Profiling Attitudes for Personalized Information Provision

PAROS is a generic system under design whose goal is to offer personalization, recommendation, and other adaptation services to information providing systems. In its heart lies a rich user model able to capture several diverse aspects of user behavior, interests, preferences, and other attitudes. The user model is instantiated with profiles of users, which are obtained by analyzing and appropriately interpreting potentially arbitrary pieces of user-relevant information coming from diverse sources. These profiles are maintained by the system, updated incrementally as additional data on users becomes available, and used by a variety of information systems to adapt the functionality to the users’ characteristics

Session 9. Professional practices and global competence

Amateur subtitling practices: an etnographic study of communication and work practices in French online translation communities / Sevita Caseres (University College Cork); Audiovisual translation and going global of Chinese film and television / Haina Jin (Communication University of China) ; You've got mail… using email interviews to investigate professional subtitling culture / Alexander Künzli (University of Geneva) ; Does changing translators affect the translation quality of a series? A corpus study / Pawel Aleksandrowicz (Maria Curie-Sklodowska University) ; Permission to emote: developing coping techniques for emotion regulation in subtitling / Nadia Georgiou (Independent Researcher), Katerina Perdikaki (University of Surrey). Chair: Helena Casas (Universitat Autònoma de Barcelona)Amateur subtitling practices: an etnographic study of communication and work practices in French online translation communities / Sevita Caseres (University College Cork). This video presentation is not available in open access. Only the abstract is available

Resilience, smartphone use and language among urban refugees in the Global south

The formidable challenges faced by urban refugees in the Global South have received considerable attention, calling for new approaches to support their resilience. Although critical interest in resilience and the role of digital technology in enabling refugees to navigate their new surroundings has been growing, little attention has been paid to the influence of language and literacy in processes of resilience-building and the use of such technology. This is important due to the diverse linguistic resources which refugees bring with them and the central role of language in adapting to contexts of forced displacement. We develop a conceptual framework for examining refugees’ transnational use of smartphones and apply the framework to data collected from participatory workshops with fifty-four Rohingya refugees in Malaysia. Results revealed varying degrees of digital literacy, linguistic capital and literacy in three main languages: the Rohingya language which refugees bring with them, Bahasa Malaysia, the national language of Malaysia and English, which is widely spoken in Malaysia. These variations significantly shape resilience-building strategies. Greater attention to the role of language and literacy in refugees’ use of digital technology will contribute to better understanding of the capacity for resilience among these individuals and more effective digital solutions

Low-intensity frequent fires in coniferous forests transform soil organic matter in ways that may offset ecosystem carbon losses.

Funder: Sequoia Parks ConservancyFunder: Gordon and Betty Moore Foundation; Id: http://dx.doi.org/10.13039/100000936The impact of shifting disturbance regimes on soil carbon (C) storage is a key uncertainty in global change research. Wildfires in coniferous forests are becoming more frequent in many regions, potentially causing large C emissions. Repeated low-intensity prescribed fires can mitigate wildfire severity, but repeated combustion may decrease soil C unless compensatory responses stabilize soil organic matter. Here, we tested how 30 years of decadal prescribed burning affected C and nitrogen (N) in plants, detritus, and soils in coniferous forests in the Sierra Nevada mountains, USA. Tree basal area and litter stocks were resilient to fire, but fire reduced forest floor C by 77% (-36.4 Mg C/ha). In mineral soils, fire reduced C that was free from minerals by 41% (-4.4 Mg C/ha) but not C associated with minerals, and only in depths ≤ 5 cm. Fire also transformed the properties of remaining mineral soil organic matter by increasing the proportion of C in a pyrogenic form (from 3.2% to 7.5%) and associated with minerals (from 46% to 58%), suggesting the remaining soil C is more resistant to decomposition. Laboratory assays illustrated that fire reduced microbial CO2 respiration rates by 55% and the activity of eight extracellular enzymes that degrade cellulosic and aromatic compounds by 40-66%. Lower decomposition was correlated with lower inorganic N (-49%), especially ammonium, suggesting N availability is coupled with decomposition. The relative increase in forms of soil organic matter that are resistant to decay or stabilized onto mineral surfaces, and the associated decline in decomposition suggest that low-intensity fires may promote mineral soil C storage in pools with long mean residence times in coniferous forests

Divergent controls of soil organic carbon between observations and process-based models

The storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance history. Yet, it remains unclear which of these factors are the dominant predictors of observed SOC stocks, globally and within biomes, and how the role of these predictors varies between observations and process-based models. Here we use global observations and an ensemble of soil biogeochemical models to quantify the emergent importance of key state factors – namely, mean annual temperature, net primary productivity, and soil mineralogy – in explaining biome- to global-scale variation in SOC stocks. We use a machine-learning approach to disentangle the role of covariates and elucidate individual relationships with SOC, without imposing expected relationships a priori. While we observe qualitatively similar relationships between SOC and covariates in observations and models, the magnitude and degree of non-linearity vary substantially among the models and observations. Models appear to overemphasize the importance of temperature and primary productivity (especially in forests and herbaceous biomes, respectively), while observations suggest a greater relative importance of soil minerals. This mismatch is also evident globally. However, we observe agreement between observations and model outputs in select individual biomes – namely, temperate deciduous forests and grasslands, which both show stronger relationships of SOC stocks with temperature and productivity, respectively. This approach highlights biomes with the largest uncertainty and mismatch with observations for targeted model improvements. Understanding the role of dominant SOC controls, and the discrepancies between models and observations, globally and across biomes, is essential for improving and validating process representations in soil and ecosystem models for projections under novel future conditions

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

From hillslope to small catchment scales (&lt;&thinsp;50 km2), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10&nbsp;m2) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4&thinsp;&times;&thinsp;across individual locations in the watershed and a &minus;&thinsp;14.9 to +&thinsp;20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics. </div

SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0

Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Synthesizing datasets collected by different research networks presents opportunities to expand the ecological gradients and scientific breadth of information available for inquiry. Synthesizing these data is challenging, especially considering the legacy of soil data that have already been collected and an expansion of new network science initiatives. To facilitate this effort, here we present the SOils DAta Harmonization database (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets from multiple research networks. SoDaH is built on several network science efforts in the United States, but the tools built for SoDaH aim to provide an open-access resource to facilitate synthesis of soil carbon data. Moreover, SoDaH allows for individual locations to contribute results from experimental manipulations, repeated measurements from long-term studies, and local- to regional-scale gradients across ecosystems or landscapes. Finally, we also provide data visualization and analysis tools that can be used to query and analyze the aggregated database. The SoDaH v1.0 dataset is archived and available at https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020)

Transient up- and down-regulation of expression of myosin light chain 2 and myostatin mRNA mark the changes from stratified hyperplasia to muscle fiber hypertrophy in larvae of gilthead sea bream (Sparus aurata L.)

Hyperplasia and hypertrophy are the two mechanisms by which muscle develops and grows. We study these two mechanisms, during the early development of white muscle in Sparus aurata, by means of histology and the expression of structural and regulatory genes. A clear stage of stratified hyperplasia was identified early in the development of gilthead sea bream but ceased by 35 dph when hypertrophy took over. Mosaic recruitment of new white fibers began as soon as 60 dph. The genes mlc2a and mlc2b were expressed at various levels during the main phases of hyperplasia and hypertrophy. The genes myog and mlc2a were significantly up-regulated during the intensive stratified formation of new fibers and their expression was significantly correlated. Expression of mstn1 and igf1 increased at 35 dph, appeared to regulate the hyperplasia-to-hypertrophy transition, and may have stimulated the expression of mlc2a, mlc2b and col1a1 at the onset of mosaic hyperplasia. The up-regulation of mstn1 at transitional phases in muscle development indicates a dual regulatory role of myostatin in fish larval muscle growth

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good