Estimation de la température de l'eau de rivière en utilisant les réseaux de neurones et la régression linéaire multiple

La température de l'eau en rivière est un paramètre ayant une importance majeure pour la vie aquatique. Les séries temporelles décrivant ce paramètre thermique existent, mais elles sont moins nombreuses et souvent courtes, ou comptent parfois des valeurs manquantes. Cette étude présente la modélisation de la température de l'eau en utilisant des réseaux de neurones et la régression linéaire multiple pour relier la température de l'eau à celle de l'air et le débit du ruisseau Catamaran, situé au Nouveau-Brunswick, Canada. Une recherche multidisciplinaire à long terme se déroule présentement sur ce site. Les données utilisées sont de 1991 à 2000 et comprennent la température de l'air de la journée en cours, de la veille et de l'avant-veille, le débit ainsi que le temps transformé en série trigonométrique. Les données de 1991 à 1995 ont été utilisées pour l'entraînement ou la calibration du modèle tandis que les données de 1996 à 2000 ont été utilisées pour la validation du modèle. Les coefficients de détermination obtenus pour l'entraînement sont de 94,2 % pour les réseaux de neurones et de 92,6 % pour la régression linéaire multiple, ce qui donne un écart-type des erreurs de 1,01 C pour les réseaux de neurones et de 1,05 C pour la régression linéaire multiple. Pour la validation, les coefficients de détermination sont de 92,2 % pour les réseaux de neurones et de 91,6 % pour la régression linéaire multiple, ce qui se traduit en un écart-type des erreurs de 1,10 C pour les réseaux de neurones et de 1,25 C pour la régression linéaire multiple. Durant la période d'étude (1991-2000), le biais a été calculé à +0,11 C pour le modèle de réseaux de neurones et à -0,26 °C pour le modèle de régression. Ces résultats permettent de conclure qu'il est possible de prévoir la température de l'eau de petits cours d'eau en utilisant la température de l'air et le débit, aussi bien avec les réseaux de neurones qu'avec la régression linéaire multiple. Les réseaux de neurones semblent donner un ajustement aux données légèrement meilleur que celui offert par la régression linéaire multiple, toutefois ces deux approches de modélisation démontrent une bonne performance pour la prédiction de la température de l'eau en rivière.Water temperature is a parameter of great importance for water resources. For instance, modifications of the thermal regime of a river can have a significant impact on fish habitat. Therefore, understanding and predicting water temperatures is essential in order to help prevent or forecast high temperature problems. In order to predict water temperatures, data series are necessary. Many data series exist for air temperatures, but water temperature series are relatively scarce and those available are often short or have missing values. This study presents the modelling of water temperature using neural networks and multiple linear regression to relate water temperature to air temperature and discharge in Catamaran Brook, New Brunswick, Canada.Catamaran Brook is a small stream (51 km2) where long-term multidisciplinary habitat research is being carried out. Many variables can impact water temperatures in a river, such as air temperature, solar radiation, wind speed, discharge, groundwater flow, etc. For this study, only air temperature and discharge were used. These were judged to be the most often available parameters for modelling temperatures in rivers, and to have the greatest impact on water temperature. More precisely, input variables included current air temperature (°C), air temperature of the previous day (°C), air temperature two days earlier (°C), discharge (m3 /s) and a trigonometric function of time (days). Data used for the analysis were from 1991 to 2000. Data from 1991 to 1995 were used to calibrate the model while data from 1996 to 2000 were used for validation purposes. Observed and predicted water temperatures for each model were presented for the calibration data and the validation data. The coefficient of determination, R2, was used to compare the efficiency of both models as well as the residual standard deviation and the bias. This is equivalent to basing the comparison on the standard deviation (or variance) of the residuals. Coefficients of determination for calibration were 94.2% for the neural networks and 92.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.01°C for the neural networks and of 1.05°C for the multiple linear regression. For validation, coefficients of determination were 92.2% for the neural networks and 91.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.10°C for the neural networks, and of 1.25°C for the multiple regression. The overall bias during the study period (1991-2000) was calculated at +0.11°C for the neural network model and at -0.26°C for the regression model. Results indicated that it was possible to predict water temperature for a small stream using air temperature, flow and time, as input variables, with neural networks and multiple linear regression. The residual series obtained by both models were very similar. Of the two models, neural networks gave slightly better results in terms of fit, but the small difference in results lets us believe that both approaches are equally good in predicting stream water temperatures

Allergologie-immunologie - Maladies autoimmunes complexes : quand les glucocorticoïdes ne suffisent plus [Difficult to treat auto-immune diseases : when glucocorticoids are not enough]

Glucocorticosteroids (GC) remain the mainstay of treatment in most systemic inflammatory diseases. GC have a broad anti-inflammatory action of rapid onset. The downsides of prolonged GC therapy are well established and include infections, osteoporosis and metabolic adverse effects, among others. In systemic sclerosis, GC are associated with an increased risk of scleroderma renal crisis and must be avoided. Adjunction of second-line immunosuppressive drugs may improve disease control and limit GC usage. We summarize here the findings of two studies published in 2021, one reporting the benefits of combining GC with mycophenolate mofetil in immune thrombocytopenia, the other suggesting that blockage of interleukin-6 may decrease disease progression in systemic sclerosis with lung involvement

Attractiveness of a lateral shelter in a channel as a refuge for juvenile brown trout during hydropeaking

Peak power production in hydroelectric storage power plants results in frequent and intense flow variations in the rivers downstream of the plants. Fish populations can be negatively impacted when subjected to these so-called hydropeaking phenomena. In researching mitigation solutions, shelters in the riverbanks of channelized rivers have been identified as a means of protecting fish from excessive flow velocities. These shelters were studied systematically using juvenile brown trout (Salmo trutta fario) in an experimental configuration in which a straight channel was equipped with a lateral embayment. The purpose of the experiments was to generate hydrodynamic hydropeaking conditions in the channel that are undesirable for juvenile trout, thereby causing them to enter the shelter. The flow velocity distribution in the intersection plane between the main channel and the lateral shelter was found to be a significant parameter for attracting fish to the shelter. The utilization rate of trout in the shelter was used as a performance indicator. Using a basic rectangular shelter configuration without forced water exchange between the shelter and the channel, the utilization rate was only 35%. This rate was more than doubled by introducing a deviation groyne to force water exchange between the channel and the shelter. The position and orientation angle of this groyne were systematically varied to maximize the utilization rate. Maximum utilization rates approaching 90% were obtained for an optimum configuration in which an island-type groyne was placed in the shelter. The results of the systematic channel tests showed the potential of the shelter to attract fish. Such a shelter could be used in channelized rivers both for morphological revitalization and to improve fish habitats. As a next step in this research, prototype shelters will be built on a natural river and monitored for 2-3years under a hydropeaking flow regime

Autoantibodies Against Albumin in Patients With Systemic Lupus Erythematosus.

Objectives: Autoantibodies and aberrant immune complexes are pathological hallmarks of systemic lupus erythematosus (SLE). This study aimed to determine the occurrence of IgG autoantibodies against human serum albumin (anti-HSA IgG) and their potential association with antibodies against bovine serum albumin (anti-BSA IgG) in patients with SLE. Methods: Sera of 180 SLE patients included to the Swiss SLE Cohort Study and 188 age- and sex-matched healthy controls were evaluated. Levels of anti-HSA IgG and anti-BSA IgG were quantified by ELISA. Selected samples were further characterized using serum fractions obtained by fast liquid chromatography (FPLC). Results: SLE patients had increased levels of anti-HSA IgG (p = 0.002) but similar levels of anti-BSA IgG compared to matched healthy controls. Anti-HSA IgG levels correlated with the SLE Disease Activity Index (SLEDAI), which was more pronounced in patients with an physician's global assessment (PGA) of ≥ 1 (r = 0.309, p = 0.0066). Anti-HSA IgG was partially complexed with serum albumin but also occurred as monomeric autoantibodies in highly positive SLE patients. A positive correlation between anti-HSA IgG and anti-BSA IgG was found that was stronger in SLE patients than in healthy controls (r = 0.3172, p < 0.001 vs. r = 0.2122, p < 0.0035). Binding of anti-BSA IgG was inhibited partially in the presence of HSA in samples with double positivity for anti-HSA and anti-BSA (median inhibition 47.9%, range 0.9-100%) and vice versa. Conclusion: In SLE patients there is an increased prevalence of anti-HSA IgG antibodies that are associated with SLE disease activity

Does it bite? The role of stimuli characteristics on preschoolers’ interactions with robots, insects and a dog

While there is increasing interest in the impact of animal interactions upon children’s wellbeing and attitudes, there has been less attention paid to the specific characteristics of the animals which attract and engage children. We used a within-subjects design to explore how differences in animal features (such as their animacy, size, and texture) impacted upon pre-school children’s social and emotional responses. This study examined pre-schoolers’ interactions with two animal-like robots (Teksta and Scoozie), two insect types (stick insects and hissing cockroaches) and a dog (Teasel, a West Highland Terrier). Nineteen preschool participants aged 35-57 months were videoed while interacting with the experimenter, a peer and each stimulus (presented individually). We used both verbal and nonverbal behaviours to evaluate interactions and emotional responses to the stimuli and found that these two measures could be incongruent, highlighting the need for systematic approaches to evaluating children’s interactions with animals. We categorised the content of children’s dialogues in relation to psychological and biological attributes of each stimulus and their distinctions between living and non-living stimuli; the majority of comments were biological, with psychological terms largely reserved for the dog and mammal-like robot only. Comments relating to living qualities revealed ambiguity towards attributes that denote differences between living and non-living creatures. We used a range of nonverbal measures, including willingness to approach and touch stimuli, rates of self-touching, facial expressions of emotion, and touch to others. Insects (hissing cockroaches and stick insects) received the most negative verbal and nonverbal responses. The mammal-like robot (rounded, fluffy body shape, large eyes, and sympathetic sounds) was viewed much more positively than its metallic counterpart, as was the real dog. We propose that these interactions provide information on how children perceive animals and a platform for the examination of human socio-emotional and cognitive development more generally. The children engaged in social referencing to the adult experimenter rather than familiar peers when uncertain about the stimuli presented, suggesting that caregivers have a primary role in shaping children’s responses to animals

Sarcoidosis - a multisystem disease.

Sarcoidosis is a systemic inflammatory disease, characterised by granuloma formation upon an unknown trigger in genetically predisposed individuals. The inflammation is characterised by an activation of both the innate immune system, with macrophages differentiating into epitheloid cells and dendritic cells, and the adaptive immune system, particularly T helper (Th) 1 and Th17 cells. Since all organs can be affected to varying extents, clinical presentation is often diverse. Most commonly, the lungs, lymph nodes, skin and eyes are involved, whereas cardiac, renal and neurological manifestations are less common but associated with higher morbidity. Depending on the clinical symptoms, a detailed evaluation including thorough clinical examination, imaging and laboratory tests should explore all possible organ involvements. In some patients, fatigue manifests as a para-sarcoidosis symptom impacting quality of life, even if sarcoidosis is in remission. Some acute syndromic presentations, such as Löfgren's syndrome, have a good prognosis and are commonly self-limiting. If possible, a topical treatment, for example for cutaneous sarcoidosis or bronchial involvement, should be applied. Treatment of severe cases with persisting disease activity necessitates long-term immunosuppressive drugs, with glucocorticoids as the first-line option. Steroid-sparing and second-line drugs include methotrexate, azathioprine, mycophenolate mofetil and immunomodulators such hydroxychloroquine, with the latter being first-line therapy in cutaneous sarcoidosis. Tumour necrosis factor-alpha inhibitors (particularly adalimumab and infliximab) are used as third-line agents but are administered earlier in cases of persistent disease activity, severe organ-involvement or intolerance to conventional drugs. Treatment decisions should be based on a multidisciplinary approach, depending on organ involvement and treatment tolerability. Para-sarcoidosis manifestations, particularly fatigue, should also be carefully addressed, where the patient could also be enrolled in multidimensional rehabilitation programmes. With various organ involvement and different phenotypes, larger studies including real-world data from registries are necessary to evaluate different sarcoidosis endotypes and preferential treatment pathways

The role of ocelli in cockroach optomotor performance

Insect ocelli are relatively simple eyes that have been assigned various functions not related to pictorial vision. In some species they function as sensors of ambient light intensity, from which information is relayed to various parts of the nervous system, e.g., for the control of circadian rhythms. In this work we have investigated the possibility that the ocellar light stimulation changes the properties of the optomotor performance of the cockroach Periplaneta americana. We used a virtual reality environment where a panoramic moving image is presented to the cockroach while its movements are recorded with a trackball. Previously we have shown that the optomotor reaction of the cockroach persists down to the intensity of moonless night sky, equivalent to less than 0.1 photons/s being absorbed by each compound eye photoreceptor. By occluding the compound eyes, the ocelli, or both, we show that the ocellar stimulation can change the intensity dependence of the optomotor reaction, indicating involvement of the ocellar visual system in the information processing of movement. We also measured the cuticular transmission, which, although relatively large, is unlikely to contribute profoundly to ocellar function, but may be significant in determining the mean activity level of completely blinded cockroaches