orthophosphate, total organic carbon, fluoride and E. coli which is considered as a main indicator of fecal contamination of waterways. CCME WQI was calculated following the Canadian Water Quality Guidelines in view of the permissible levels set by the World Health Organization (WHO), Lebanese Standards Institution (LIBNOR) and CCME. With the exception of marginal levels of EC and TDS according to WHO and CCME, assessed water quality parameters were within the permissible ranges of standards for domestic water use. As for the CCME WQI, the obtained values fell between 90.73 and 94.42 % which indicates a “Good Quality” level confirming the suitability of water for domestic use. This research presents the first attempt to evaluate the CCME WQI of Ras El-Ain Ponds for quality monitoring and proper decision making. More comprehensive validation of CCME WQI that covers temporal and climatic variabilities is recommended for the assessment process

Intraoperative periprosthetic humeral fracture during reverse shoulder arthroplasty: a sequelae of prior biceps tenodesis

Intraoperative periprosthetic humeral fractures are a rare but debilitating complication of reverse shoulder arthroplasty and can occur during multiple stages of the procedure. Prior biceps tenodesis has been found to reduce cortical humeral strength and predispose the patient to humeral fracture. We present a case of a 68-year-old female with a previous history of biceps tenodesis due to an irreparable rotator cuff tear. Months later, and after symptoms persisted, a reverse shoulder arthroplasty was performed. During the surgery and while performing final reduction, a fracture line was observed involving the hole used for the previous tenodesis procedure. The fracture was repaired, and the patient reported favorable outcomes. We report several factors that might have contributed to sustenance of this intraoperative fracture including prior biceps tenodesis, use of a press fit humeral stem, and the sex of the patient.Level of evidence: V

The Therapeutic Wound Healing Bioactivities of Various Medicinal Plants

The skin serves as the body’s first line of defense, guarding against mechanical, chemical, and thermal damage to the interior organs. It includes a highly developed immune response that serves as a barrier against pathogenic infections. Wound healing is a dynamic process underpinned by numerous cellular activities, including homeostasis, inflammation, proliferation, and remodeling, that require proper harmonious integration to effectively repair the damaged tissue. Following cutaneous damage, microorganisms can quickly enter the tissues beneath the skin, which can result in chronic wounds and fatal infections. Natural phytomedicines that possess considerable pharmacological properties have been widely and effectively employed forwound treatment and infection prevention. Since ancient times, phytotherapy has been able to efficiently treat cutaneous wounds, reduce the onset of infections, and minimize the usage of antibiotics that cause critical antibiotic resistance. There are a remarkable number of wound-healing botanicals that have been widely used in the Northern Hemisphere, including Achiella millefolium, Aloe vera, Althaea officinalis, Calendula officinalis, Matricaria chamomilla, Curcuma longa, Eucalyptus, Jojoba, plantain, pine, green tea, pomegranate, and Inula. This review addresses the most often used medicinal plants from the Northern Hemisphere that facilitate the treatment of wounds, and also suggests viable natural alternatives that can be used in the field of wound care

Mild and efficient protection of diol and carbonyls as cyclic acetals catalysed by iron (III) chloride

BIOVERT:INGENIERIE+MAL:LC

Intérêt du macrophyte Myriophyllum alterniflorum pour la détection de contaminants dans l'environnement

The aim of this thesis is to demonstrate the interest of a submerged aquatic macrophyte, Myriophyllum alterniflorum for the detection of contaminants in the environment. In situ studies were conducted over 28 days in five aquatic environments, affected by different levels of anthropogenic pressure, during three field seasons (spring 2015, autumn 2015 and spring 2016), to determine whether the accumulation of contaminants in the plant and whether biomarkers can be used to detect the presence of contaminants in water. The accumulation of contaminants over time was correlated with the levels of contaminants in the water; the influence of the duration of exposure has been studied. In all three campaigns, biomarker response, MDA content, and nitrate reductase activity were correlated with contaminant levels in water and in the plant; however, the influence of the duration of exposure on the evolution of the biomarker response is lower compared to the accumulation of contaminants. Thus, the study of biomarkers could allow a more reliable assessment of the quality of water bodies than the monitoring of contaminant accumulation in the plant. During the spring 2015 campaign, a much broader biomarker panel was investigated to define the most relevant biomarkers for assessing water quality. A methodology for evaluating water quality is proposed, considering a biomarker analysis protocol: a first assay of Chlb and MDA is simple and less expensive. When no evidence of human impact is shown, no further analysis is required. On the other hand, when an alteration is highlighted, the analysis of other more specific biomarkers such as G6PDH and γ-GCS activities will be necessary. The response of γ-GCS activity is specific for metal stress, so the response of this biomarker should lead to the analysis of metals / metalloids in M. alterniflorum.Le but de ce travail de thèse est de démontrer l’intérêt d’un macrophyte aquatique submergé, Myriophyllum alterniflorum pour la détection de contaminants dans l’environnement. Des études in situ ont été réalisées pendant 28 jours sur cinq milieux aquatiques, affectés par différents types de pression anthropique, durant trois campagnes de terrain (printemps 2015, automne 2015 et printemps 2016), pour déterminer si l’accumulation des contaminants dans la plante et si des biomarqueurs du myriophylle peuvent être utilisés pour détecter la présence de contaminants dans les eaux. L’accumulation des contaminants au cours du temps était corrélée avec les teneurs des contaminants dans l’eau ; l’influence de la durée d’exposition a été étudiée. Au cours des trois campagnes, la réponse des biomarqueurs, teneur en MDA et activité de nitrate réductase était corrélée avec les teneurs en contaminants dans l’eau et dans la plante ; cependant l’influence de la durée d’exposition sur l’évolution de la réponse des biomarqueurs est moindre par rapport à celle de l’accumulation des contaminants. Ainsi, l’étude des biomarqueurs pourrait permettre une évaluation plus fiable de la qualité des masses d’eau que le suivi de l’accumulation dans la plante. Au cours de la campagne printemps 2015, un panel de biomarqueurs plus large a été étudié afin de définir les biomarqueurs les plus pertinents pour détecter spécifiquement les pressions liées aux activités urbaines ou industrielles. Une méthodologie d’évaluation de la qualité des eaux est proposée, en considérant un protocole d’analyse des biomarqueurs : un premier dosage de Chlb et MDA est simple et moins coûteux. Quand aucune preuve d'impact anthropique n'est montrée, aucune analyse complémentaire n'est requise. En revanche, lorsqu’une altération est mise en évidence, l’analyse d'autres biomarqueurs plus spécifiques tels que les activités G6PDH et γ-GCS sera nécessaire. La réponse de l'activité γ-GCS est spécifique du stress métallique, ainsi, la réponse de ce biomarqueur devrait amener à réaliser l’analyse des métaux/métalloïdes dans M. alterniflorum

Interest of the macrophyte Myriophyllum alterniflorum for the detection of contaminants in the environment

Le but de ce travail de thèse est de démontrer l’intérêt d’un macrophyte aquatique submergé, Myriophyllum alterniflorum pour la détection de contaminants dans l’environnement. Des études in situ ont été réalisées pendant 28 jours sur cinq milieux aquatiques, affectés par différents types de pression anthropique, durant trois campagnes de terrain (printemps 2015, automne 2015 et printemps 2016), pour déterminer si l’accumulation des contaminants dans la plante et si des biomarqueurs du myriophylle peuvent être utilisés pour détecter la présence de contaminants dans les eaux. L’accumulation des contaminants au cours du temps était corrélée avec les teneurs des contaminants dans l’eau ; l’influence de la durée d’exposition a été étudiée. Au cours des trois campagnes, la réponse des biomarqueurs, teneur en MDA et activité de nitrate réductase était corrélée avec les teneurs en contaminants dans l’eau et dans la plante ; cependant l’influence de la durée d’exposition sur l’évolution de la réponse des biomarqueurs est moindre par rapport à celle de l’accumulation des contaminants. Ainsi, l’étude des biomarqueurs pourrait permettre une évaluation plus fiable de la qualité des masses d’eau que le suivi de l’accumulation dans la plante. Au cours de la campagne printemps 2015, un panel de biomarqueurs plus large a été étudié afin de définir les biomarqueurs les plus pertinents pour détecter spécifiquement les pressions liées aux activités urbaines ou industrielles. Une méthodologie d’évaluation de la qualité des eaux est proposée, en considérant un protocole d’analyse des biomarqueurs : un premier dosage de Chlb et MDA est simple et moins coûteux. Quand aucune preuve d'impact anthropique n'est montrée, aucune analyse complémentaire n'est requise. En revanche, lorsqu’une altération est mise en évidence, l’analyse d'autres biomarqueurs plus spécifiques tels que les activités G6PDH et γ-GCS sera nécessaire. La réponse de l'activité γ-GCS est spécifique du stress métallique, ainsi, la réponse de ce biomarqueur devrait amener à réaliser l’analyse des métaux/métalloïdes dans M. alterniflorum.The aim of this thesis is to demonstrate the interest of a submerged aquatic macrophyte, Myriophyllum alterniflorum for the detection of contaminants in the environment. In situ studies were conducted over 28 days in five aquatic environments, affected by different levels of anthropogenic pressure, during three field seasons (spring 2015, autumn 2015 and spring 2016), to determine whether the accumulation of contaminants in the plant and whether biomarkers can be used to detect the presence of contaminants in water. The accumulation of contaminants over time was correlated with the levels of contaminants in the water; the influence of the duration of exposure has been studied. In all three campaigns, biomarker response, MDA content, and nitrate reductase activity were correlated with contaminant levels in water and in the plant; however, the influence of the duration of exposure on the evolution of the biomarker response is lower compared to the accumulation of contaminants. Thus, the study of biomarkers could allow a more reliable assessment of the quality of water bodies than the monitoring of contaminant accumulation in the plant. During the spring 2015 campaign, a much broader biomarker panel was investigated to define the most relevant biomarkers for assessing water quality. A methodology for evaluating water quality is proposed, considering a biomarker analysis protocol: a first assay of Chlb and MDA is simple and less expensive. When no evidence of human impact is shown, no further analysis is required. On the other hand, when an alteration is highlighted, the analysis of other more specific biomarkers such as G6PDH and γ-GCS activities will be necessary. The response of γ-GCS activity is specific for metal stress, so the response of this biomarker should lead to the analysis of metals / metalloids in M. alterniflorum

Yoga for Cancer-Related Fatigue in Survivors of Hematopoietic Stem Cell Transplantation: A Mixed-Methods Feasibility Study

Despite its potential benefits in cancer survivorship, yoga has not been tested in cancer survivors treated with hematopoietic stem cell transplantation (HSCT). The aim of this mixed-methods study is to evaluate the feasibility of a yoga intervention offered to adult HSCT survivors with cancer-related fatigue (CRF). The secondary goals are 1) to evaluate the association of baseline CRF severity with depression, sleep disturbances, and pain; 2) to evaluate the changes in CRF, depression, sleep disturbances, pain, and physical activity from baseline to postintervention; 3) to evaluate the association of CRF change with changes in depression, sleep disturbances, and pain, and physical activity; 4) to evaluate the association of yoga adherence with self-efficacy and self-regulation skills and abilities; and 5) to explore participants’ perceptions of yoga and physical activity. Twenty adult HSCT survivors were enrolled in a 6-week restorative yoga intervention, and eight of them participated in focus groups upon intervention completion. The accrual acceptance rate was 23.2% (20/86 participants). Twelve of the 20 participants who enrolled completed the study. Overall adherence was 45.4%. No adverse reactions attributable to yoga were reported. Of the five CRF dimensions (i.e., total CRF, physical CRF, general CRF, mental CRF, emotional CRF) evaluated at baseline, total CRF and emotional CRF correlated significantly with sleep disturbances (r=0.52, P=0.02; r=0.57, P=0.01, respectively). Baseline emotional CRF also correlated significantly with depression (r=0.68, P=0.02). Participants reported postintervention improvements in general CRF (d=-0.75), physical CRF (d=-0.66), vigor (d=0.63) and sleep disturbances (d=-0.81) (all Ps< 0.05). Improvements in two or more of the CRF dimensions correlated significantly with reductions in depression, sleep disturbances, and pain; correlations ranged from 0.58 to 0.86. Improvements in three CRF dimensions (general CRF, mental CRF, emotional CRF) also correlated significantly with increases in self-reported physical activity; correlations ranged from -0.58 to -0.60. Correlations between overall adherence and self-efficacy and self-regulation skills and abilities were not significant, ranging from -0.29 to 0.41. Focus group participants described a range of benefits from yoga practice, most notably stress reduction. Barriers and hurdles to practicing yoga included general time constraints, long travel distance to the intervention site, distractions during home practice, and difficult yoga poses. The most important aspects of the yoga classes from the participants’ perspective were individualized instruction style and camaraderie. Participants reported three motives for physical activity engagement: maintaining and improving general wellbeing, regaining general health, and having company to exercise with. Fear of falling and/or injury was perceived by participants as the major reason for physical activity avoidance. Yoga and walking were the most commonly preferred types of physical activity by participants. The results of this study indicate that a yoga trial in adult HSCT survivors is feasible from a safety standpoint and needs to employ strategies to improve accrual acceptance, retention, and protocol adherence rates. The reported reductions in CRF and sleep disturbances are promising and provide the foundation for hypotheses to be tested in subsequent studies. The association of CRF with depression, sleep disturbances, pain, and physical activity indicates that CRF is a multifactorial symptom partly related to concurrent symptoms and physical activity levels. The relationship between yoga adherence and self-efficacy and self-regulation skills and abilities needs to be reevaluated with larger samples. The emergent themes from the qualitative data can be used to optimize yoga and other physical activity interventions in HSCT survivors.PHDNursingUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149985/1/bmohamad_1.pd

Smart Jammer Detection for Self-Aware Cognitive UAV Radios

Cellular connectivity for a massive number of Unmanned Aerial Vehicles (UAVs) will overcrowd the radio spectrum and cause spectrum scarcity. Incorporating Cognitive Radio (CR) with UAVs (Cognitive-UAV-Radios) has been proposed to overcome such an issue. However, the broadcasting nature of CR and the dominant line-of-sight links of UAV makes the Cognitive-UAV-Radios susceptible to jamming attacks. In this paper, we propose a framework to detect smart jammer, which locates and attacks the UAV commands with low Jamming-to-Signal-Power-Ratio (JSR). Smart jammer is more challenging than the types of jammers that always require high power values. Our work focuses on learning a Dynamic Bayesian Network (DBN) to model and analyze the signals' behaviour statistically. A Markov Jump Particle Filter (MJPF) is employed to perform predictions and consequently detect jamming signals. The results are satisfactory in terms of detection probability and false alarm rate that outperform the conventional Energy Detector approach

Continual learning of predictive models in video sequences via variational autoencoders

This paper proposes a method for performing continual learning of predictive models that facilitate the inference of future frames in video sequences. For a first given experience, an initial Variational Autoencoder, together with a set of fully connected neural networks are utilized to respectively learn the appearance of video frames and their dynamics at the latent space level. By employing an adapted Markov Jump Particle Filter, the proposed method recognizes new situations and integrates them as predictive models avoiding catastrophic forgetting of previously learned tasks. For evaluating the proposed method, this article uses video sequences from a vehicle that performs different tasks in a controlled environment.Comment: Manuscript accepted at the 27th IEEE International Conference on Image Processing (ICIP 2020