Inuit Tapiriit Kanatami, (Inuktitut syllabics: ᐃᓄᐃᑦ ᑕᐱᕇᑦ ᑲᓇᑕᒥ, meaning "Inuit are united in Canada") previously known as the Inuit Tapirisat of Canada (Eskimo Brotherhood of Canada), is a nonprofit organization in Canada that represents over 65,000 Inuit across Inuit Nunangat and the rest of Canada. Their mission is to "serve as a national voice protecting and advancing the rights and interests of Inuit in Canada."Founded in 1971 by Inuit leaders, the organization has gone to accomplish various things such as, assisting in the negotiation of land claims, representing the voice of Inuit and their culture by using television, taking legal action against those who have violated their rights, and creating a program to improve education for Inuit children. The ITK has sought to attain its goals, either in cooperation with various levels of government or in opposition. Altogether, the ITK looks to advocate on the behalf of Inuit in Canada. The contributions of the ITK led to the creation of Nunavut.
Climate change is increasing the frequency of droughts, raising the need for sustainable irrigation management in viticulture. This study evaluated the effects of three deficit irrigation regimes—well-watered (WW), mild deficit (MiD), and moderate deficit (MoD)—implemented through the decision support system Vintel® in a Pinot gris vineyard in Friuli Venezia Giulia (Italy). Vine physiology, grape ripening, and wine aroma profile were assessed across two seasons. The water deficit treatments modulated yield parameters (specifically, cluster weight was reduced by 12% and 10% for Mid and Mod as compared to WW) and delayed sugar accumulation, particularly under MoD (9% Brix reduction as compared to WW). While basic wine composition largely reflected grape maturity, volatile aroma compounds showed variable responses to irrigation and were strongly modulated by seasonal conditions. MiD had a minimal impact on the aroma profile, whereas MoD led to reduced sugar and altered volatile composition, especially under hot and dry conditions. DSS-based mild-deficit irrigation can be adopted to reduce vineyard water consumption without compromising Pinot gris wine quality.
Vision models pretrained on large-scale RGB natural image datasets are widely reused for electron microscopy image segmentation. In electron microscopy, volumetric data are acquired as serial sections and processed as stacks of adjacent grayscale slices, where neighboring slices provide symmetric contextual information for identifying features on the central slice. The common strategy maps such stacks to pseudo-RGB inputs to enable transfer learning from pretrained models. However, this mapping imposes channel-specific semantics inherited from natural images, even though electron microscopy slices are homogeneous in the modality and symmetric in their predictive roles. As a result, pretrained models may encode inductive biases that are misaligned with the inherent symmetry of volumetric electron microscopy data. In this work, it is demonstrated that RGB-pretrained models systematically assign unequal importance to individual input slices when applied to stacked electron microscopy data, despite the absence of any intrinsic channel ordering. Using saliency-based attribution analysis across multiple architectures, a consistent channel-level asymmetry was observed that persists after fine-tuning and affects model interpretability, even when segmentation performance is unchanged. To address this issue, a targeted modification of pretraining weights based on uniform channel initialization was proposed, which restores symmetric feature attribution while preserving the benefits of pretraining. Experiments on the SNEMI, Lucchi and GF-PA66 datasets confirm a substantial reduction in attribution bias without compromising or even improving segmentation accuracy.
Background Animals of many different species, trophic levels, and life history strategies migrate, and the improvement of animal tracking technology allows ecologists to collect increasing amounts of detailed data on these movements. Understanding when animals migrate is important for managing their populations, but is still difficult despite modelling advancements. Methods We designed a model that parametrically estimates the timing of migration from animal tracking data. Our model identifies the beginning and end of migratory movements as signaled by change-points in step length and turning angle distributions. To this end, we can also use the model to estimate how an animal’s movement changes when it begins migrating. In addition to a thorough simulation analysis, we tested our model on three datasets: migratory ferruginous hawks ( Buteo regalis ) in the Great Plains, barren-ground caribou ( Rangifer tarandus groenlandicus ) in northern Canada, and non-migratory brown bears ( Ursus arctos ) from the Canadian Arctic. Results Our simulation analysis suggests that our model is most useful for datasets where an increase in movement speed or directional autocorrelation is clearly detectable. We estimated the beginning and end of migration in caribou and hawks to the nearest day, while confirming a lack of migratory behaviour in the brown bears. In addition to estimating when caribou and ferruginous hawks migrated, our model also identified differences in how they migrated; ferruginous hawks achieved efficient migrations by drastically increasing their movement rates while caribou migration was achieved through significant increases in directional persistence. Conclusions Our approach is applicable to many animal movement studies and includes parameters that can facilitate comparison between different species or datasets. We hope that rigorous assessment of migration metrics will aid understanding of both how and why animals move.
The objective of this systematic review was to examine the associations between sleep timing (e.g., bedtime/wake-up time, midpoint of sleep), sleep consistency/regularity (e.g., intra-individual variability in sleep duration, social jetlag, catch-up sleep), and health outcomes in adults aged 18 years and older. Four electronic databases were searched in December 2018 for articles published in the previous 10 years. Fourteen health outcomes were examined. A total of 41 articles, including 92 340 unique participants from 14 countries, met inclusion criteria. Sleep was assessed objectively in 37% of studies and subjectively in 63% of studies. Findings suggest that later sleep timing and greater sleep variability were generally associated with adverse health outcomes. However, because most studies reported linear associations, it was not possible to identify thresholds for "late sleep timing" or "large sleep variability". In addition, social jetlag was associated with adverse health outcomes, while weekend catch-up sleep was associated with better health outcomes. The quality of evidence ranged from "very low" to "moderate" across study designs and health outcomes using GRADE. In conclusion, the available evidence supports that earlier sleep timing and regularity in sleep patterns with consistent bedtimes and wake-up times are favourably associated with health. (PROSPERO registration no.: CRD42019119534.) Novelty This is the first systematic review to examine the influence of sleep timing and sleep consistency on health outcomes. Later sleep timing and greater variability in sleep are both associated with adverse health outcomes in adults. Regularity in sleep patterns with consistent bedtimes and wake-up times should be encouraged.
