Miracle-dz/UniFAR-FTUs huggingface dataset:
Trophic status of the south-eastern Baltic Sea: A comparison of coastal and open areas

Primary production, nutrient concentrations, phytoplankton biomass (incl. chlorophyll a) and water transparency (Secchi depth), are important indicators of eutrophication. Earlier basin-wide primary production estimates for the Baltic Sea, a shallow shelf sea, were based mainly on open-sea data, neglecting the fundamentally different conditions in the large river plumes, which might have substantially higher production. Mean values of the period 1993–1997 of nutrient concentrations (phosphate, nitrate, ammonium and silicate), phytoplankton biomass, chlorophyll a (chl a) concentration, turbidity and primary production were calculated in the plumes of the rivers Oder, Vistula and Daugava and Klaipeda Strait as well as the open waters of the Arkona Sea, Bornholm Sea, eastern Gotland Sea and the Gulf of Riga. In the plumes, these values, except for primary production, were significantly higher than in the open waters. N:P ratios in the plumes were >16 (with some exceptions in summer and autumn), indicating potential P-limitation of phytoplankton growth, whereas they were <16 in the open Baltic Proper, indicating potential N-limitation. On the basis of in situ phytoplankton primary production, phytoplankton biomass and nutrient concentrations, the large river plumes and the Gulf of Riga could be characterized as eutrophic and the outer parts of the coastal waters and the open sea as mesotrophic. Using salinity to define the border of the plumes, their mean extension was calculated by means of a circulation model. Taking into account the contribution of coastal waters, the primary production in the Baltic Proper and the Gulf of Riga was 42·6 and 4·3×106 t C yr−1, respectively. Hence, an annual phytoplankton primary production in the whole Baltic Sea was estimated at 62×106 t C yr−1. The separate consideration of the plumes had only a minor effect on the estimation of total primary production in comparison with an estimate based on open sea data only. There is evidence for a doubling of primary production in the last two decades. Moreover, a replacement of diatoms by dinoflagellates during the spring bloom was noticed in the open sea but not in the coastal waters. A scheme for trophic classification of the Baltic Sea, based on phytoplankton primary production and biomass, chl a and nutrient concentrations, is proposed.
Simulated Variability of the Circulation in the North Atlantic from 1953 to 2003

Abstract The variability of the circulation in the North Atlantic and its link with atmospheric variability are investigated in a realistic hindcast simulation from 1953 to 2003. The interannual-to-decadal variability of the subpolar gyre circulation and the Meridional Overturning Circulation (MOC) is mostly influenced by the North Atlantic Oscillation (NAO). Both circulations intensified from the early 1970s to the mid-1990s and then decreased. The monthly variability of both circulations reflects the fast barotropic adjustment to NAO-related Ekman pumping anomalies, while the interannual-to-decadal variability is due to the baroclinic adjustment to Ekman pumping, buoyancy forcing, and dense water formation, consistent with previous studies. An original characteristic of the oceanic response to NAO is presented that relates to the spatial patterns of buoyancy and wind forcing over the North Atlantic. Anomalous Ekman pumping associated with a positive NAO phase first induces a decrease of the southern sub.
The painful face: pain expression recognition using active appearance models

Pain is typically assessed by patient self-report. Self-reported pain, however, is difficult to interpret and may be impaired or not even possible, as in young children or the severely ill. Behavioral scientists have identified reliable and valid facial indicators of pain. Until now they required manual measurement by highly skilled observers. We developed an approach that automatically recognizes acute pain. Adult patients with rotator cuff injury were video-recorded while a physiotherapist manipulated their affected and unaffected shoulder. Skilled observers rated pain expression from the video on a 5-point Likert-type scale. From these ratings, sequences were categorized as no-pain (rating of 0), pain (rating of 3, 4, or 5), and indeterminate (rating of 1 or 2). We explored machine learning approaches for pain-no pain classification. Active Appearance Models (AAM) were used to decouple shape and appearance parameters from the digitized face images. Support vector machines (SVM) were used with several representations from the AAM. Using a leave-one-out procedure, we achieved an equal error rate of 19% (hit rate = 81%) using canonical appearance and shape features. These findings suggest the feasibility of automatic pain detection from video.
LearningQ: A Large-Scale Dataset for Educational Question Generation

We present LearningQ, a challenging educational question generation dataset containing over 230K document-question pairs. It includes 7K instructor-designed questions assessing knowledge concepts being taught and 223K learner-generated questions seeking in-depth understanding of the taught concepts. We show that, compared to existing datasets that can be used to generate educational questions, LearningQ (i) covers a wide range of educational topics and (ii) contains long and cognitively demanding documents for which question generation requires reasoning over the relationships between sentences and paragraphs. As a result, a significant percentage of LearningQ questions (~30%) require higher-order cognitive skills to solve (such as applying, analyzing), in contrast to existing question-generation datasets that are designed mostly for the lowest cognitive skill level (i.e. remembering). To understand the effectiveness of existing question generation methods in producing educational questions, we evaluate both rule-based and deep neural network based methods on LearningQ. Extensive experiments show that state-of-the-art methods which perform well on existing datasets cannot generate useful educational questions. This implies that LearningQ is a challenging test bed for the generation of high-quality educational questions and worth further investigation. We open-source the dataset and our codes at https://dataverse.mpi-sws.org/dataverse/icwsm18.
Can Maxout Units Downsize Restoration Networks? - Single Image Super-Resolution Using Lightweight CNN with Maxout Units

Rectified linear units (ReLU) are well-known to be helpful in obtaining faster convergence and thus higher performance for many deep-learning-based applications. However, networks with ReLU tend to perform poorly when the number of filter parameters is constrained to a small number. To overcome it, in this paper, we propose a novel network utilizing maxout units (MU), and show its effectiveness on super-resolution (SR) applications. In general, the MU has been known to make the filter sizes doubled in generating the feature maps of the same sizes in classification problems. In this paper, we first reveal that the MU can even make the filter sizes halved in restoration problems thus leading to compaction of the network sizes. To show this, our SR network is designed without increasing the filter sizes with MU, which outperforms the state of the art SR methods with a smaller number of filter parameters. To the best of our knowledge, we are the first to incorporate MU into SR applications and show promising performance results. In MU, feature maps from a previous convolutional layer are divided into two parts along channels, which are then compared element-wise and only their max values are passed to a next layer. Along with some interesting properties of MU to be analyzed, we further investigate other variants of MU and their effects. In addition, while ReLU have a trouble for learning in networks with a very small number of convolutional filter parameters, MU do not. For SR applications, our MU-based network reconstructs high-resolution images with comparable quality compared to previous deep-learning-based SR methods, with lower filter parameters.
Flow velocity and wetted perimeter effects on furrow infiltration

Infiltration theory and previous studies show that furrow infiltration increases with wetted perimeter. This effect can strongly influence water distribution along furrows. Stagnant blocked-furrow measurements on Portneuf silt loam soil supported this relationship. However, both recirculating infiltrometer and field-scale measurements showed no consistent infiltration:wetted perimeter relationship. The infiltrometer data, collected using a wide range of flow rates on a wide range of slopes, did show infiltration inversely related to flow velocity. This relationship results from the effect of flow on soil aggregate breakdown, particle movement, and depositional seal formation. Because both velocity and wetted perimeter increase with flow rate, their opposing effects on infiltration can result in little apparent effect when flow rates change. These interactions strengthen the inverse relationship between infiltration and furrow slope.
Collaborative Networked Virtual Surgical Simulators (CNVSS) Implementing Hybrid Client–Server Architecture: Factors Affecting Collaborative Performance

Currently, surgical skills teaching in medical schools and hospitals is changing, requiring the development of new tools to focus on (i) the importance of the mentor’s role, (ii) teamwork skills training, and (iii) remote training support. Collaborative Networked Virtual Surgical Simulators (CNVSS) allow collaborative training of surgical procedures where remotely located users with different surgical roles can take part in the training session. To provide successful training involving good collaborative performance, CNVSS should guarantee synchronicity in time of the surgical scene viewed by each user and a quick response time which are affected by factors such as users’ machine capabilities and network conditions. To the best of our knowledge, the impact of these factors on the performance of CNVSS implementing hybrid client–server architecture has not been evaluated. In this paper the development of a CNVSS implementing a hybrid client–server architecture and two statistical designs of experiments (DOE) is described by using (i) a fractional factorial DOE and (ii) a central composite DOE, to determine the most influential factors and how these factors affect the collaboration in a CNVSS. From the results obtained, it was concluded that packet loss, bandwidth, and delay have a larger effect on the consistency of the shared virtual environment, whereas bandwidth, server machine capabilities, and delay and interaction between factors bandwidth and packet loss have a larger effect on the time difference and number of errors of the collaborative task.
Effect Of Vegetation Density On The Hydrodynamic Of Submerged Vegetated Flow

Vegetation density affects the hydrodynamic of flow field, increasing the hydraulic roughness scale; accelerate the conversion of mean kinetic energy into turbulent kinetic energy at the scale of the plant stems and branches. This study presents the laboratory experiment on the effect of increase in vegetation density using PIV techniques. The vegetation densities was varied while the channel bed-slope and submergence depth were kept constant. The results showed a remarkable reduction in flow rate, resulting in high turbulent shear stresses at the top of vegetation layer. It is evident that vegetation density is a significant vegetation parameter on the induction of hydraulic roughness.
New Toads and Frogs Results

We present a number of new results for the combinatorial game Toads and Frogs. We begin by presenting a set of simplification rules, which allow us to split positions into independent components or replace them with easily computable numerical values. Using these simplication rules, we prove that there are Toads and Frogs positions with arbitrary numerical values and arbitrarily high temperatures, and that any position in which all the pieces are contiguous has an integer value that can be computed quickly. We also give a closed form for the value of any starting position with one frog, and derive some partial results for two-frog positions. Finally, using a computer implementation of the rules, we derive new values for a large number of starting positions.
Dendroclimatic Relationships of Post Oak Across a Precipitation Gradient in the Southcentral United States

Abstract Post oak is a dominant species along the prairie border in the southcentral United States where upland forests gradually merge into the grasslands of the Southern Plains. These vegetation changes coincide with a sharp decrease in mean annual precipitation. Increment core studies at more than 50 sites from southern Texas to central Missouri indicate that old-growth post oak forests are still widespread, probably because these typically small, poorly formed trees were not systematically logged. Analysis of five tree-ring chronologies located across the precipitation gradient indicates that post oak radial growth is directly related to precipitation and inversely related to temperature for several months during and preceding the growing season. Post oak chronologies tend to become more variable and climate sensitive westward toward the prairie border, consistent with the decline in rainfall and the westward decrease in forest cover, species diversity, and tree size. This increase in climate sensitiv.
ExpansionNet: exploring the sequence length bottleneck in the Transformer for Image Captioning

Most recent state of art architectures rely on combi-nations and variations of three approaches: convolutional, recurrent and self-attentive methods. Our work attempts in laying the basis for a new research direction for sequence modeling based upon the idea of modifying the sequence length. In order to do that, we propose a new method called “Expansion Mechanism” which transforms either dynamically or statically the input sequence into a new one featuring a diﬀerent sequence length. Furthermore, we introduce a novel architecture that exploits such method and achieves competitive performances on the MS-COCO 2014 data set, yielding 134.6 and 131.4 CIDEr-D on the Karpathy test split in the ensemble and single model conﬁguration respectively and 130 CIDEr-D in the oﬃcial online testing server, despite being neither recurrent nor fully attentive. At the same time we address the eﬃciency aspect in our design and introduce a convenient training strategy suitable for most computational resources in contrast to the standard one. Source code is available at https://github.com/jchenghu/ExpansionNet.
Improving Graph Representation Learning by Contrastive Regularization

Graph representation learning is an important task with applications in various areas such as online social networks, e-commerce networks, WWW and semantic webs. For unsupervised graph representation learning, many algorithms such as Node2Vec and Graph-SAGE make use of “negative sampling” and/or noise contrastive estimation loss. This bears similar ideas to contrastive learning, which “contrasts” the node representation similarities of semantically similar (positive) pairs against those of negative pairs. However, despite the success of contrastive learning, we found that directly applying this technique to graph representation learning models (e.g., graph convolutional networks) does not always work. We theoretically analyze the generalization performance and pro-pose a light-weight regularization term that avoids the high scales of node representations’ norms and the high variance among them to improve the generalization performance. Our experimental re-sults further validate that this regularization term significantly improves the representation quality across different node similarity definitions and outperforms the state-of-the-art methods.
Microstructures in Diamictites of the Lower Gowganda Formation (Huronian), Near Elliot Lake, Ontario: Evidence for Deforming-Bed Conditions at the Grounding Line?

ABSTRACT Diamictites examined in the lower Gowganda Formation (2.5-2.2 Ga) to the north of Elliot Lake reveal a large number of macrostructures and microstructures. From micromorphological analyses the microstructures show a group of structures indicative of both ductile and brittle deformation likely developed during glacial sedimentation. The diamictites possibly were deposited in a proximal subglacial or subaqueous environment as a product of soft deforming-bed sediments being extruded beneath an active ice sheet at its grounding-line margin as it entered a marine basin. This is the first known example of glacial deforming-bed conditions being shown to have possibly developed beneath Precambrian ice sheets.
Propagation of drought through groundwater—a new approach using linear reservoir theory

The effect of drought on groundwater heads and discharge is often complex and poorly understood. Therefore the propagation of a drought from groundwater recharge to discharge and the influence of aquifer characteristics on the propagation was analysed by tracking a drought in recharge through a linear reservoir. The recharge was defined as a sinusoid function with a period of 1 year. The decrease in recharge owing to drought was simulated by multiplying the recharge during 1 year with a drought fraction between 0 and 1, which represents a decrease in the recharge of 100 to 0%, respectively. The droughts were identified using the threshold level approach, with a threshold that is constant in time. For this case analytical formulations were derived, which express the drought duration and deficit in the groundwater discharge in terms of the decrease in recharge, the reservoir coefficient that characterizes aquifer properties and the height of the threshold level. The results showed that the delay in the groundwater system caused a shift of the main part of the decrease in recharge from the high‐flow to the low‐flow period. This resulted in an increase in drought deficit for discharge compared with the drought deficit for recharge. Also the development of multiyear droughts caused an increase in drought deficit. The attenuation in the groundwater system caused a decrease in drought deficit. In most cases the net effect of these processes was an increase of drought deficit as a result of the propagation through groundwater. Only for small droughts the deficit decreased from recharge to discharge. The amount of increase or decrease depends on the reservoir coefficient and the severity of the drought. Under most conditions a maximum in the drought deficit occurred for a reservoir coefficient of around 200 days. Copyright © 2003 John Wiley & Sons, Ltd.
Large F‐region electron‐temperature enhancements generated by high‐power HF radio waves

During recent experiments at Arecibo, Puerto Rico, large (1000-2000 K) enhancements in electron temperature have been observed when high-power radio waves reflect near the nighttime F region peak. The electron temperature enhancements are accompanied by significant (50-300 K) increases in ion temperature, large (10-15%) reductions in electron density, and strong HF-induced spread F. When large electron temperature enhancements develop, the ionosphere appears to become dynamically unstable resulting in the production of geomagnetic field-aligned striations having elevated electron temperatures and depleted electron densities.
Middening in the Outer Hebrides : an ethnoarchaeological investigation

This thesis comprises two complementary parts: an investigation, using interviews and published accounts, of how and why nutrients are recycled in a 'traditional' farming economy; and an ethnoarchaeological analysis of samples from an abandoned farmstead to identify potential traces of recycling. The Uists and Benbecula in the Outer Hebrides were selected for fieldwork because local conditions favoured intensive recycling in the recent past, farmers with experience of such practices are still available for interview, and surviving farmers can identify functional areas on abandoned farmsteads. Interviews and published sources emphasise the importance of recycling in maintaining the fertility of cultivated blacklands and peatlands and in enhancing the fertility, stability and water-retentiveness of cultivated machair. The use of nutrients reflects their intrinsic properties, their availability and the characteristics of different land types. For example, dung is preferentially applied to blackland and staple grain crops, seaweed to machair and fodder crops. Dung and seaweed are complementary in availability: dung from overwintering livestock is subject to the same constraints as arable farming, while seaweed is most abundant in stormy winters, a slack time for farmers. Samples from different functional areas within an abandoned farmstead were analysed for biological, physical and chemical composition. Functional areas can be distinguished using the variables measured. This results from, and allows the tracing of, the recycling of resources within the farmstead, from the barn and kiln to the byre, thence to the midden and finally to the vegetable plot. In conclusion, archaeological implications are briefly explored for the Outer Hebrides. Intensive recycling may have been less necessary and the accumulation of dung less difficult in prehistory, if climate was warmer, soils more fertile, population density lower and society less inegalitarian. Iron age 'midden' sites with deep organic dumps may be evidence that recycling was indeed less intensive.
Are two elements better than one? Dual isotope‐ratio detrending of evaporative effects on lake carbonate paleoelevation proxies

Stable isotope‐based proxy methods enhance our ability to interpret geodynamical histories for tectonic provinces via paleoelevational reconstructions. These methods require that the unmodified isotopic composition of meteoric water is recorded by authigenic minerals, a critical assumption that has not been tested across wide‐ranging environmental and topographical contexts. Here, we show that Quaternary lake carbonateδ18O values are not strongly, nor significantly, correlated with regional elevation due to the isotopic modification of in‐flow waters following entry into the lake environment. These modifications are largely caused by surface water evaporation, and can result in >3 km errors in paleoelevation estimates if not accounted for. However, our analysis suggests that positive shifts in surface waterδ18O are accompanied by similar magnitude shifts in δ13C‐DIC. This positive co‐variation inδ18O and δ13C may be used to detrend lake carbonate compositions for the effects of surface water evaporation using a parameter we define here as the ‘13C‐excess’. When Tibetan lakes are excluded from the data set,13C‐excess values are significantly correlated with mean up‐slope hypsometric altitude with an error of ±500 m. Application of the13C‐excess approach to Cenozoic lake carbonate records from the western U.S. Cordillera both challenges and reinforces previous paleoelevational interpretations based onδ18O alone.