Miracle-dz/UniFAR-FTUs huggingface dataset:
The Management of Sediment Transported by Glacial Melt-Water Streams and its Significance for the Estimation of Sediment Yield

This paper describes the calibration of sediment traps in melt-water intake structures of the Grande Dixence hydro-electricity scheme for the purpose of generating medium-term estimates of suspended sediment and bedload transport by pro-glacial streams. The frequency of emptying/purging of sediment from traps in 17 glacier basins in the Val d’Hérens is combined with their design sediment volume to provide first approximations of the mean annual volume of sediment purged. This is followed by more detailed consideration of 11 years of records from three of the basins, to investigate mean seasonal and inter-annual patterns of purging. The difficulties of relating sediment purging to sediment transport are considered. A sediment calibration strategy based on 2 years of turbidity records, hand sampling of suspended sediment concentration, and monitoring of the accumulation of sediment in sediment traps is proposed for one of the glacier basins, and is checked using hourly and 4 h suspended sediment observations from two further ablation seasons. The calibration is applied to 10 years of discharge and purge records to establish estimates of mean seasonal and inter-annual patterns of suspended sediment and bed-load transport.
Climate Change and Buildings in Nigeria: A Search for Mitigation and Adaptation framework for Residential Design Guide.

A number of studies have acknowledged that climate change and buildings interrelate and suggested that sustainable design and construction are key factors to reducing the greenhouse gas (ghg) emissions from buildings. These studies also argued that climate change effects can be country specific, hence the need for localised interventions. Other researchers have also carried out studies on sector based strategies involving the built environment professionals and their roles. Yet the roles of the built environment professionals in developing economies and especially in the Sub-Saharan Africa received little attention. A review of these studies is undertaken to derive themes for the qualitative survey conducted on some built environment professionals (architects, builders, engineers and planners) in Nigeria. This research study investigates; the knowledge and awareness level of these professionals, their current practices and how to improve these practices. Findings from the interview survey showed that there is generally, a low level of sustainable information, knowledge and awareness amongst these interviewees. The study further proffers recommendations for the development and the overall sustainability of the built environment in Nigeria.
Spectral Image Fusion From Compressive Measurements Using Spectral Unmixing and a Sparse Representation of Abundance Maps

In the past years, one common way of enhancing the spatial resolution of a hyperspectral (HS) image has been to fuse it with complementary information coming from multispectral (MS) or panchromatic images. This paper proposes a new method for reconstructing a high-spatial, high-spectral image from measurements acquired after compressed sensing by multiple sensors of different spectral ranges and spatial resolutions, with specific attention to HS and MS compressed images. To solve this problem, we introduce a fusion model based on the linear spectral unmixing model classically used for HS images and investigate an optimization algorithm based on a block coordinate descent strategy. The nonnegative and sum-to-one constraints resulting from the intrinsic physical properties of abundances as well as a total variation penalization are used to regularize this ill-posed inverse problem. Simulation results conducted on realistic compressed HS and MS images show that the proposed algorithm can provide fusion results that are very close to those obtained with uncompressed images, with the advantage of using a significantly reduced number of measurements.
The climate of the Mediterranean Basin and of Eurasia of the last glacial maximum as reconstructed by inverse vegetation modelling and pollen data

Keywords: vegetation model ; Monte-Carlo sampling ; palaeoclimatology ; last glacial maximum ; Europe ; Eurasia ; mediterranean ; climate reconstruction ; pollen ; LGM Note: Article Library - 4058 Article Library Box - Joel Guiot (Q) Reference ECOS-ARTICLE-2008-090 Record created on 2008-02-22, modified on 2016-08-08
Approximate MaxEnt Inverse Optimal Control and its Application for Mental Simulation of Human Interactions

The problem of the inverse optimal control (also known as inverse reinforcement learning) is to recover an agent’s (or expert’s) reward function given a controller or policy (or samples from the agent’s behavior) when the dynamics of the process is known. To describe our approach to IOC, which is based on the Maximum Entropy Inverse Optimal Control of [1], we first define a parametric-reward Markov Decision Process (θ-MDP). θ-MDP is defined as a tuple (X ,A,P, g, θ), where X is a measurable state space (e.g., R), A is a finite set of actions, P : X × A → M(X ) is the transition probability kernel, g : X × A → R is a mapping from state-action pairs to feature vectors of dimension d, and θ ∈ R parametrizes the reward. We consider θ-MDPs with finite horizon of T . For notational convenience, given a sequence z1:T = (z1, . . . , zT ), we denote f(z1:T ) = ∑T t=1 g(zt). In IOC, we assume that P is known (or estimated separately). Consider a set of demonstrated trajectories Dn = {Z 1:T }i=1 with each trajectory Z1:T = (Z1, . . . , ZT ) ∼ ζ with Zt = (Xt, At) and ζ being an unknown distribution over the set of trajectory. Also denote ν ∈ M(X ) as the distribution of X1. We assume that this initial distribution is known. For a policy π, denote Pπ(Z1:T ) as the distribution induced by following policy π. In the discrete state case, Pπ(Z1:T ) = ∏T−1 t=1 P(Xt+1|Xt, At)π(At|Xt) (and similarly for continuous state spaces). Define the causal conditioned probability P {A1:T ||X1:T } = ∏T t=1 P {At|Xt} = ∏T t=1 πt(At|Xt), which reflects the fact that future states do not influence earlier actions (compare with conditional probability P {A1:T |X1:T }). We define the causal entropy Hπ as Hπ = EPπ(Z1:T ) [− logP {A1:T ||X1:T }]. The primal optimization problem in Maximum Entropy Inverse Optimal Control estimator [1]
Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification

Cross-domain sentiment classification aims to leverage useful information in a source domain to help do sentiment classification in a target domain that has no or little supervised information. Existing cross-domain sentiment classification methods cannot automatically capture non-pivots, i.e., the domain-specific sentiment words, and pivots, i.e., the domain-shared sentiment words, simultaneously. In order to solve this problem, we propose a Hierarchical Attention Transfer Network (HATN) for cross-domain sentiment classification. The proposed HATN provides a hierarchical attention transfer mechanism which can transfer attentions for emotions across domains by automatically capturing pivots and non-pivots. Besides, the hierarchy of the attention mechanism mirrors the hierarchical structure of documents, which can help locate the pivots and non-pivots better. The proposed HATN consists of two hierarchical attention networks, with one named P-net aiming to find the pivots and the other named NP-net aligning the non-pivots by using the pivots as a bridge. Specifically, P-net firstly conducts individual attention learning to provide positive and negative pivots for NP-net. Then, P-net and NP-net conduct joint attention learning such that the HATN can simultaneously capture pivots and non-pivots and realize transferring attentions for emotions across domains. Experiments on the Amazon review dataset demonstrate the effectiveness of HATN.
Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Nonoverlapping Cameras

This paper proposes a novel unsupervised algorithm learning discriminative features in the context of matching road vehicles between two nonoverlapping cameras. The matching problem is formulated as a same-different classification problem; which aims to compute the probability of vehicle images from two distinct cameras being from the same vehicle or different vehicle(s). We employ a novel measurement vector that consists of three independent edge-based measures and their associated robust measures computed from a pair of aligned vehicle edge maps. The weight of each measure is determined by an unsupervised learning algorithm that optimally separates the same-different classes in the combined measurement space. This is achieved with a weak classification algorithm that automatically collects representative samples from same-different classes, followed by a more discriminative classifier based on Fisher's linear discriminants and Gibbs sampling. The robustness of the match measures and the use of unsupervised discriminant analysis in the classification ensures that the proposed method performs consistently in the presence of missing/false features, temporally and spatially changing illumination conditions and systematic misalignment caused by different camera configurations. Extensive experiments based on real data of more than 200 vehicles at different times of the day demonstrate promising results.
An attempt at a new analysis of the mortality caused by smallpox and of the advantages of inoculation to prevent it

‘I simply wish that, in a matter which so closelyconcerns the wellbeing of the human race, no deci-sion shall be made without all the knowledge whicha little analysis and calculation can provide’Daniel Bernoulli 1760.INTRODUCTIONShould the general population be vaccinatedagainst smallpox (Variola Major)? Would the bene-ﬁts of mass vaccination outweigh the risks? Howmany deaths would occur as the result of a massvaccination campaign against smallpox? Canmathematical models of smallpox vaccination beused to determine health policy? Although small-pox was declared eradicated by the World HealthOrganization in 1979, these questions have all beenrecently debated based upon the premise thatsmallpox may be used as a weapon of bioterror-ism. Hence, a series of analyses has recently beenpublished that use mathematical models to try todetermine the most effective public healthresponse in the event of such an attack [1–4]. How-ever, these same controversial public health ques-tions were debated in the 18th century whensmallpox was endemic and Reviews in Medical Vir-ology has published two classic papers describingthe natural history of smallpox in 1902 and 1913to help inform these discussions [5,6]. We nowpublish an even earlier paper.In 1760 Daniel Bernoulli (1700–1782), one of thegreatest scientists of the 18th century, wrote amathematical analysis of the problem in order totry to inﬂuence public health policy by encoura-ging the universal inoculation against smallpox;his analysis was ﬁrst presented at the Royal Acad-emy of Sciences in Paris in 1760 and later pub-lished in 1766 [7]. Here, we republish anddiscuss both the historical and the current signiﬁ-cance of Bernoulli’s classic paper. A detailed dis-cussion of the mathematics of Bernoulli’s analysishas previously been presented by Dietz andHeesterbeck [8]. According to Creighton [9] smallpox ﬁrstappeared in England in the 16th century. Smallpoxwas known in Western Europe in medieval times,but a particularly virulent strain emerged in theearly 17th century and gradually the case fatalityrate increased [10]. By the 18th century smallpoxwas endemic. Bernoulli calculated that approxi-mately three quarters of all living people (in the18th century) had been infected with smallpox[7]. One-tenth of all mortality at that time wasdue to smallpox, although there was considerableannual variation in smallpox mortality due to epi-demic outbreaks overlaying the endemic smallpoxmortality rate. For example, in London during theperiod 1761–1796 the annual number of deathsdue to smallpox varied from 3000 to 15000. Wheresmallpox was endemic it was almost wholly a dis-ease of childhood, with a case-fatality rate of 20%–30%; the mean age of death due to smallpox hasbeen estimated as 2.6 years [10] or 4.5 years [11].
Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning

Popular off-policy deep reinforcement learning algorithms compensate for over-estimation bias during temporal-difference learning by utilizing pessimistic estimates of the expected target returns. In this work, we propose a novel learnable penalty to enact such pessimism, based on a new way to quantify the critic’s epistemic uncertainty. Furthermore, we propose to learn the penalty alongside the critic with dual TD-learning , a strategy to estimate and minimize the bias magnitude in the target returns. Our method enables us to accurately counteract overestimation bias throughout training without incurring the downsides of overly pessimistic targets. Empirically, by integrating our method and other orthogonal improvements with popular off-policy algorithms, we achieve state-of-the-art re-sults in continuous control tasks from both proprioceptive and pixel observations.
Lettuce response to electrical conductivity with surface irrigation and sub-irrigation systems

2 Abstract Salinity suppresses plant growth and reduce agricultural productivity due to a water deficit, ion toxicity, causing nutrient skewness. A sub-irrigation system on principle, is based on capillary rise of water, up to the root zone, decreasing nutrient leaching compared with traditional watering systems. In void areas of northern Mexico, there are often high levels of calcium (Ca), magnesium and sulphate in irrigation water, directly affecting the electrical conductivity (EC). This paper proposed to evaluate the effect of EC on the growth of lettuce plants using two types of irrigation systems: surface and sub-irrigation. The diameter of the plants was bigger in plants with surface irrigation system compared to those with sub-irrigation; however, plants sub-irrigated with solution 3.3 dS m -1 showed a higher fresh weight than those with surface irrigation, so this system is a good option to meliorate the effect of salinity. The rate of photosynthesis, transpiration and leaf conductance were not altered by the irrigation system at all, but transpiration and conductance were higher in sub-irrigated plants. A higher EC of the nutrient solution increased the bottom EC of the substrate, and the middle and top layer, and the surface irrigation system was higher compared to that presented by
Formally Verified Solution Methods for Infinite-Horizon Markov Decision Processes

We formally verify executable algorithms for solving Markov decision processes (MDPs) in the interactive theorem prover Isabelle/HOL. We build on existing formalizations of probability theory to analyze the expected total reward criterion on inﬁnite-horizon problems. Our developments formalize the Bellman equation and give conditions under which optimal policies exist. Based on this analysis, we verify dynamic programming algorithms to solve tabular MDPs. We evaluate the formally veriﬁed implementations experimentally on standard problems and show they are practical. Furthermore, we show that, combined with eﬃcient unveriﬁed implementations, our system can compete with and even out-perform state-of-the-art systems.
WRF high resolution simulation of Iberian mean and extreme precipitation climate

In this study precipitation from a high resolution WRF climate simulation is presented and evaluated against daily gridded observations in the Iberian Peninsula. The simulation corresponds to a dynamical downscaling of ERA‐Interim, in the period 1989–2009, performed with two nested grids, at 27 and 9 km horizontal resolution. The higher resolution simulation indicates a significantly improved representation of Iberian precipitation fields, at all timescales, with emphasis on the representation of variability and of extreme weather statistics. Results compare well with recent studies with other models and/or for other regions, further supporting the use of WRF as a regional climate model.
EVALUATION OF TRANSIT SIGNAL PRIORITY STRATEGIES FOR SMALL-MEDIUM CITIES

Transit Signal Priority (TSP) has mainly been applied in larger metropolitan areas where demand for transit service is moderate to high. This study evaluates theoretical TSP applications to a small- medium size urban area (where demand for transit service is low) as a means of attracting more transit customers and providing better service to existing routes. Small-medium size cities often have a transit service with headways greater than 30 minutes. During peak periods, traffic congestion causes missed connections at transfer points and can increase the transit rider's total trip time by as much as one hour. This study evaluated several scenarios involving the early green and extended green strategies, 30 minute and 15 minute bus headways, and midday and afternoon peak periods. The microscopic traffic simulation model, VISSIM, was used to accurately model a downtown region of Fargo, ND with several bus routes. Results indicated potential bus travel time savings as high as 14%, with a decrease in bus stopped delay of 38%. Impacts to the local system were investigated as well, side-street person-delay increased as much as 14% during the afternoon peak
Identifying the best locations to provide safe highway crossing opportunities for wildlife

Providing mid- and large-sized mammals with safe opportunities to cross roadways can reduce the impacts of highways on wildlife. To maximize effectiveness, this type of mitigation must be placed in locations where animals naturally approach and cross the highway. Results of a study funded by the Colorado Department of Transportation indicate that mid- and large-sized mammals focus crossing activity at specific locations that are correlated to features of the surrounding habitat and the roadway itself. Therefore, both the design of a highway and its placement in the landscape should be considered when creating mitigation projects to help wildlife safely cross a highway. It is important to note that no single set of variables identifies all preferred crossing locations. Because every landscape and every highway is unique, identifying the best location for each mitigation project must be approached individually. However, the study results suggest a set of guidelines, comprising the following: (1) use habitat suitability as the primary indicator of crossing activity; (2) consider how landscape structure interacts with habitat suitability to either increase or decrease the level of use an area of suitable habitat receives by a particular species; (3) consider how the design of the existing highway interacts with habitat suitability and landscape structure to influence crossing behavior; (4) synthesize this information by mapping the landscape and roadway features/conditions likely to be associated with crossing or that are attractive/repellant to the species present. Use these maps to identify the most likely crossing locations. Finally, because the preferred habitat and behavior of a given species can vary across its range, it is important to employ professionals familiar with the landscapes and species of concern on the analysis team.
EURASIAN JOURNAL OF ECONOMICS AND FINANCE

This paper discusses why citizens perceive a tax system as fair or unfair. We review the literature about tax fairness and tax preferences. From this literature, we extract the most common explanations for tax fairness perception. Most important are the topics of vertical and horizontal fairness, complexity and the discussion between the benefit and the ability-to-pay-principle. Within these topics, we deal also with very current topics like the controversy between capital and labor taxation or the affluence tax. To answer the questions how the tax fairness is perceived in Germany and what criteria are most useful to explain these attitudes, we conduct two surveys. One is a convenience sample, by the help of SoSciPanel a German online respondent pool, and the other is a student survey. Also, the role of self-interest in these aspects is addressed. Especially we want to shed light on the role of income expectations by the difference between the full population survey and the student survey, since the latter group is more homogenous in actual income.
EURASIAN JOURNAL OF ECONOMICS AND FINANCE

There has been increasing attention all over the world on corporate governance issues after experiencing some financial crises and corporation scandals. It is assumed that the investors search for emerging economies to diversify their investment portfolios and maximize their returns is considering corporate governance applications. Investors are also concerned about governance factors to minimize their risks. In this study, we examine the impact of corporate governance variables on firms‟ financial performance in Turkey. The relationship between ownership structures, board structures and financial performances are tested. Influence of corporate governance variables, board size, share of independent board members, foreign investors, leverage ratio on firms‟ financial performance “return on assets” are utilized on firms traded in Turkey‟s stock exchange BIST 100. This research concludes that corporate governance variables influence firms‟ performances. Shares of independent board members and leverage have negative influences while foreign ownership has a positive influence on firms‟ financial performances.
Golden Age

This study aims to determine the discipline of children at KB Puri Siwi Tamansari Academic Year 2016/2017 and find out the improvement of children's discipline through playing traffic simulations at KB Puri Siwi Tamansari Academic Year 2016/2017. This research method uses a type of classroom action research. This research was conducted in two stages, namely cycle I and cycle II. The subjects of this study were Puri Siwi Play Group students aged 3-4 years Tamansari Tlogowungu Pati as many as 16 students. The results of this study indicate that traffic simulations to improve child discipline are carried out with two cycles, the first cycle is carried out by simulating traffic signs with micro equipment, sikus II is carried out by simulating traffic signs with macro equipment. The results of data analysis and observations through traffic simulations showed an increase from the pre-cycle of 30% of children who completed their discipline, rising in the first cycle to 56.7%. That is, an increase of 24%. And in the second cycle increased to 81% and an increase of 25%. The results achieved in the second cycle had met the intended completeness target, namely 80% of all children scored with a complete category of 85. This increase in the average value proved the success of traffic simulations can improve children's discipline.