Miracle-dz/UniFAR-FTUs huggingface dataset:
Large landslides in London Clay at Herne Bay, Kent

Summary Stability analyses of three large coastal landslides in the London Clay cliffs east of Herne Bay in Kent are presented together with summarised accounts of the investigations which made them possible. The results of these analyses are then compared with the results from other field and laboratory studies of residual strength and slope stability in London Clay.
Thermohaline circulation and interaction between ice shelf cavities and the adjacent open ocean

The circulation system in an ice shelf cavity is driven by buoyancy fluxes due to melting and freezing of ice and horizontal pressure gradients at the interface between the cavity and the open ocean. Hence the inflow and outflow pattern and the hydrography in the open ocean influence the general hydrographic condition in the cavity, which at least provides the potential for melting and freezing processes. Applying a three-dimensional ocean general circulation model to an idealized ice shelf cavity geometry coupled with an open ocean at a topographic ice shelf barrier, we found an important parameter controlling the interaction between these two systems. Idealized studies for different ice shelf and sea bottom topographies and forcing mechanisms for the open ocean show that the ice shelf edge represents a natural barrier for barotropic interaction, because of the sudden decrease in water column thickness. Since the water column thickness and the Coriolis force determine the characteristics for geostrophic flow, separated circulation systems arise for the open ocean and the ice shelf cavity. Only in areas where constant water column thickness and, from the oceanographic point of view, constant f/H contours can be observed across the barrier, an increased barotropic current can surmount the ice edge and ventilate the water mass beneath the ice shelf. This is only the case at lateral sloping sidewalls or at deep depressions, which can be found, for example, in the southern Weddell Sea. In all other cases the circulation in the ice shelf cavity is closed and almost unaffected by the hydrography outside the barrier.
Transmission Capacity of Wireless Networks

Transmission capacity (TC) is a performance metric for wireless networks that measures the spatial intensity of successful transmissions per unit area, subject to a constraint on the permissible outage probability (where outage occurs when the SINR at a receiver is below a threshold). This volume gives a unified treatment of the TC framework that has been developed by the authors and their collaborators over the past decade. The mathematical framework underlying the analysis (reviewed in Ch. 2) is stochastic geometry: Poisson point processes model the locations of interferers, and (stable) shot noise processes represent the aggregate interference seen at a receiver. Ch. 3 presents TC results (exact, asymptotic, and bounds) on a simple model in order to illustrate a key strength of the framework: analytical tractability yields explicit performance dependence upon key model parameters. Ch. 4 presents enhancements to this basic model --- channel fading, variable link distances, and multi-hop. Ch. 5 presents four network design case studies well-suited to TC: i) spectrum management, ii) interference cancellation, iii) signal threshold transmission scheduling, and iv) power control. Ch. 6 studies the TC when nodes have multiple antennas, which provides a contrast vs. classical results that ignore interference.
Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon

Abstract Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8 m3/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m3/s per decade in January for the Upper and Lower basin, respectively. Editor D. Koutsoyiannis; Associate editor Sheng Yue Citation Ramadan, H.H. , Beighley, R.E. , and Ramamurthy, A.S. , 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.
Constrained Monte Carlo method and calculation of the temperature dependence of magnetic anisotropy

We introduce a constrained Monte Carlo method which allows us to traverse the phase space of a classical spin system while fixing the magnetization direction. Subsequently we show the method’s capability to model the temperature dependence of magnetic anisotropy, and for bulk uniaxial and cubic anisotropies we recover the low-temperature Callen-Callen power laws in M. We also calculate the temperature scaling of the two-ion anisotropy in L10 FePt, and recover the experimentally observed M 2.1 scaling. The method is newly applied to evaluate the temperature-dependent effective anisotropy in the presence of the Neel surface anisotropy in thin films with different easy-axis configurations. In systems having different surface and bulk easy axes, we show the capability to model the temperature-induced reorientation transition. The intrinsic surface anisotropy is found to follow a linear temperature behavior in a large range of temperatures.
Δ self-consistent field method to obtain potential energy surfaces of excited molecules on surfaces

We present a modification of the $\ensuremath{\Delta}$ self-consistent field ($\ensuremath{\Delta}\text{SCF}$) method of calculating energies of excited states in order to make it applicable to resonance calculations of molecules adsorbed on metal surfaces, where the molecular orbitals are highly hybridized. The $\ensuremath{\Delta}\text{SCF}$ approximation is a density-functional method closely resembling standard density-functional theory (DFT), the only difference being that in $\ensuremath{\Delta}\text{SCF}$ one or more electrons are placed in higher lying Kohn-Sham orbitals instead of placing all electrons in the lowest possible orbitals as one does when calculating the ground-state energy within standard DFT. We extend the $\ensuremath{\Delta}\text{SCF}$ method by allowing excited electrons to occupy orbitals which are linear combinations of Kohn-Sham orbitals. With this extra freedom it is possible to place charge locally on adsorbed molecules in the calculations, such that resonance energies can be estimated, which is not possible in traditional $\ensuremath{\Delta}\text{SCF}$ because of very delocalized Kohn-Sham orbitals. The method is applied to ${\text{N}}_{2}$, CO, and NO adsorbed on different metallic surfaces and compared to ordinary $\ensuremath{\Delta}\text{SCF}$ without our modification, spatially constrained DFT, and inverse-photoemission spectroscopy measurements. This comparison shows that the modified $\ensuremath{\Delta}\text{SCF}$ method gives results in close agreement with experiment, significantly closer than the comparable methods. For ${\text{N}}_{2}$ adsorbed on ruthenium (0001) we map out a two-dimensional part of the potential energy surfaces in the ground state and the $2\ensuremath{\pi}$ resonance. From this we conclude that an electron hitting the resonance can induce molecular motion, optimally with 1.5 eV transferred to atomic movement. Finally we present some performance test of the $\ensuremath{\Delta}\text{SCF}$ approach on gas-phase ${\text{N}}_{2}$ and CO in order to compare the results to higher accuracy methods. Here we find that excitation energies are approximated with accuracy close to that of time-dependent density-functional theory. Especially we see very good agreement in the minimum shift of the potential energy surfaces in the excited state compared to the ground state.
Hydrological footprints of urban developments in the Lake Simcoe watershed, Canada: a combined paired‐catchment and change detection modelling approach

Urban sprawl and regional climate variability are major stresses on surface water resources in many places. The Lake Simcoe watershed (LSW) Ontario, Canada, is no exception. The LSW is predominantly agricultural but is experiencing rapid population growth because of its proximity to the Greater Toronto area. This has led to extensive land use changes that have impacted its water resources and altered run‐off patterns in some rivers draining to the lake. Here, we use a paired‐catchment approach, hydrological change detection modelling and remote sensing analysis of satellite images to evaluate the impacts of land use change on the hydrology of the LSW (1994 to 2008). Results show that urbanization increased up to 16% in Lovers Creek, the most urban‐impacted catchment. Annual run‐off from Lovers Creek increased from 239 to 442 mm/year in contrast to the reference catchment (Black River at Washago) where run‐off was relatively stable with an annual mean of 474 mm/year. Increased annual run‐off from Lovers Creek was not accompanied by an increase in annual precipitation. Discriminant function analysis suggests that early (1992–1997; pre‐major development) and late (2004–2009; fully urbanized) periods for Lovers Creek separated mainly based on model parameter sets related to run‐off flashiness and evapotranspiration. As a result, parameterization in either period cannot be used interchangeably to produce credible run‐off simulations in Lovers Creek because of greater scatter between the parameters in canonical space. Separation of early and late‐period parameter sets for the reference catchment was based on climate and snowmelt‐related processes. This suggests that regional climatic variability could be influencing hydrologic change in the reference catchment, whereas urbanization amplified the regional natural hydrologic changes in urbanizing catchments of the LSW. Copyright © 2014 John Wiley & Sons, Ltd.
AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting

Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system. With the accurate EV station situation prediction, suitable charging behaviors could be scheduled in advance to relieve range anxiety. Many existing deep learning methods are proposed to address this issue, however, due to the complex road network structure and comprehensive external factors, such as point of interests (POIs) and weather effects, many commonly used algorithms could just extract the historical usage information without considering comprehensive influence of external factors. To enhance the prediction accuracy and interpretability, the Attribute-Augmented Spatial-Temporal Graph Informer (AST-GIN) structure is proposed in this study by combining the Graph Convolutional Network (GCN) layer and the Informer layer to extract both external and internal spatial-temporal dependence of relevant transportation data. And the external factors are modeled as dynamic attributes by the attribute-augmented encoder for training. AST-GIN model is tested on the data collected in Dundee City and experimental results show the effectiveness of our model considering external factors influence over various horizon settings compared with other baselines.
Fast Processing of SPARQL Queries on RDF Quadruples

In this paper, we propose a new approach for fast processing of SPARQL queries on large RDF datasets containing RDF quadruples (or quads). Our approach called RIQ employs a decrease-and-conquer strategy: Rather than indexing the entire RDF dataset, RIQ identifies groups of similar RDF graphs and indexes each group separately. During query processing, RIQ uses a novel filtering index to first identify candidate groups that may contain matches for the query. On these candidates, it executes optimized queries using a conventional SPARQL processor to produce the final results. Our initial performance evaluation results are promising: Using a synthetic and a real dataset, each containing about 1.4 billion quads, we show that RIQ outperforms RDF-3X and Jena TDB on a variety of SPARQL queries.
A Discrete Ion Stochastic Continuum Overdamped Solvent Algorithm for Modeling Electrolytes.

In this paper we develop a methodology for the mesoscale simulation of strong electrolytes. The methodology is an extension of the Fluctuating Immersed Boundary (FIB) approach that treats a solute as discrete Lagrangian particles that interact with Eulerian hydrodynamic and electrostatic fields. In both cases the Immersed Boundary (IB) method of Peskin is used for particle-field coupling. Hydrodynamic interactions are taken to be overdamped, with thermal noise incorporated using the fluctuating Stokes equation, including a "dry diffusion" Brownian motion to account for scales not resolved by the coarse-grained model of the solvent. Long range electrostatic interactions are computed by solving the Poisson equation, with short range corrections included using a novel immersed-boundary variant of the classical Particle-Particle Particle-Mesh (P3M) technique. Also included is a short range repulsive force based on the Weeks-Chandler-Andersen (WCA) potential. The new methodology is validated by comparison to Debye-H{u}ckel theory for ion-ion pair correlation functions, and Debye-H{u}ckel-Onsager theory for conductivity, including the Wein effect for strong electric fields. In each case good agreement is observed, provided that hydrodynamic interactions at the typical ion-ion separation are resolved by the fluid grid.
Guarding ground: a vision for a National Indigenous Cultural Authority

All rights reserved. No part of these materials shall be reproduced, stored or introduced into a retrieval system, or transmitted in any form or by any means (electronic, mechanical, photocopying recording or otherwise) without permission of the Terri Janke and Company Pty Ltd. WARNING The document contains names of deceased Aboriginal and Torres Strait Islander people. Important legal notice This paper provides general advice only in an effort to encourage constructive debate on the topic. It is not intended to be legal advice. If you have a particular legal issue, we recommend that you seek independent legal advice from a suitably qualified legal practitioner.
Information Technology Platforms: Definition and Research Directions

The concept of an information technology (IT) related platform is broad and covers phenomena ranging from the operating system Linux to the Internet. Such platforms are of increasing importance to innovation and value creation across many facets of industry and daily life. There is, however, a lack of common understanding in both research and industry about what is mean by the term platform when related to IT. This lack of consensus is detrimental to research and knowledge development. Thus, the aims of this study are to: (i) provide a sound definition of the IT-platform concept by identifying its distinguishing dimensions; and (ii) identify important current research directions for the IT-platform concept. To achieve these aims a systematic literature review was undertaken with 133 relevant articles taken from major information systems journals, conferences, and business publications. The study contributes by providing a sound base for future research into IT-platforms.
Query Complexity of Sampling and Small Geometric Partitions

In this paper we study the following problem. Discrete partitioning problem (DPP). Let $\mathbb{F}_q$ Pn denote the n-dimensional finite projective space over $\mathbb{F}_q$ . For positive integer k ⩽ n, let {Ai } i = 1 N be a partition of ( $\mathbb{F}_q$ Pn ) k such that: (1) for all i ⩽ N, Ai = ∏ j=1 k Aj i (partition into product sets), (2) for all i ⩽ N, there is a (k − 1)-dimensional subspace Li ⊆ $\mathbb{F}_q$ Pn such that Ai ⊆ (Li ) k . What is the minimum value of N as a function of q, n, k? We will be mainly interested in the case k = n. DPP arises in an approach that we propose for proving lower bounds for the query complexity of generating random points from convex bodies. It is also related to other partitioning problems in combinatorics and complexity theory. We conjecture an asymptotically optimal partition for DPP and show that it is optimal in two cases: when the dimension is low (k = n = 2) and when the factors of the parts are structured, namely factors of a part are close to being a subspace. These structured partitions arise naturally as partitions induced by query algorithms. Our problem does not seem to be directly amenable to previous techniques for partitioning lower bounds such as rank arguments, although rank arguments do lie at the core of our techniques.
Extinction threshold in spatial stochastic logistic model: Space homogeneous case

We consider the extinction regime in the spatial stochastic logistic model in $\mathbb{R}^d$ (a.k.a. Bolker--Pacala--Dieckmann--Law model of spatial populations) using the first-order perturbation beyond the mean-field equation. In space homogeneous case (i.e. when the density is non-spatial and the covariance is translation invariant), we show that the perturbation converges as time tends to infinity; that yields the first-order approximation for the stationary density. Next, we study the critical mortality---the smallest constant death rate which ensures the extinction of the population---as a function of the mean-field scaling parameter $\varepsilon>0$. We find the leading term of the asymptotic expansion (as $\varepsilon\to0$) of the critical mortality which is apparently different for the cases $d\geq3$, $d=2$, and $d=1$.
Anomalously deep mantle transition zone below Central Europe: Evidence of lithospheric instability

The depths of the 410 and 660 km phase transitions provide critical information on the thermal state of the mantle transition zone (MTZ) and, by implication, on the circulation of the upper mantle. We analyze converted seismic waves to produce a high resolution image of these discontinuities beneath the Pannonian Basin of Central Europe. Models to explain the extension of the basin in the Middle Miocene involve subduction roll‐back and gravitational instability of an over‐thickened lithosphere. We find that cold dense material appears to have accumulated in the MTZ, consistent with the idea of supply from several subduction episodes, or upper mantle overturn. Variation in depth of the 660 km discontinuity by as much as 40 km suggests that cold lithospheric mantle is ponding on top of this phase transition. Where the phase transition is deepest, eventual transfer of this material into the lower mantle may be expected to develop.
Gas Sources of Natural Gas Hydrates in the Shenhu Drilling Area, South China Sea: Geochemical Evidence and Geological Analysis

The Shenhu gas hydrate drilling area is located in the central Baiyun sag, Zhu II depression, Pearl River Mouth basin, northern South China Sea. The gas compositions contained in the hydrate‐bearing zones is dominated by methane with content up to 99.89% and 99.91%. The carbon isotope of the methane (δ13C1) are −56.7‰ and −60.9‰, and its hydrogen isotope (δD) are −199‰ and −180‰, respectively, indicating the methane from the microbial reduction of CO2. Based on the data of measured seafloor temperature and geothermal gradient, the gas formed hydrate reservoirs are from depths 24–1699 m below the seafloor, and main gas‐generation zone is present at the depth interval of 416–1165 m. Gas‐bearing zones include the Hanjiang Formation, Yuehai Formation, Wanshan Formation and Quaternary sediments. We infer that the microbial gas migrated laterally or vertically along faults (especially interlayer faults), slump structures, small‐scale diapiric structures, regional sand beds and sedimentary boundaries to the hydrate stability zone, and formed natural gas hydrates in the upper Yuehai Formation and lower Wanshan Formation, probably with contribution of a little thermogenic gas from the deep sedments during this process.
Exponentials of general multivector (MV) in 3D Clifford algebras

Closed form expressions to calculate the exponential of a general multivector (MV) in Clifford geometric algebras (GAs) Cl(p,q) are presented for n=p+q=3. The obtained exponential formulas were applied to find exact GA trigonometric and hyperbolic functions of MV argument. We have verified that the presented exact formulas are in accord with series expansion of MV hyperbolic and trigonometric functions. The exponentials may be applied to solve GA differential equations, in signal and image processing, automatic control and robotics.
A $q$-linear analogue of the plane wave expansion

We obtain a $q$-linear analogue of Gegenbauer's expansion of the plane wave. It is expanded in terms of the little $q$-Gegenbauer polynomials and the \textit{third} Jackson $q$-Bessel function. The result is obtained by using a method based on bilinear biorthogonal expansions.
Towards practical object detection for weed spraying in precision agriculture

Weeds pose a persistent threat to farmers’ yields, but conventional methods for controlling weed populations, like herbicide spraying, pose a risk to the surrounding ecosystems. Precision spraying aims to reduce harms to the surrounding environment by targeting only the weeds rather than spraying the entire field with herbicide. Such an approach requires weeds to first be detected. With the advent of convolutional neural networks, there has been significant research trialing such technologies on datasets of weeds and crops. However, the evaluation of the performance of these approaches has often been limited to the standard machine learning metrics. This paper aims to assess the feasibility of precision spraying via a comprehensive evaluation of weed detection and spraying accuracy using two separate datasets, different image resolutions, and several state-of-the-art object detection algorithms. A simplified model of precision spraying is proposed to compare the performance of different detection algorithms while varying the precision of the spray nozzles. The key performance indicators in precision spraying that this study focuses on are a high weed hit rate and a reduction in herbicide usage. This paper introduces two metrics, namely, weed coverage rate and area sprayed, to capture these aspects of the real-world performance of precision spraying and demonstrates their utility through experimental results. Using these metrics to calculate the spraying performance, it was found that 93% of weeds could be sprayed by spraying just 30% of the area using state-of-the-art vision methods to identify weeds.