Miracle-dz/UniFAR-FTUs huggingface dataset:
The institutional design of river basin organizations – empirical findings from around the world

ABSTRACT River basin organizations (RBOs) have become a key feature of international water resources governance, providing riparian states with multiple means for overcoming collective action problems that emerge due to the transboundary nature of resources. However, little is known about the RBOs themselves, especially with regard to their organizational structure as well as the mechanisms they actually employ for governing water resources. This paper presents a comprehensive overview of the institutional design of all international RBOs by summarizing the empirical data available through the RBO Institutional Design Database in the context of the Transboundary Freshwater Dispute Database. It contributes to both water resources governance research, requiring institutional design data in order compare different RBOs or to comprehensively assess the contributions RBOs can make to better governing shared watercourses, as well as policy, facing the challenge of establishing new or reforming existing RBOs for more sustainable water resources governance in shared basins.
Learning from the Veg Box: Designing Unpredictability in Agency Delegation

The Internet of Things (IoT) promises to enable applications that foster a more efficient, sustainable, and healthy way of life. If end-users are to take full advantage of these developments we foresee the need for future IoT systems and services to include an element of autonomy and support the delegation of agency to software processes and connected devices. To inform the design of such future technology, we report on a breaching experiment designed to investigate how people integrate an unpredictable service, through the veg box scheme, in everyday life. Findings from our semi-structured interviews and a two-week diary study with 11 households reveal that agency delegation must be warranted, that it must be possible to incorporate delegated decisions into everyday activities, and that delegation is subject to constraint. We further discuss design implications on the need to support people's diverse values, and their coordinative and creative practices.
Lagged response of nutrient leaching to reduced surpluses at the field and catchment scales

Lag times in reduced nutrient leaching after improved agricultural practices must be assessed to inform management decisions and evaluate their cost‐effectiveness. This study estimated the leaching of phosphorus (P) and nitrogen (N) at two scales, a 33.8‐ha nested field (data from 1973 to 2011) and an 820‐ha agricultural catchment (data from 1992 to 2010). Field management was evaluated along with long‐term nutrient trends. Estimates including and excluding nutrient concentrations in the stream under dry catchment conditions (mean 2.5 months year−1) revealed that wastewater contributed 10% of the total P (TP) catchment leaching, mostly in dissolved reactive (DRP) form. More recent flow‐proportional sampling at the two scales demonstrated 45% higher particulate P leaching from the field than with discrete water sampling, whereas a past discrete sampling strategy may have overestimated DRP contributions to the stream. The accumulated field P balance was increasingly negative after 1987, whereas crop yields increased. From 1998, the measured accumulated TP leaching from the field was lower than the mean accumulated leaching, considering the estimated downward trend (−10%) over the 38‐year study period (p < 0.05).
Compositional variation of aeschynite-group minerals in the Bayan Obo Nb-REE-Fe ore deposit, Inner Mongolia, China

The aeschynite-group minerals occurring in an aegirine-fluorite-dolomite- aeschynite vein in the Bayan Obo Nb-REE-Fe deposit show complex compositional zoning in BSE images. Microprobe analyses revealed that the concentrations of REE2O3 are globally high in aeschynite-group minerals, ranging from 36.72 to 40.32 wt. %. Four species were identified in the same sample, these being aeschynite-(Ce), aeschynite-(Nd), nioboaeschynite-(Ce) and nioboaeschynite-(Nd). The correlations among cations suggest two special coupled substitutions with charge-balanced described by the exchange vectors as CaNb(Nd,Sm,Pr)-1 Ti-1 and LaNbTh-1 Ti-1. The chondrite-normalized REE patterns are hump-shaped with the maximum at Pr or Nd. The chondrite-nomalized La/Nd ratios vary in the range ∼0.15 to 0.40. It indicates that at Bayan Obo aeschynite minerals are relatively strongly La-depleted and Nd-enriched. The compositional variations in aeschynite-group minerals were controlled by the crystal chemistry and affected by fluid composition.
Does Distributionally Robust Supervised Learning Give Robust Classifiers?

Distributionally Robust Supervised Learning (DRSL) is necessary for building reliable machine learning systems. When machine learning is deployed in the real world, its performance can be significantly degraded because test data may follow a different distribution from training data. DRSL with f-divergences explicitly considers the worst-case distribution shift by minimizing the adversarially reweighted training loss. In this paper, we analyze this DRSL, focusing on the classification scenario. Since the DRSL is explicitly formulated for a distribution shift scenario, we naturally expect it to give a robust classifier that can aggressively handle shifted distributions. However, surprisingly, we prove that the DRSL just ends up giving a classifier that exactly fits the given training distribution, which is too pessimistic. This pessimism comes from two sources: the particular losses used in classification and the fact that the variety of distributions to which the DRSL tries to be robust is too wide. Motivated by our analysis, we propose simple DRSL that overcomes this pessimism and empirically demonstrate its effectiveness.
Early Holocene glacial lake meltwater injections into the Labrador Sea and Ungava Bay

[1] In this paper we analyze drainage routes and estimate fluxes of meltwater released from Labrador-Ungava glacial lakes into the Labrador Sea, Ungava Bay, and Hudson Bay between 7.5 and 6.0 kyr BP (8.4–7.0 calendar (cal) years ka). The analysis and estimates are based on landform-based reconstructions of the Laurentide Ice Sheet (LIS) decay pattern and the associated glacial lake evolution. Geomorphological data constraining the spatial extent of glacial lakes are coupled to a digital terrain model for meltwater volume calculations. The LIS ice recession between 7.5 and 6.0 kyr BP led to the formation of a large number of glacial lakes, which drained in approximately 30 meltwater pulses, with fluxes exceeding 0.015 Sv (1 Sv = 106 m3 s−1), into Labrador Sea, Ungava Bay, and Hudson Bay. The inferred rapid ice margin retreat during late stages of deglaciation indicates that these drainage events were relatively short-lived. The early Holocene glacial lakes of Labrador-Ungava released meltwater, resulting in a total inflow of ∼6000 km3 freshwater to the North Atlantic. The pulsed nature of meltwater release from the lakes is likely to have resulted in rapid repeated cooling of the Labrador Sea surface water.
Six-DoF pose estimation using dual-axis rotating laser sweeps using a probabilistic framework

Pose estimation systems have seen some big developments in the last two decades due to technological advances and a greater need for these systems. The industry that thrives and simultaneously popularizes these developments is the entertainment industry. One of the latest developments in home entertainment are Virtual Reality systems that lets users have an immersive experience when playing video games. In order to fully achieve this immersive experience, objects in the ‘real world’ can be used to manipulate objects in the virtual world. Therefore the ‘real world’ objects need to be located in the user's environment to a great extent. One of these virtual reality kits utilizes an optical solution that incorporates dual-axis rotating laser sweeps on the transmitter side and photodiodes on the receiver side to achieve the positioning of these objects. Since the transmitters are stand-alone systems that can be purchased at a relatively low price, we propose to use this hardware in combination with custom low-cost receiver hardware to achieve an affordable yet precise and accurate six degrees-of-freedom human body pose estimation system.
High‐resolution sequence stratigraphy of a Hettangian‐Sinemurian paralic succession, Bornholm, Denmark

Sequence stratigraphic interpretation of paralic successions is complicated by the complex interfingering of marine and continental strata. The successions may also include terrestrial extensions of marine parasequences and completely independent lacustrine parasequence analogues. Failure in recognizing the possible interbeddding of these two independent parasequence types may lead to construction of sequence stratigraphic schemes based on incompatible data sets. We have studied a Lower Jurassic paralic section from the Baltic island of Bornholm, situated in the Tornquist Zone, which demarcates the transition from the stable Precambrian Baltic Shield to the subsiding Danish Basin and Danish-Polish Trough. The Hettangian-Sinemurian Sose Bugt Member (Ronne Formation) of Bornholm includes lacustrine, fluvial and restricted marine, estuarine deposits reflecting the basin-margin position. Biostatigraphic resolution is poor and a sequence stratigraphic interpretation of the paralic succession is far from straightforward. A multidisciplinary approach including facies analysis, recognition and lateral trading of key surfaces, palynostratigraphy, palynofacies, coal petrography, palaeopedology, clay mineralogy and source rock geochemistry is applied in order to obtain a high degree of precision in the interpretation of the paralic facies. In this way four sequences are recognized in the overall backstepping lacustrine to estuarine succession. Marine and marginal marine parasequences are distinguished from their purely lacustrine analogues, and an internally consistent sequence stratigraphic scheme is proposed. This is compared and tentatively correlated with fossiliferous marine sediments in the Danish Basin and with published eustatic cycle charts.
Nonlinear Properties of Random Gravity Waves in Water of Finite Depth

Abstract The weakly nonlinear theory for a stationary and homogeneous field of random gravity waves in water of finite depth is developed to the third order. This describes the second-order nonlinearities as a bound wavefield that can be expressed in terms of the freely propagating first-order waves. Expressions are obtained for the second-order spectrum and for the first nonlinear correction to the free-wave phase velocity. Calculations of these nonlinearities are made for a specified spectral form (the TMA spectrum) and also for some spectra derived from measurements. Three influences are considered: (i) the directional distribution, which spreads the interacting waves and, if narrow, will enhance the bound-wave contribution to the spectrum; (ii) the growth stage, or maturity, which is quantified by the ratio of the phase velocity at the peak frequency to the surface friction velocity and, if small, will increase the nonlinearity considerably; and (iii) the depth. Although the nonlinearity increases for.
CONCURRENCY AND COMPUTATION : PRACTICE AND EXPERIENCE Concurrency Computat

The paper presents an extension of the composite programmable graph grammar (CP-graph grammar) suitable for modeling the parallel direct solver algorithm utilized by the hp finite element method (hpFEM). In the proposed graph grammar model, the computational mesh is represented by a CP-graph. The presented graph grammar models the solver algorithm by a set of graph grammar productions. The graph grammar model makes it possible to examine the concurrency of the algorithm by analyzing the interdependence between the atomic tasks, tasks and super-tasks. The atomic tasks correspond to the graph grammar productions, representing basic undividable parts of the algorithms. The level of atomic tasks models the concurrency for the shared memory architectures. On the other hand, the tasks correspond to the groups of atomic tasks with predefined inter-task communication channels. They constitute the grain for the decomposition of the parallel algorithm for the distributed memory architecture. Finally, the super-tasks correspond to a group of tasks resulting from the execution of load balancing algorithm. The solver algorithm is tested on distributed memory linux cluster for up to 192 processors. Copyright © 2009 John Wiley & Sons, Ltd.
Evaluation of Time Lapse Acoustic Monitoring of Immiscible Fluid Flows in Near Surface by Attenuation Examination Method

Velocity information alone, in acoustic monitoring of fluid fronts and interfaces when non-aqueous spills occur in the near surface unconsolidated sediments or water table/aquifers, and of those associated with consequent remediation, may not describe such immiscible flows and displacement fronts adequately. Attenuation characteristics examination, for its greater sensitivity to subsurface fluids, can offer better resolution in describing such subsurface processes. Characterization of controlled immiscible fluid displacement process signifying examination of attenuation characteristics, by comparing spectral curves, so, is demonstrated as extended results of an experimental study. In the experiment oil is displaced with brine, flowed through a saturated pack of ceramic beads against gravity under controlled constant head flow conditions. P-wave data were acquired employing pulse transmission with 1MHz sensors. Pertinent concise review of well studied wave attenuation mechanisms and associated anelastic and viscoelastic models is provided for connective lucidity of presented results and interpretation. Application of the method following a benchmarked time-lapse type workflow for data analyses, results presentation and plausible inferring/interpretation is effectively evaluated. Cited method unambiguously resolved, oil from brine and the interfacial mixing and evolution. Subtle insight instilling and interpretation enhancing frequency dependent combined effects related to fluid density, viscosity and flow rate were observed, too.
Revisiting Experience Replay: Continual Learning by Adaptively Tuning Task-wise Relationship

Continual learning requires models to learn new tasks while maintaining previously learned knowledge. Various algorithms have been proposed to address this real challenge. Till now, rehearsal-based methods, such as experience re-play, have achieved state-of-the-art performance. These approaches save a small part of the data of the past tasks as a memory buffer to prevent models from forgetting previously learned knowledge. However, most of them treat every new task equally, i.e., ﬁxed the hyperparameters of the framework while learning different new tasks. Such a setting lacks the consideration of the relationship/similarity between past and new tasks. For example, the previous knowledge/features learned from dogs are more beneﬁcial for the identiﬁcation of cats (new task), compared to those learned from buses. In this regard, we propose a meta learning algorithm based on bi-level optimization to adaptively tune the relationship be-tween the knowledge extracted from the past and new tasks. Therefore, the model can ﬁnd an appropriate direction of gradient during continual learning and avoid the serious overﬁt-ting problem on memory buffer. Extensive experiments are conducted on three publicly available datasets ( i.e., CIFAR-10, CIFAR-100, and Tiny ImageNet). The experimental re-sults demonstrate that the proposed method can consistently improve the performance of all baselines.
Time‐dependent shortest paths with discounted waits

We study a variant of the shortest path problem in a congested environment. In this setting, the travel time of each arc is represented by a piecewise continuous affine function of departure time. Besides, the driver is allowed to wait at nodes to avoid wasting time in traffic. While waiting, the driver is able to perform useful tasks for her job or herself, so the objective is to minimize only driving time. Although optimal solutions may contain cycles and pseudo‐polynomially many arcs, we provide a representation of the solutions that is polynomial in the absolute value of the inverse of the slopes as well as in the dimensions of the graph. We further prove that the problem is NP ‐Hard when the slopes are integer. We introduce a restriction of the problem where waits must be integer and propose pseudo‐polynomial algorithms for the latter. We also provide a pseudo‐FPTAS, polynomial in the ratio between the bound on the total waiting time and the minimum travel time. Finally, we discuss harder variants of the problem and show their inapproximability.
Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification

Motivated by a sampling problem basic to computational statistical inference, we develop a toolset based on spectral sparsification for a family of fundamental problems involving Gaussian sampling, matrix functionals, and reversible Markov chains. Drawing on the connection between Gaussian graphical models and the recent breakthroughs in spectral graph theory, we give the first nearly linear time algorithm for the following basic matrix problem: Given an n× n Laplacian matrix M and a constant −1 ≤ p ≤ 1, provide efficient access to a sparse n× n linear operator C such that M ≈ CC>, where ≈ denotes spectral similarity. When p is set to −1, this gives the first parallel sampling algorithm that is essentially optimal both in total work and randomness for Gaussian random fields with symmetric diagonally dominant (SDD) precision matrices. It only requires nearly linear work and 2n i.i. d. random univariate Gaussian samples to generate an n-dimensional i.i. d. Gaussian random sample in polylogarithmic depth. The key ingredient of our approach is an integration of spectral sparsification with multilevel method: Our algorithms are based on factoring M into a product of well-conditioned matrices, then introducing powers and replacing dense matrices with sparse approximations. We give two sparsification methods for this approach that may be of independent interest. The first invokes Maclaurin series on the factors, while the second builds on our new nearly linear time spectral sparsification algorithm for random-walk matrix polynomials. We expect these algorithmic advances will also help to strengthen the connection between machine learning and spectral graph theory, two of the most active fields in understanding large data and networks.
The Starburst Active Database Rule System

The paper describes the development of the Starburst Rule System, an active database rules facility integrated into the Starburst extensible relational database system at the IBM Almaden Research Center. The Starburst rule language is based on arbitrary database state transitions rather than tuple or statement level changes, yielding a clear and flexible execution semantics. The rule system has been implemented completely. Its rapid implementation was facilitated by the extensibility features of Starburst, and rule management and rule processing are integrated into all aspects of database processing.
La experiencia integradora de un Centro de Educación Primaria desde la perspectiva del profesorado

In this article we present a study, which was realized in a primary school in the region of Murcia and whose objective was to observe, how the educational phenomena developed in their natural environment (classroom) through interpretations of their main characters (interviews and meetings of the teachers), with the objective to establish a dialogue, which could help us to improve and to develop the right educational practice. The teachers' opinion about the treatment of diversity and those elements, which made it difficult to attend the students and to offer an adequate educational response for students with special educational needs, guided us through the experience, which we present in the following.
The relationship between bathymetry and gravity in the Atlantic Ocean

The free air gravity anomaly and depth are sampled at 2-km intervals along two long, reasonably straight ship tracks across the Atlantic Ocean. The resulting series are then processed as if they were time series, and filters are obtained to predict the gravity observations from the bathymetry. More than half the energy in the gravity field can be predicted by this means, and that which cannot emphasizes unusual structures beneath the sea floor. More information can be obtained by comparing the gravity and the bathymetry after both series have been Fourier-transformed. Isostatic compensation begins when the wavelength exceeds about 100 km and increases with increasing wavelength. The results are compared with predictions from various simple models and agree best with a model in which the topography results from variations of crustal thickness and the plate thickness is little greater than 10 km when the compensation occurs. These observations can be understood if the topography results from large-scale intrusions into the lower crust within tens of kilometers of the spreading center. Though such a model for a slowly spreading ridge differs from most of those which have been previously put forward and must be regarded with skepticism until it is supported by evidence from other sources, it appears to be compatible with the limited information now available.
Post-impact Soil Assessments of Crude Oil Spill Site in Kpean Community in Khana LGA (Ogoni) of Rivers State, Nigeria .

A post-impact assessment of soil physico-chemical parameters of crude oil polluted site at Yorla oil field in Kpean community, Khana LGA. (Ogoni) of Rivers State was carried out. Soil samples were randomly collected at two soil depths (0 -15 cm and15 -30 cm) at both the impacted and un-impacted (control) sites. Results showed that crude oil impact increased the total hydrocarbon content (THC) (1276 ±115.6 – 1935 ±119.1 mg/kg) and pH (5.02 ±0.12 – 5.04 ±0.27) of the soil as against 167 ± 22.9 – 170 ± 52.1 mg/kg of the un-impacted site. Soil nitrate, phosphate, total organic carbon (TOC) and total organic matter (TOM) were drastically reduced in the impacted site with values of 36.77 ±7.6 mg/kg, 11.09 ± 2.7 – 14.44 ±1.2mg/kg, 1.96 ± 0.1 – 2.07 ± 0.1 % and 3.33 ± 0.11 - 3.52 ± 0.12 % compared with the un-impacted site of 44.12 ± 0.0 mg/kg, 13.75 ± 2.8 - 15.13 ± 1.4 mg/kg, 2.03 ± 0.2 – 2.22 ± 0.2% and 3.45 ± 0.21 - 3.77 ± 0.16 % correspondingly. There was no significant difference in soil pH (p = 0.05) in both the impacted and un-impacted sites. Therefore crude oil impact alters soil physico-chemical parameters and could be detrimental to the soil ecosystem.
Coastal Chalk Cliff Instability

Most of the rocky coastlines around the world are subject to active erosion processes. Because of the growing hazard to local communities from coastal cliff retreat, it is necessary to investigate where, when and how cliffs collapse. The results of these studies are vital for the planners and local authorities responsible for safety and access to cliffs and beaches. This volume focuses on the coastal chalk cliffs of the English Channel, where a multidisciplinary approach has been used to understand active coastal cliff recession. The book is organized around three main themes: the geological factors controlling cliff instability, the marine parameters influencing coastal erosion and the use of some new tools for hazard assessments. This volume will be of use to academics and professionals working on rocky shores, with an interest in sedimentary geology, stratigraphy, tectonics, geomorphology, engineering geology, coastal engineering and GIS.