Miracle-dz/UniFAR-FTUs huggingface dataset:
The production of secondary ice particles during riming

Two series of experiments were undertaken to investigate whether secondary ice particles are thrown off during the accretion of supercooled water drops upon an ice surface. Riming took place in cloud at a temperature of about −9°C, and the accreted droplets were of various diameters up to 100 μm. Drops were accreted upon targets moving at velocities from 0·15 to 2·1 m s−1. The number of secondary ice particles produced per unit mass of rime appears to be far too low to account for the high concentrations of ice particles observed in some natural clouds.1
Analysis of submarine sand wave imaging by SAR in Taiwan shoal

In this paper, submarine sand wave imaging by SAR in Taiwan shoal and their relationships with sea surface wind and sea surface current are discussed. A total of 69 synthetic aperture radar (SAR) images over 11 years between 1996 and 2006 are collected and 496 profiles of sand wave SAR images are used for the observations of sand wave SAR images. The sea surface wind estimated from NCEP/QSCAT blended wind data and the sea surface current calculated form highfrequency (HF) radar system are utilized for the study on the observations of sand wave SAR images with the wind speed and current speed. The results show submarine sand waves in Taiwan Shoal are mainly distributed from 117.75°E to 118.70°E and 22.7°N to 23.35°N with a high percent of 72.2. About 91% of sand waves are observed by SAR under wind speed of 9 m/s while only 6% of sand waves are imaged above wind speed of 10 m/s. And under the adverse wind direction, the observed sand wave reaches its maximum, while the crosswind has its minimum. These support that low and middle wind speed and adverse wind direction are favorable for SAR imaging submarine sand waves, high wind speed and crosswind are unfavorable. The observations of sand wave SAR images reach its seasonal maximum with a percentage of 49 in summer and have its minimum in autumn with 8%, while spring and winter has percentage of 20 and 23 respectively. The comparisons for monthly mean sea surface wind speed and monthly mean sea surface current speed with observed sand waves also shows strong relationships, which are lower sea surface wind speeds and higher sea surface current speed, the higher probability of sand waves observed by SAR. This may indicate that the higher observation of the sand waves by SAR is partly due to wind speed and current speed.
Corporate Social Responsibility and Shareholder's Value: An Event Study Analysis

Corporate social responsibility (CSR) has become one of the core components of corporate strategy and a crucial instrument to minimize conflicts with stakeholders. While corporations are busy adopting and enhancing CSR practices, the academic literature on understanding the impact of CSR is scarce, especially in the capital market. This paper traces the market reaction to corporate entry and exit from the Domini 400 Social Index, recognized as a CSR benchmark, between 1990 and 2004. The results reveal a significant negative effect on abnormal returns after exit announcements from the Domini index. The effect persists even after controlling for concurring financial distress shocks and stock market seasonality.
Ecotypological Assessment of Mangrove ecosystem in Tropical Estuarine: Case study in Segara Anakan Estuarine, Cilacap, Central Java

The purpose of this paper is to evaluate the condition of ekotypology the mangrove ecosystem in Segara Anakan Estuarine. covering broad estimates, the distribution of mangroves and vegetation typology. Wide estimation and distribution of mangrove approximated with spatial analysis of vegetation index using unsupervised classification and normalized difference vegetation index (NDV) I, while the mangrove vegetation typology using transect quadratic single method swath on 3 replications. Data were analyzed to obtain the value of the relative density, relative dominance, relative frequency, importance value, diversity and distribution patterns. Research has also found that extensive mangrove decreased by 2.550,69 ha 62,02 % over the previous year. Mangrove vegetation composed by 27 species, including 17 species of trees, 2 types of shrubs, two types of climbers, three kinds of nails ferns/palm, and 3 types of herbaceous ground. Abundance of species ranges between 13-12475 ind/ha. Typology of vegetation around the zone belonging to the low diversity (H '<2) where the eastern zone dominated kind Rhizopora apiculata (IVI = 97.62 to 154.99%), in the middle zone kind R. apiculata, Agiceras . corniculatum, and N. fruticant INP range from 58.97 to 67.09%, while the western zone of S. caseolaris and A. marina (IVI 46.80 to 148.02). The pattern of spread of the type forming an irregular pattern, except on the type of R. apiculata and S. caseolaris spread group (clumped).
Crop Evapotranspiration and Irrigation Scheduling in Blueberry

There are currently 139,000 ha of blueberry worldwide, including 66,000 ha of highbush [comprises northern highbush (Vaccinium corymbosum), southern highbush (Vaccinium sp.), and rabbiteye (V. virgatum formerly V. asheii) cultivars] and 73,000 ha of lowbush blueberry (V. angustifolium) (Strik & Yarborough, 2005; USHBC, 2009). The majority of the fruit is produced in North and South America and Europe, although production is increasing in Asia and Africa. No matter where blueberry is grown, proper irrigation management is critical for producing high yields and good fruit quality. Even within a few days without rain or irrigation, water stress develops quickly in blueberry, reducing photosynthesis and leading to less growth and fruit production. Over irrigation, however, reduces blueberry root function, increases soil erosion and nutrient leaching, and enhances the probability of developing crown and root rot infection by soil pathogens such as Phytophthora. Developing accurate irrigation regimes requires knowledge of both the timing and amount of water needed to replenish any lost by crop transpiration and soil evaporation. In this chapter, I discuss the importance of irrigation on growth and development in blueberry and examine its relationship to plant water relations. Identified are symptoms of water stress, the most critical stages of water limitations, and various techniques used to monitor plant water status throughout the growing season. I then discuss irrigation scheduling for blueberry, including procedures used to calculate crop evapotranspiration and estimate total irrigation requirements, and finally present recent data on the best methods to apply irrigation. Information is provided on the response of blueberry to not only different irrigation systems and configurations but also of when and where to apply the water. Throughout the chapter, irrigation methods and practices are related to other factors essential to consider when growing blueberries, including interactions with field establishment, planting bed management, nitrogen nutrition, and root disease.
Effects of dykes on plant species composition in a large lowland river floodplain

The effects of floodplain fragmentation by dykes on grassland vegetation were evaluated through field studies along the Middle Elbe River (federal states Saxony‐Anhalt and Brandenburg, Germany). Plant species composition was examined in 206 sites between 1996 and 1998 in the entire floodplain, which can be divided into the floodplain types ‘recent floodplain’, ‘older floodplain’ (which is separated from the recent one by dykes) and the ‘margin of the floodplain’ (which is the part of the older floodplain that forms the boundary and is furthest from the river). Dynamics in hydrology were examined weekly between November 1996 and February 1999 with the help of 40 water level wells which were installed near the studied sites. The hydrological parameters ‘average water level’, ‘average groundwater level’, ‘flooding duration’, ‘flooding depth higher 50 cm above soil surface’ and ‘standard deviation of the water level line’ were calculated to characterize the considered floodplain types and to relate species composition to hydrology. Furthermore several parameters of current management of the vegetation were recorded to evaluate the importance of land use versus hydrology for floodplain grasslands.
A rate-dependent model for the ductile behavior of salt rocks

Salt rocks, such as potash and rock salt, show a complex mechanical behavior that is rate and history dependent. Various approaches exist to represent the main features of the response of these rocks through constitutive models. The approach proposed in this paper is to formulate the constitutive equations using internal state variables (ISV) in the context of the unified theory of inelastic flow. To illustrate the application of this approach, the authors use an updated version of a viscoplastic model with reduced expressions for laboratory triaxial tests at relatively high confining pressure. It is shown that, under these conditions, mixed hardening of salt rocks can be described through a combination of scalar and directional ISV. The authors also describe in some detail a procedure to obtain the material parameters for the model equations. The paper shows some characteristics of the model response for various loading paths, illustrating the good agreement with experimental observations and highlightin.
GCM Simulations of the Three-Dimensional Propagation of Stationary Waves

Abstract Plumb's formulation of the stationary wave activity flux is used to determine how well versions of the GFDL and NCAR general circulation models simulate the sources, sinks, and horizontal propagation of atmospheric stationary waves, which play an important role in determining regional climate. The wave activity flux provides insight into the simulation of nondynamic as well as dynamic processes in these models. Model performances for current climate simulations are evaluated with respect to NMC analyses averaged over 1978–1990. The models fare best when the stationary wave forcing is strongest, that is, in the wintertime Northern Hemisphere, where they reproduce the observed three-branch structure of upward wave activity flux. For the Northern Hemisphere summer and the Southern Hemisphere in both summer and winter, the models show less agreement with observations, although they do simulate the generally downward flux observed during Northern Hemisphere summer, which the analysis suggests is cause.
Estimation of clear‐sky land surface longwave radiation from MODIS data products by merging multiple models

[1] The surface longwave radiation budget plays an important role in the Earth's climate system. Remote sensing provides the most practical way to map surface longwave radiation on a large scale and at a high spatial resolution. In this paper, we evaluate both surface downward longwave radiation (DLR) and upwelling longwave radiation (ULR) models under clear-sky conditions from MODIS data products. There are multiple DLR models available with variable uncertainties, and the Bayesian Model Averaging (BMA) method is incorporated in this study to combine the predictive distribution of these models for better accuracy. The integrated estimates for DLR based on the BMA method have lower root-mean-square errors (RMSEs) and higher coefficients of determination (R2) than the best individual model. The RMSEs decreased by approximately 10 W/m2 at two forest sites and by approximately 4 W/m2 at other sites. The R2value increased at each site by more than 0.05. Two models for calculating the surface upwelling longwave radiation (ULR) are also evaluated at 16 sites. The results show that both the land surface temperature (LST)–emissivity method and the direct method, the Wang-U model underestimate the clear-sky ULR. The validation results show that the surface net longwave radiation (NLR) estimated using DLR estimates based on the BMA method and ULR estimates based on the LST-emissivity method is the most accurate.
It’s not a ‘thing’ but a ‘place’: reconceptualising ‘assets’ in the context of fire risk landscapes

At a national policy level, Australian governments have embraced the notion of shared responsibility between agencies and communities for disaster resilience, including bushfire. Emergency management agencies take an asset-based approach to management based on an assumption that valued places can be quantified by cataloguing individual ‘things’ in the landscape. Implicit in shared responsibility, however, is incorporation of local knowledge of landscape and risk into planning. This already difficult task can be made more complex as local constructions of risk in the landscape sometimes appear at odds with management agency perspectives. This research examined local constructions of bushfire risk in two contrasting Australian landscapes – one semi-rural, one peri-urban. The results suggest that local ecological knowledge arises from interactions between people, the landscape and objects (e.g. flora and fauna) in the landscape. Place meanings transcend individual ‘things’, emerging instead from experience of the whole landscape, both social and ecological and at multiple scales. We argue therefore, that understanding bushfire cannot be segregated from wider social and ecological processes at a landscape level. Shared responsibility will involve respectful and meaningful engagement between agencies and landholders in collaborative planning to ensure local knowledge informs asset-based management.
A simplified semiempirical approach to probabilities of extreme hydrologic droughts

On the basis of an available theory approximately valid for stationary first-order two-state Markovian processes and an assumption that the distribution of drought severity is approximately two-parameter gamma, a semiempirical method is proposed for the estimation of the probabilities of extreme drought durations and severities which may occur in the annual flow sequence of a stream during a period of finite length. The method is applied to the annual flows of eight streams in various parts of the world, and the semiempirical probability distributions obtained using this method are compared with experimental distributions obtained using synthetic streamflows generated with a lag one Markov model as well as a long-memory broken line model. The comparisons suggest that considerable insight into the extreme drought probabilities can be gained by the use of the simple semiempirical method introduced here.
Neural Acoustic Context Field: Rendering Realistic Room Impulse Response With Neural Fields

Room impulse response (RIR), which measures the sound propagation within an environment, is critical for synthesizing high-fidelity audio for a given environment. Some prior work has proposed representing RIR as a neural field function of the sound emitter and receiver positions. However, these methods do not sufficiently consider the acoustic properties of an audio scene, leading to unsatisfactory performance. This letter proposes a novel Neural Acoustic Context Field approach, called NACF, to parameterize an audio scene by leveraging multiple acoustic contexts, such as geometry, material property, and spatial information. Driven by the unique properties of RIR, i.e., temporal un-smoothness and monotonic energy attenuation, we design a temporal correlation module and multi-scale energy decay criterion. Experimental results show that NACF outperforms existing field-based methods by a notable margin. Please visit our project page for more qualitative results.
The role of climate variability and fire in early and mid Holocene forest dynamics of southern Sweden

The objective of this study was to investigate the possible links between regional climate, fire and vegetation at the small spatial scale during the early and mid Holocene in southern Sweden using pollen, plant macrofossil and charcoal records from a small bog. The fire history was compared with climate reconstructions inferred from various proxy records in the study region. High fire activity is related to dry and warm climate around 8550, 7600, 5500–5100 and 4500 cal. a BC. Low fire activity ca. 6500–6000 and 4750 BC may correspond to the widespread ‘8.2 k event’ (ca. 6200 BC) recorded across the North Atlantic region, and a later, brief period of increased precipitation, respectively. The decrease in broadleaved trees culminating ca. 6500–6000 BC correlates with the ‘8.2 k event’. A long mid Holocene period with low fire activity (ca. 4350–1000 BC) agrees with the pattern emerging for Europe from the global charcoal database, and may correspond to generally wetter and cooler conditions. High fire activity ca. 8550 BC probably triggered the local establishment of Corylus. Warmer and drier conditions (and high fire activity) ca. 7600 BC might have favoured the establishment of Alnus, Quercus and Tilia. The fire‐adapted Pinus maintained important populations throughout the early and mid Holocene. Copyright © 2008 John Wiley & Sons, Ltd.
Using Weak Supervision and Data Augmentation in Question Answering

The onset of the COVID-19 pandemic accentuated the need for access to biomedical literature to answer timely and disease-specific questions. During the early days of the pandemic, one of the biggest challenges we faced was the lack of peer-reviewed biomedical articles on COVID-19 that could be used to train machine learning models for question answering (QA). In this paper, we explore the roles weak supervision and data augmentation play in training deep neural network QA models. First, we investigate whether labels generated automatically from the structured abstracts of scholarly papers using an information retrieval algorithm, BM25, provide a weak supervision signal to train an extractive QA model. We also curate new QA pairs using information retrieval techniques, guided by the clinicaltrials.gov schema and the structured abstracts of articles, in the absence of annotated data from biomedical domain experts. Furthermore, we explore augmenting the training data of a deep neural network model with linguistic features from external sources such as lexical databases to account for variations in word morphology and meaning. To better utilize our training data, we apply curriculum learning to domain adaptation, fine-tuning our QA model in stages based on characteristics of the QA pairs. We evaluate our methods in the context of QA models at the core of a system to answer questions about COVID-19.
Errors in Radar CMP Velocity Estimates Due to Survey Geometry, and Their Implication for Ice Water Content Estimation

The accuracy of velocity determination from common mid-point (CMP) ground penetrating radar surveys has been assessed in the past and found to be sufficient for migration and depth determination. Increasingly, these velocities are also being used to quantify subsurface physical properties such as water content. This paper demonstrates that small errors in measured velocity can result in large errors in these derived properties. We have evaluated the size of some error sources with specific reference to a given glaciological model and common glaciological survey conditions. At worst, large static errors and 3% errors in measured offset result in interval velocity errors of ∼8.6%. This error is large enough that derived water content has an error greater than 80% (e.g., 2.8±2.4 volumetric % water). Common acquisition and processing practices result in ∼4.9% interval velocity errors (corresponding to ∼50% error in water content, e.g., 2.8±1.4 volumetric %); best practices could result in errors as low as ∼0.
Deterministic Fully Dynamic SSSP and More

We present the first non-trivial fully dynamic algorithm maintaining exact single-source distances in unweighted graphs. This resolves an open problem stated by Sankowski [COCOON 2005] and van den Brand and Nanongkai [FOCS 2019]. Previous fully dynamic single-source distances data structures were all approximate, but so far, non-trivial dynamic algorithms for the exact setting could only be ruled out for polynomially weighted graphs (Abboud and Vassilevska Williams, [FOCS 2014]). The exact unweighted case remained the main case for which neither a subquadratic dynamic algorithm nor a quadratic lower bound was known.Our dynamic algorithm works on directed graphs and is deterministic, and can report a single-source shortest paths tree in subquadratic time as well. Thus we also obtain the first deterministic fully dynamic data structure for reachability (transitive closure) with subquadratic update and query time. This answers an open problem of van den Brand, Nanongkai, and Saranurak [FOCS 2019]. Finally, using the same framework we obtain the first fully dynamic data structure maintaining all-pairs $(1+\epsilon)$-approximate distances within non-trivial sub-$n^{\omega}$ worst-case update time while supporting optimal-time approximate shortest path reporting at the same time. This data structure is also deterministic and therefore implies the first known non-trivial deterministic worst-case bound for recomputing the transitive closure of a digraph.
Sensorless Estimation of Contact Using Deep-Learning for Human-Robot Interaction

Physical human-robot interaction has been an area of interest for decades. Collaborative tasks, such as joint compliance, demand high-quality joint torque sensing. While external torque sensors are reliable, they come with the drawbacks of being expensive and vulnerable to impacts. To address these issues, studies have been conducted to estimate external torques using only internal signals, such as joint states and current measurements. However, insufficient attention has been given to friction hysteresis approximation, which is crucial for tasks involving extensive dynamic to static state transitions. In this paper, we propose a deep-learning-based method that leverages a novel long-term memory scheme to achieve dynamics identification, accurately approximating the static hysteresis. We also introduce modifications to the well-known Residual Learning architecture, retaining high accuracy while reducing inference time. The robustness of the proposed method is illustrated through a joint compliance and task compliance experiment.
Integrated urban data visualising and decision-making framework

The work package (WP) 2 on Basic Exploration, Stakeholder Studies and Requirement Analysis created the scientific fundament of the project and produced essential knowledge for the conceptualisation of UrbanData2Decide. Task 2.5 brought together the previous research results and elaborated an integrated research model as well as a stakeholder requirements catalogue with first use case scenarios. In this integrated deliverable previous results of WP2 were combined to define a first blueprint for the UrbanData2Decide system as it will be developed later in the project.
Theory of non-Hermitian fermionic superfluidity on a honeycomb lattice: Interplay between exceptional manifolds and Van Hove singularity

We study the non-Hermitian fermionic superfluidity subject to dissipation of Cooper pairs on a honeycomb lattice, for which we analyze the attractive Hubbard model with a complex-valued interaction. Remarkably, we demonstrate the emergence of the dissipation-induced superfluid phase that is anomalously enlarged by a cusp on the phase boundary. We find that this unconventional phase transition originates from the interplay between exceptional lines and van Hove singularity, which has no counterpart in equilibrium. Moreover, we demonstrate that the infinitesimal dissipation induces the nontrivial superfluid solution at the critical point. Our results can be tested in ultracold atoms with photoassociation techniques by postselcting special measurement outcomes with the use of quantum-gas microscopy and can lead to understanding the NH many-body physics triggered by exceptional manifolds in open quantum systems.