Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision Making Under Uncertainty: Theory and Application

Many important problems involve decision making under uncertainty -- that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Training, warning, and media richness effects on computer-mediated deception and its detection

Although deception research in the communication field has a long history, it is a relatively new topic of research in management information systems. Deception detection research has expanded to include lies transmitted via computer-mediated communication. Recent studies have only begun to look at the influence of media richness, training, and warning on deception detection accuracy. Studies on the effect of training on deception cue recognition with cross-media comparison are scarce. In addition, few studies have been conducted on the effects of training with warning on deception detection. This study examines the effects of media richness, training, warning, and the combination of training and warning on deception detection accuracy. To test the hypotheses, a laboratory experiment, in which deceivers were interviewed based upon deceptive information in their enhanced resumes, was conducted. Results of the study indicate that training in deceptive cue recognition improves deception detection success.
Current patterns and future perspectives of best management practices research: A bibliometric analysis

Best management practices (BMPs), as pollution control systems to improve the water environment, were proposed by the Federal Water Pollution Control Act in 1972 (Ice et al. 2010). Best management practices were initially designed for the purpose of controlling soil erosion (Logan 1993). As nonpoint source (NPS) pollution has caused major water quality degradation and threatened the safety of water resources worldwide, BMPs have been recommended as an effective tool used widely to reduce NPS pollution (D'Arcy and Frost 2001; Giri et al. 2012; Ice 2004). Countries, including the United States and the United Kingdom, first initiated BMPs and have had successful experience in agricultural NPS pollution control since the 1970s (Krivak 1978; Mueller et al. 1981). Over the span of a few decades, the application of BMPs has accelerated, and new practices (e.g., stormwater management, watershed management, low impact development, and critical source areas [CSAs]) have been continuously put forward (Martin-Mikle et al. 2015; Niraula et al. 2013; Sage et al. 2015; Zhang et al. 2015). In recent years, several in-depth studies of BMPs have been carried out, such as the Conservation Effect Assessment Project in the United States (Simon and Klimetz 2008), the Watershed Evaluation of Beneficial Management…
World - Fecal sludge management : diagnostics and guidelines for service delivery in poor urban areas - summary report

Urban sanitation remains a significant challenge for most low- and middle-income countries. While sanitation coverage has been increasing across both the 48 least developed countries (LDCs) and developing regions as a whole, progress has been relatively slow. In many cities, even where improved on-site facilities are used to contain excreta, the level of quality and access to services for the emptying, conveyance, treatment, and disposal of the resulting fecal sludge is usually limited. These services are collectively called fecal sludge management (FSM) services. FSM services are the focus of this study, within the broader context of urban sanitation and integrated urban water management (IUWM). This document provides a summary of the diagnostic tools developed for assessing FSM services and is based on field work carried out in the five cities of Balikpapan in Indonesia, Dhaka in Bangladesh, Hawassa in Ethiopia, Lima in Peru, and Santa Cruz in Bolivia. It summarizes the tools themselves, lessons learnt about their use, and general policy recommendations.
Color Image Enhancement Using a Retinex Algor ithm with Bilater al Filter ing for Images with Poor Illumination

Color enhancement basically deals with color manipulation in digital images. Recently, the technique has become widely used as a result of the increasing use of digital cameras. Retinex-based color-enhancement algorithms are a popular technique. In this paper, retinex with bilateral filtering is proposed to improve the quality of poorly illuminated images. Generally, it consists of three main steps: first, a retinex-based algorithm with color restoration; second, transformation mapping using histogram matching; and finally, smoothing the image using a bilateral filter. The experimental results demonstrate that the proposed method can successfully enhance image contrast while avoiding the halo effect and maintaining the color distribution in the image.
Mercury chloride-induced oxidative stress in human erythrocytes and the effect of vitamins C and E in vitro

Mercury can exist in the environment as metal, as monovalent and divalent salts and as organomercurials, one of the most important of which is mercuric chloride (HgCl2). It has been shown to induce oxidative stress in erythrocytes through the generation of free radicals and alteration of the cellular antioxidant defense system. The effect of simultaneous pretreatment with vitamins C and E on the toxicity of HgCl2 in human erythrocytes was evaluated. We examined the effect of several different doses of HgCl2 (1.052, 5.262, 10.524 M), or HgCl2 in combination with vitamin C (VC; 10 M) and vitamin E (VE; 30 M), on the levels of malondialdehyde (MDA) and superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) activities in human erythrocytes in vitro. Erythrocytes were incubated under various treatment conditions (HgCl2 alone, vitamins alone, or HgCl2 plus vitamin) at 37°C for 60 min and the levels of MDA and SOD, CAT and GPx activities, were determined. Treatment with HgCl2 alone increased the levels of MDA and decreased SOD, CAT and GPx activities in erythrocytes (P < 0.05). VC and VE-pretreated erythrocytes showed a significant protection aganist the cytotoxic effects induced by HgCl2 on the studied parameters. There were no statistical differences among VC+VE-treated erythrocytes, as compared to non-treated control cells. These results indicated that the presence of vitamins at concentrations that are similar to the levels found in plasma could be able to ameliorate HgCl2-induced oxidative stress by decreasing lipid peroxidation and altering antioxidant defense system in erythrocytes.
Cinceles en la Edad del Bronce italiana: aspectos tecnológicos y tipológicos Chisels in the italian Bronze Age: technological and typological aspects

Bronze chisels are tools used “a percussion posee”; this means they need a minimum length and some functional parts (tang, body, blade); they could have a handle of perishable material and they were used with a hammer to work wood, bronze and other materials. Chisels can be classified following their functional parts; the first element is the shape (rod or socketed chisel); the second one is body section; the third one is tang section. Chronology and distribution of every type were identified to obtain a general view of this class of tools during the Italian Bronze Age.
Treatment of severe cutaneous small-vessel vasculitis with mycophenolate mofetil.

A 46-year-old man presented with a 5-week history of painful purpuric ulcerative lesions on his legs (Figure1). A skin biopsy specimen taken by his referring physician exhibited perivascular infiltration of polymorphonuclear leukocytes, fibrinoid deposition on the vessel walls, and extravasation of erythrocytes that was diagnostic of small-vessel vasculitis (leukocytoclastic vasculitis). No involvement of the deep dermis or subcutaneous tissue was noted in the pathology report. A prior 10-day course of prednisone had proven ineffective. His medical history was positive for intermittent hematuria that predated his vasculitis by several years. The hematuria was microscopic and had been worked up by a urologist and determined to be without systemic involvement. There were no other positive findings on review of systems and no evidence of systemic vasculitis. Medications at the onset of his vasculitis included sertraline, ibuprofen, and zolpidem, none of which was new. Laboratory evaluation revealed no abnormalities in his complete blood cell count, comprehensive metabolic panel, hepatitis profile, erythrocyte sedimentation rate, or serum protein electrophoresis. Serologic findings were negative for cryoglobulins; ANCA; and anti-Smith, antiScl-70, anti-Ro (SS-A), anti-La (SS-B), antihistone, anti– Jo-1, and anticentromeric antibodies. Urinalysis findings were positive for 2 blood, 2 protein, and 11 to 30 red blood cells per high-powered field, consistent with the microscopic hematuria in the patient’s history. Findings of direct immunofluorescence studies of a biopsy specimen taken from the presumed newest lesion on the left thigh were scantly positive for IgM in blood vessels and negative for IgA and IgG; C3 findings were moderately positive in a few vessels and in a discontinuous granular pattern along the basement membrane. Treatment was initiated with colchicine, 0.6 mg twice daily, along with dapsone, 150 mg/d. This regimen blocked the development of new lesions, but there was no change in the ulcerations with these therapies. During the course of his treatment, the patient developed abdominal pain, which he attributed to dapsone, and therapy was discontinued.
an exploratory analysis in the São Francisco River Basin, Brazil

This paper uses recently released municipio-level data on rural poverty in Brazil to identify and analyze spatial patterns of rural poverty in the Sao Francisco River Basin (SFRB) . Moran’s I statistics are generated and used to test for spatial autocorrelation, and to prepare cluster maps that locate rural poverty “hot spots” and “cold spots”. Our results indicate that poverty reduction policies in the SFRB should take into account the spatial distribution of poverty. Not only is poverty in the SFRB clustered spatially, but the bulk of the basin’s poor resides in municipios that comprise the poverty ‘hot spots’ we identified. These clusters did not correspond to state-level boundaries (the political delineations often used to measure poverty and to manage poverty reduction programs), so scope may exist for geographically refocusing poverty reduction efforts to make them more efficient. Maybe more importantly the results set the stage for the use of spatial econometrics for a future multivariate analysis of rural poverty in the basin.
P- and S-wave velocity models of shallow dry sand formations from surface wave multimodal inversion

ABSTRACTSurficial formations composed of loose, dry granular materials constitute a challenging target for seismic characterization. They exhibit a peculiar seismic behavior, characterized by a nonlinear seismic velocity gradient with depth that follows a power-law relationship, which is a function of the effective stress. The P- and S-wave velocity profiles are then characterized by a power-law trend, and they can be defined by two power-law exponents αP,S and two power-law coefficients γP,S. In case of depth-independent Poisson’s ratio, the P-wave velocity profile can be defined using the VS power-law parameters and Poisson’s ratio. Because body wave investigation techniques (e.g., P-wave tomography) may perform ineffectively on such materials because of high attenuation, we addressed the potential of surface-wave method for a reliable seismic characterization of shallow formations of dry, uncompacted granular materials. We took into account the dependence of seismic wave velocity on effective pressure .
A Remote Sensing Analysis of the flood in Poyang Lake Area

Poyang Lake is characterized by in-out and is a seasonable and shadow lake of fresh water. The lake gives a unique prospect that it is like a lake during a rise of water, while like a river during a fall of water; and shows mass during flood, while showing linear during drought.When the flood comes, it does damage to neighbouring area and leads to enormous loss. The article takes an example of the huge flood on the base of adopting the pictures of TM remote sensing satellite. Then, I refer to some proposal on the cause of flood and defending flood.
Protein secondary structure prediction with semi Markov HMMs

Secondary structure prediction has been an essential task in determining the structure and function of the proteins. Prediction accuracy is improving every year towards the 88% estimated theoretical limit. There are two approaches for the secondary structure prediction. The first one, ab initio (single sequence) prediction does not use any homology information. The evolutionary information, if available, is used by the second approach to improve the prediction accuracy by a few percentages. In this paper, we address the problem of single sequence prediction by developing a semi Markov HMM, similar to the one proposed by Schmidler et al. We introduce a better dependency model by considering the statistically significant amino acid correlation patterns at segment borders. Also, we propose an internal dependency model considering right to left dependencies without modifying the left to right HMM topology. In addition, we propose an iterative training method to better estimate the HMM parameters. Putting all these together, we obtained 1.5% improvement in three-state-per-residue accuracy.
UvA-DARE ( Digital Academic Repository ) Learning to recognize horn and whistle sounds for humanoid robots

The efficiency and accuracy of several state-of-the-art algorithms for real-time sound classification on a NAO robot are evaluated, to determine how accurate they are at distinguishing horn and whistle sounds in both optimal conditions, and a noisy environment. Each approach uses a distinct combination of an audio analysis method and a machine learning algorithm, to recognize audio signals captured by NAO’s four microphones. A short summary of three audio analysis preprocessing methods is provided, as well as a description four machine learning techniques (Logistic Regression, Stochastic Gradient Descent, Support Vector Machine, and AdaBoost-SAMME) which could be used to train classifiers which would distinguish whistle and horn signals from background noise. Experimental results show that for each of the acquired data sets, there are multiple high-accuracy solutions available. Actually, the accuracy and precision results were all so high, that a more challenging dataset is needed to determination which method is optimal for this application.
UvA-DARE (Digital Academic Repository) Learnings from a Retail Recommendation System on Billions of Interactions at bol.com

—Recommender systems are ubiquitous in the modern internet, where they help users ﬁnd items they might like. We discuss the design of a large-scale recommender system handling billions of interactions on a European e-commerce platform. We present two studies on enhancing the predictive performance of this system with both algorithmic and systems-related approaches. First, we evaluate neural network-based approaches on proprietary data from our e-commerce platform, and conﬁrm recent results outlining that the beneﬁts of these methods with respect to predictive performance are limited, while they exhibit severe scalability bottlenecks. Next, we investigate the impact of a reduction of the response latency of our serving system, and conduct an A/B test on the live platform with more than 19 million user sessions, which conﬁrms that the latency reduction of the recommender system correlates with a signiﬁcant increase in business-relevant metrics. We discuss the implications of our ﬁndings with respect to real world recommendation systems and future research on scalable session-based recommendation.
Bulletin of the American Meteorological Society Adjustments in the forcing-feedback framework for understanding climate change

9 The traditional forcing-feedback framework has provided an indispensable basis for dis10 cussing global climate changes. However, as analysis of model behavior has become more 11 detailed, shortcomings and ambiguities in the framework have become more evident and 12 physical effects unaccounted for by the traditional framework have become interesting. In 13 particular, the new concept of adjustments, which are responses to forcings that are not 14 mediated by the global mean temperature, has emerged. This concept, related to the older 15 ones of climate efficacy and stratospheric adjustment, is a more physical way of capturing 16 unique responses to specific forcings. We present a pedagogical review of the adjustment 17 concept, why it is important, and how it can be used. The concept is particularly useful for 18 aerosols, where it helps to organize what has become a complex array of forcing mechanisms. 19 It also helps clarify issues around cloud and hydrological response, transient vs. equilibrium 20 climate change, and geoengineering. 21 Wales, Sydney, Australia. E-mail: S.Sherwood@unsw.edu. au 1 More intensive analyses of climate simulations are revealing a need 22 to revise definitions of forcing and feedback, and to recognize the new 23 concept of rapid adjustments 24
The Fronts and Atlantic Storm-Track Experiment ( FASTEX )

by Alain Joly, coordinator, Météo-France, Groupe de recherches sur l’Atmosphère Météorologique, France, Yvon Lemaître, Centre d’étude de l’Environnement Terrestre et Planétaire, France, Sidney A. Clough, Joint Centre for Mesoscale Meteorology, United Kingdom, Kieran Commins and Peter Lynch, Met Eireann, Ireland, Flosi H. Sigurðsson, Veðurstofa Íslands, Iceland, and Jean-Pierre Cammas, Laboratoire d’Aérologie, France,
APPLICATION OF CASA MODEL TO THE ESTIMATION OF CHINESE TERRESTRIAL NET PRIMARY PRODUCTIVITY

The net primary production (NPP) of Chinese terrestrial vegetation in 1997 was estimated based on the CASA model. The geographic distribution of NPP was explored using GIS and remote sensing imagery (NOAA/AVHRR),together with spatial data on vegetation, climate, soil type and solar radiation. The model estimates China's terrestrial NPP in 1997 as 195 PgC, or about 40% of the worlds terrestrial total. NPP decreased from southeast China toward the northwest. Southern Hainan Island, Southwestern Yunnan and Southeastern Tibet showed large NPP values, with the value exceding 900 gC·m -2·a -1, whereas the Takelamagan desert located in western China had very small values-less than 10 gC·m -2·a -1.
UvA-DARE (Digital Academic Repository) Super universality of the quantum Hall effect and the "large N picture" of the ϑ angle

It is shown that the “massless chiral edge excitations” are an integral and universal aspect of the low energy dynamics of the ϑ vacuum that has historically gone unnoticed. Within the SU (M + N)/S(U(M) × U(N)) non-linear sigma model we introduce an effective theory of “edge excitations” that fundamentally explains the quantum Hall effect. In sharp contrast to the common beliefs in the ﬁeld our results indicate that this macroscopic quantization phenomenon is, in fact, a super universal strong coupling feature of the ϑ angle with the replica limit M = N = 0 only playing a role of secondary importance. To demonstrate super universality we revisit the large N expansion of the CP N − 1 model. We obtain, for the ﬁrst time, explicit scaling results for the quantum Hall effect including quantum criticality of the quantum Hall plateau transition. Consequently a scaling diagram is obtained describing the cross-over between the weak coupling “instanton phase” and the strong coupling “quantum Hall phase” of the large N theory. Our results are in accordance with the “instanton picture” of the ϑ angle but fundamentally invalidate all the ideas, expectations and conjectures that are based on the historical “large N picture. ”
As Time Goes By : Constraint Handling Rules A Survey of CHR Research from 1998 to 2007

Constraint Handling Rules (CHR) is a high-level programming language based on multiheaded multiset rewrite rules. Originally designed for writing user-defined constraint solvers, it is now recognized as an elegant general purpose language. CHR-related research has surged during the decade following the previous survey by Frühwirth (1998). Covering more than 180 publications, this new survey provides an overview of recent results in a wide range of research areas, from semantics and analysis to systems, extensions and applications.
Computational Thinking : Changes to the Human Connectome Associated with Learning to Program Completed Research Paper

Computational thinking (Guzdial 2008; Wing 2006; Wing 2008) means solving problems using a logical, often mathematical, foundation. One important type of computational thinking involves being able to observe a problem in the world and then formulate a plan of action that can be carried out by a computer. Computational thinking is what computing professionals (MIS personnel, computer scientists) do when they analyze and design systems.