Our Work

Automated dataloggers recorded the bottom temperature of snow (BTS) in the Uinta Mountains of Utah (USA) hourly for eight years (2018-2026).  Pairs of data loggers were deployed on the surfaces o…

Automated dataloggers recorded the bottom temperature of snow (BTS) in the Uinta Mountains of Utah (USA) hourly for eight years (2018-2026).  Pairs of data loggers were deployed on the surfaces of two rock glaciers, as well as at adjacent non-rock glacier control sites.  BTS on the rock glaciers averaged -3.5 °C in the months of February and March under deep snow cover.  During the same time, temperatures averaged >-2.0 °C at nearby non-rock glacier control sites.  This offset is consistent with the presence of permafrost within these rock glaciers.  This result indicates that estimates of rock glacier movement from remote sensing and field measurements are likely due to ice deformation, and are consistent with hydrologic evidence that these landforms contain internal ice.  This dataset provides a valuable baseline for monitoring future permafrost change in these mountains.

Machine Learning (ML) and Artificial Intelligence (AI) are being applied to key metallurgical process units within the HAlMan project to improve process understanding, support operational decision-mak…

Machine Learning (ML) and Artificial Intelligence (AI) are being applied to key metallurgical process units within the HAlMan project to improve process understanding, support operational decision-making, increase efficiency, and identify optimized operating conditions. The work combines experimental data, thermodynamic modelling, advanced machine learning techniques, and multi-objective optimization to address both pyrometallurgical and hydrometallurgical processes. A central objective is to move beyond conventional process analysis and develop predictive tools capable of identifying relationships between operating conditions, material characteristics, process performance, and energy requirements. The resulting models can support researchers and industrial operators in evaluating different production scenarios and selecting operating conditions according to priorities such as throughput, energy consumption, and operating cost.

Calls for transformative change have become central to sustainability research and practice. However, most frameworks and empirical insights on how transformation occurs originate from Western Europe …

Calls for transformative change have become central to sustainability research and practice. However, most frameworks and empirical insights on how transformation occurs originate from Western Europe or the Global South. This uneven knowledge production leaves Central and Eastern Europe (CEE) largely invisible in advancing the understanding of transformative change mechanisms. This paper addresses this gap by examining efforts to trigger transformative change at the land-food-energy nexus in Czechia. Drawing on stakeholder analysis and in-depth interviews with key transformative actors, we apply the iceberg model as an analytical framework to unpack the enablers and disablers of transformative change at operational, structural, and narrative levels. While operational and structural enablers and disablers largely mirror those identified in Western European contexts (such as the importance of supportive policies, subsidies, and taxation), those at the narrative level diverge significantly. Historical legacies of state-enforced collectivism in the Czechoslovak Socialist Republic, the path-dependencies of post-1989 political-economic transformation, and the rise of contemporary populism together constrain the legitimacy of transformative change anchored in the principles of solidarity, community, and redistribution. To this end, we argue that globally promoted narratives of transformative change may be normatively powerful yet contextually misaligned. Furthermore, we demonstrate that the CEE experience offers valuable insights into how societies negotiate change under conditions of rigid governance, weak traditions of public participation, pervasive individualism, and transformation fatigue stemming from turbulent socio-economic transitions after 1989.

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Airborne Laser Scanning point clouds — from LAZ to TileDB, with gridded product and waveform simulation pipelines

What's Changed Autoscale on data change; Fit replaces Bokeh's reset by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1332 Accumulate detector view histograms in int32 by @SimonHeybrock …

What's Changed Autoscale on data change; Fit replaces Bokeh's reset by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1332 Accumulate detector view histograms in int32 by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1323 Require sciline>=26.9.0 by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1334 Fix dashboard freeze from error-bar endcaps shared across sessions by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1335 Fix flatten plot hover shared across sessions by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1337 Trim the dashboard widget rule to rules and pointers by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1340 Fit Y autoscale of 1-D plots to the visible x-range by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1342 Make the placeholder guards in plotter render tests fire by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1341 Accept integer-valued axes in correlation histograms by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1343 Show the pixel index in the hover of 2-D plots with index axes by @SimonHeybrock in https://github.com/scipp/esslivedata/pull/1345 Full Changelog: https://github.com/scipp/esslivedata/compare/26.9.3...26.10.0

Commits 42808b1: Fix EOF handling in the Python value reader (#2552) (Chi-Wei Lee) #2552

Cognitive linguistics is an interdisciplinary approach, which has been developed since 1970s. Cognitive linguistics differs from other types of linguistics with its mental representation. Cognitive fr…

Cognitive linguistics is an interdisciplinary approach, which has been developed since 1970s. Cognitive linguistics differs from other types of linguistics with its mental representation. Cognitive frame model represents the concepts, events of terminological system of oil and gas in the frame structure. Consequently, frame models are usually understood to be instruments for data explaining, corpus analysing and describing concepts and conceptual structures under the terminological system of oil and gas engineering, putting them in details – subframe and slots. This paper highlights the importance of cognitive linguistics and its mechanism such as frame model.