Interpretable machine learning models for the estimation of seismic drifts in CLT buildings

An accurate estimation of drift demands is crucial for designing and assessing structures under seismic loads. Given the novelty of massive timber buildings, predictive models for the estimation of drifts in mid- to high-rise CLT structures are lacking, particularly in the form of simple models suitable for preliminary design evaluations or regional seismic assessments. In this paper, we present and compare several Machine Learning (ML) models for the estimation of peak inter-storey and roof drifts in multi-storey Cross-Laminated Timber (CLT) walled structures. The ML techniques used include: Multiple Linear Regression, Regression Trees, Random Forest, K-nearest Neighbour, and Support Vector Regression. To this end, 69 structures spanning mid-rise to tall timber buildings are subjected to a large collection of acceleration records and used to create the training and testing datasets. Different structural configurations and behaviour factors, related to the assumed energy dissipation capacity of the buildings, are considered. A diversity of feature selection techniques informs our choice of parameters to the reduced input space leading to a set of six most efficient features: the spectral acceleration at the building’s fundamental period (Sa(T1)), the Peak Ground Velocity (PGV), tuning ratio (T1/Tm), behaviour factor (q), wall height (Hw), and the wall subdivision ratio (Wr). After verifying the high accuracy of our model predictions, the SHapley Additive exPlanation method (SHAP) is used to gain insight into the influence of key input features on the ML model outputs. Finally, our ML drift estimations are compared against previous proposals and design code assumptions, and the potential causes of disagreement are discussed

TGF-β inhibitor Smad7 regulates dendritic cell-induced autoimmunity

TGF-β is an anti-inflammatory cytokine whose signaling is negatively controlled by Smad7. Previously, we established a role for Smad7 in the generation of autoreactive T cells; however, the function of Smad7 in dendritic cells (DCs) remains elusive. Here, we demonstrate that DC-specific Smad7 deficiency resulted in elevated expression of the transcription factors Batf3 and IRF8, leading to increased frequencies of CD8(+)CD103(+) DCs in the spleen. Furthermore, Smad7-deficient DCs expressed higher levels of indoleamine 2,3-dioxygenase (IDO), an enzyme associated with tolerance induction. Mice devoid of Smad7 specifically in DCs are resistant to the development of experimental autoimmune encephalomyelitis (EAE) as a result of an increase of protective regulatory T cells (Tregs) and reduction of encephalitogenic effector T cells in the central nervous system. In agreement, inhibition of IDO activity or depletion of Tregs restored disease susceptibility. Intriguingly, when Smad7-deficient DCs also lacked the IFN-γ receptor, the mice regained susceptibility to EAE, demonstrating that IFN-γ signaling in DCs mediates their tolerogenic function. Our data indicate that Smad7 expression governs splenic DC subset differentiation and is critical for the promotion of their efficient function in immunity

Seabird species vary in behavioural response to drone census

This is the final version of the article. Available from the publisher via the DOI in this record.Unmanned aerial vehicles (UAVs) provide an opportunity to rapidly census wildlife in remote areas while removing some of the hazards. However, wildlife may respond negatively to the UAVs, thereby skewing counts. We surveyed four species of Arctic cliff-nesting seabirds (glaucous gull Larus hyperboreus, Iceland gull Larus glaucoides, common murre Uria aalge and thick-billed murre Uria lomvia) using a UAV and compared censusing techniques to ground photography. An average of 8.5% of murres flew off in response to the UAV, but >99% of those birds were non-breeders. We were unable to detect any impact of the UAV on breeding success of murres, except at a site where aerial predators were abundant and several birds lost their eggs to predators following UAV flights. Furthermore, we found little evidence for habituation by murres to the UAV. Most gulls flew off in response to the UAV, but returned to the nest within five minutes. Counts of gull nests and adults were similar between UAV and ground photography, however the UAV detected up to 52.4% more chicks because chicks were camouflaged and invisible to ground observers. UAVs provide a less hazardous and potentially more accurate method for surveying wildlife. We provide some simple recommendations for their use.We thank T. Leonard and the Seabird Ecological Reserves Advisory Committee for permission to work at Witless Bay, the Canadian Wildlife Service for permits to work at Newfoundland and Nunavut and the Government of Nunavut for permits to work in Nunavut. Newfoundland and Labrador Murre Fund, Bird Studies Canada and the Molson Foundation directly funded the work. An NSERC Discovery Grant, the Canada Research Chair in Arctic Ecology and Polar Continental Shelf Project also helped fund the project. We thank T. Burke, G. Sorenson, T. Lazarus and M. Guigueno for their help and J. Nakoolak for keeping us safe from bear

Characterization of Actinomycetes Antagonist Fusariumoxysporum f.sp.passiflora Isolated from Rhizosphere Soil ofPurple Passion Fruit Plants, South Sulawesi, Indonesia

To survey rhizosphere actinomycetes as potential biocontrol against fungal diseaseof passion fruits, rhizosphere soil of the plant were used as an isolation sources. Twenty fivestrains were assigned to Streptomyces-like strain based on morphological properties of sporechain. Four strain with distinguishing characteristic based on the macroscopic appearance ofcolonies on different media, were recovery from rhizosphere soil of passion fruits plantsuggesting that various Streptomyces spp. grow surrounding of plant roots. On an agarmedium, four strains (11.43%) commonly formed a clear growth-inhibition zone against fungal pathogen of passion fruits, Fusarium oxysporum f.sp. radicalix passiflori (FORP), indicatingthat this strains can produce antifungal substances. The present results indicate that four strainare a suitable candidate for the biocontrol of fusarium wilt. Keywords: Actinomycetes, AntifungalFusarium oxysporum f.sp.passiflora Rhizosphere, Purple Passion Fruit Plants, South Sulawesi, Indonesi

Simultaneously Hermaphroditic Shrimp Use Lipophilic Cuticular Hydrocarbons as Contact Sex Pheromones

Successful mating is essentially a consequence of making the right choices at the correct time. Animals use specific strategies to gain information about a potential mate, which is then applied to decision-making processes. Amongst the many informative signals, odor cues such as sex pheromones play important ecological roles in coordinating mating behavior, enabling mate and kin recognition, qualifying mate choice, and preventing gene exchange among individuals from different populations and species. Despite overwhelming behavioral evidence, the chemical identity of most cues used in aquatic organisms remains unknown and their impact and omnipresence have not been fully recognized. In many crustaceans, including lobsters and shrimps, reproduction happens through a cascade of events ranging from initial attraction to formation of a mating pair eventually leading to mating. We examined the hypothesis that contact pheromones on the female body surface of the hermaphroditic shrimp Lysmata boggessi are of lipophilic nature, and resemble insect cuticular hydrocarbon contact cues. Via chemical analyses and behavioural assays, we show that newly molted euhermaphrodite-phase shrimp contain a bouquet of odor compounds. Of these, (Z)-9-octadecenamide is the key odor with hexadecanamide and methyl linoleate enhancing the bioactivity of the pheromone blend. Our results show that in aquatic systems lipophilic, cuticular hydrocarbon contact sex pheromones exist; this raises questions on how hydrocarbon contact signals evolved and how widespread these are in the marine environment

Seismic acceleration demands in tall CLT buildings, predictive models and intensity measures

An accurate prediction of floor accelerations is crucial for estimating damage to contents and non-structural components in a building. Oversimplifying the nature of acceleration demands might result in biased estimates of building damage and consequently bias in the calculation of economic losses. However, given the relative novelty of multi-storey tall timber buildings, dedicated studies and models of their seismic acceleration demands are lacking. The need for these is stressed further when we recognise that the behaviour of walled timber structures is decidedly different from that of other conventional structural types. In this study, we apply modern data-driven approaches to evaluate efficient intensity measures (IMs) and develop regression models for predicting the peak floor acceleration (PFA) of multi-storey cross-laminated timber (CLT) buildings. Twenty-four IMs are evaluated and their prediction performance is compared. The sensitivity of acceleration demands to different IMs over a wide range of CLT buildings is investigated. We perform a systematic feature selection process using three different data-driven techniques. The selected features are then used to develop nine regression models to estimate PFA. Various modelling techniques, consisting of conventional (Linear and Polynomial regressions) as well as machine learning algorithms (Decision trees, Random forest, K-nearest neighbour, and Support vector regression) are used. The dataset used to train the models is obtained from numerical results of 69 CLT building models with variations in building height, panel fragmentation levels, and q-factors (ductility levels) subjected to a large set of strong earthquakes. After assessing the accuracy of our model predictions, their PFA estimates obtained are compared against previous research and design codes. Finally, simplified expressions for estimating peak floor accelerations in CLT structures are provided for practical purposes

TGF-beta Is Required To Maintain the Pool of Immature Langerhans Cells in the Epidermis

The pivotal role of TGF-beta in Langerhans cell (LC) development has been previously established in TGF-beta-deficient mice, which lack epidermal LCs. As to whether TGF-beta also governs LC homeostasis and function remains elusive. To assess the role of TGF-beta-mediated control of cutaneous dendritic cells (DCs) in vivo, we generated mice with a conditional knockout of the TGF-beta receptor 1 (T beta R1) under a DC-specific promoter (DC-T beta R1(del) mice). While initial LC seeding occurred in DC-T beta R1(del) mice, the cells disappeared from the epidermis during the first week of life. T beta R1-deficient LCs demonstrated spontaneous maturation and gained migratory potential based on increased surface expression of MHC class II, costimulatory molecules, and CCR7 and downregulation of E-cadherin. In parallel to their early loss from the epidermis, migrating LCs were reduced in the dermis and skin-draining lymph nodes of adult DC-T beta R1(del) mice, whereas the number of Langerin(+) dermal DCs was similar to wild-type. In the absence of LCs, low-dose contact hypersensitivity in DC-T beta R1(del) mice was significantly diminished. In contrast, ear swelling was restored to wild-type levels when a higher hapten dose was applied to efficiently target T beta R1-deficient dermal DCs. In conclusion, TGF-beta inhibits in vivo LC maturation and migratory phenotype, identifying TGF-beta as a critical factor controlling LC homeostasis in the steady state. The Journal of Immunology, 2010, 185: 3248-325