Miracle-dz/UniFAR-FTUs huggingface dataset:
The BUGS Book: A Practical Introduction to Bayesian Analysis

Introduction: Probability and Parameters Probability Probability distributions Calculating properties of probability distributions Monte Carlo integration Monte Carlo Simulations Using BUGS Introduction to BUGS DoodleBUGS Using BUGS to simulate from distributions Transformations of random variables Complex calculations using Monte Carlo Multivariate Monte Carlo analysis Predictions with unknown parameters Introduction to Bayesian Inference Bayesian learning Posterior predictive distributions Conjugate Bayesian inference Inference about a discrete parameter Combinations of conjugate analyses Bayesian and classical methods Introduction to Markov Chain Monte Carlo Methods Bayesian computation Initial values Convergence Efficiency and accuracy Beyond MCMC Prior Distributions Different purposes of priors Vague, 'objective' and 'reference' priors Representation of informative priors Mixture of prior distributions Sensitivity analysis Regression Models Linear regression with normal errors Linear regression with non-normal errors Nonlinear regression with normal errors Multivariate responses Generalised linear regression models Inference on functions of parameters Further reading Categorical Data 2 x 2 tables Multinomial models Ordinal regression Further reading Model Checking and Comparison Introduction Deviance Residuals Predictive checks and Bayesian p-values Model assessment by embedding in larger models Model comparison using deviances Bayes factors Model uncertainty Discussion on model comparison Prior-data conflict Issues in Modelling Missing data Prediction Measurement error Cutting feedback New distributions Censored, truncated and grouped observations Constrained parameters Bootstrapping Ranking Hierarchical Models Exchangeability Priors Hierarchical regression models Hierarchical models for variances Redundant parameterisations More general formulations Checking of hierarchical models Comparison of hierarchical models Further resources Specialised Models Time-to-event data Time series models Spatial models Evidence synthesis Differential equation and pharmacokinetic models Finite mixture and latent class models Piecewise parametric models Bayesian nonparametric models Different Implementations of BUGS Introduction BUGS engines and interfaces Expert systems and MCMC methods Classic BUGS WinBUGS OpenBUGS JAGS A Appendix: BUGS Language Syntax Introduction Distributions Deterministic functions Repetition Multivariate quantities Indexing Data transformations Commenting B Appendix: Functions in BUGS Standard functions Trigonometric functions Matrix algebra Distribution utilities and model checking Functionals and differential equations Miscellaneous C Appendix: Distributions in BUGS Continuous univariate, unrestricted range Continuous univariate, restricted to be positive Continuous univariate, restricted to a finite interval Continuous multivariate distributions Discrete univariate distributions Discrete multivariate distributions Bibliography Index
Combining Class-Specific Fragments for Object Classification

We describe an approach to object classification based on the conjunction of multiple classspecific object fragments detected in the image. The method represents members of a given class (such as a face, or a car) using combinations of common sub-structures, termed fragments. These fragments are partial 2-D patterns extracted from examples views of objects belonging to the class in question. An object view is covered by multiple, overlapping fragments of several types, and at multiple levels of complexity. We describe the detection of the individual fragments, and the combination of the fragments to detect complete objects. The combination of fragments to form a consistent overall arrangement is based in this scheme on a number of simple mechanisms: the use of overlapping fragments, a spatial `voting' scheme, and by imposing some constraints on the tolerated location of the fragments within the overall object view. We present experimental results of the application of the method to the detection of face and car views in cluttered scenes and to partially occluded objects. We present evidence that by combining fragments from different objects the method can deal successfully with intra-object variability within a class. The method is more economical and more resistant to occlusion and deformations than methods relying on global object views. Introduction In this paper we study the challenging task of detecting different objects from a given class (such as a face or a car) in an image. In addition to the unknown location and illumination of the object, the method must deal with intra-class variability between objects from the same class. The detection process must therefore cover a range of possible shapes, missing parts and additional clutter. To deal with the problem of shape variability and detect novel shapes of a given class, Turk & Pentland (1991) used the principal components of registered face views. Views of novel objects can be approximated by the superposition of several basis functions, or 'eigenfaces'. Poggio & Sung (1994) used a distribution-based modeling scheme for detecting faces in cluttered scenes. They represented a face view as a gray level vector with 283 components, and trained a multi-layered preceptron network to classify such data as face/non-face vectors. The generalization to novel shapes within the class is obtained in these schemes by the inherent generalization capacity of the neural network mechanism. Rowley, Baluja & Kanade (1995) and Lin, Kung & Lin (1996) BMVC99
Cue-motivated reward seeking is negatively regulated by expected reward magnitude in Pavlovian-instrumental transfer

The Pavlovian-instrumental transfer (PIT) paradigm is widely used to assay the motivational influence of reward-paired cues, which is reflected by their ability to stimulate instrumental reward-seeking behavior. Leading models of incentive learning assume that motivational value is assigned to cues based on the total amount of reward they signal (i.e., their state value). Based on recent findings, we lay out the alternative hypothesis that cue-elicited reward predictions may actually suppress the motivation to seek out new rewards through instrumental behavior in order to facilitate efficient retrieval of a reward that is already expected, before it is lost or stolen. According to this view, cue-motivated reward seeking should be inversely related to the magnitude of an expected reward, since there is more to lose by failing to secure a large reward than a small reward. We investigated the influence of expected reward magnitude on PIT expression. Hungry rats were initially trained to lever press for food pellets before undergoing Pavlovian conditioning, in which two distinct auditory cues signaled food pellet delivery at cue offset. Reward magnitude was varied across cues and groups. While all groups had at least one cue that signaled three food pellets, the alternate cue signaled either one (Group 1/3), three (Group 3/3), or nine food pellets (Group 3/9). PIT testing revealed that the motivational influence of reward-predictive cues on lever pressing varied inversely with expected reward magnitude, with the 1-pellet cue augmenting performance and the 3and 9-pellet cues suppressing performance, particularly near the expected time of reward delivery. This pattern was mirrored by opposing changes in the food-port entry behavior, which varied positively with expected reward magnitude. We discuss how these findings may relate to cognitive control over cue-motivated behavior. Reward-paired cues acquire motivational properties which allow them to facilitate the expression of instrumental reward-seeking behavior, a phenomenon referred to as Pavlovian-instrumental transfer (PIT)(Holmes et al., 2010; Cartoni et al., 2016; Corbit and Balleine, 2016). The PIT paradigm is widely used to study the mechanisms of Pavlovian incentive motivation and how they contribute to pathological reward seeking in addiction and related disorders in both humans (Garbusow et al., 2016; Vogel et al., 2018; Genauck et al., 2020; Sebold et al., 2021) and animal models (Wyvell and Berridge, 2001; Corbit and Janak, 2007; Saddoris et al., 2011; LeBlanc et al., 2012; Shiflett, 2012; LeBlanc et al., 2013; Shiflett et al., 2013; LeBlanc et al., 2014; Ostlund et al., 2014; Corbit and Janak, 2016; Marshall and Ostlund, 2018). However, despite decades of research, the specific factors that regulate the expression of PIT are not well
Trapping the Transition State in a [2,3]-Sigmatropic Rearrangement by Applying Pressure

Transition states are of central importance in chemistry. While they are, by definition, transient species, it has been shown before that it is possible to “trap” transition states by applying stretching forces. We here demonstrate that the task of transforming the transition state of a chemical reaction into a minimum on the potential energy surface can be achieved using hydrostatic pressure. We apply the computational extended hydrostatic compression force field (X-HCFF) approach to the educt of a [2,3]-sigmatropic rearrangement in both static and dynamic calculations and find that the five-membered cyclic transition state of this reaction becomes a minimum at pressures in the range between 100 and 150 GPa. Born–Oppenheimer molecular dynamics (BOMD) simulations suggest that slow decompression leads to a 70:30 mix of the product and the educt of the sigmatropic rearrangement. Our findings are discussed in terms of geometric parameters and electronic rearrangements throughout the reaction. To provide reference data for experimental investigations, we simulated the IR, Raman, and time-resolved UV/vis absorption spectra for the educt, transition state, and product. We speculate that the trapping of transition states by using pressure is generally possible if the transition state of a chemical reaction has a more condensed geometry than both the educt and the product, which paves the way for new ways of initiating chemical reactions.
VU Research Portal Clinical management of endometriosis

Objective: To evaluate long-term cyclic and continuous administration of oral contraceptive pills (OCP) in preventing ovarian endometrioma recurrence after laparoscopic cystectomy. Design: Prospective, randomized, controlled trial. Interventions: Patients were divided randomly into three groups: nonusers receiving no therapy and cyclic and continuous users receiving low-dose, monophasic OCP for 24 months in cyclic or continuous administration, respectively. Main Outcome Measures: Endometrioma recurrence, size of recurrent endometrioma, and growth rate during at least 2 years follow-up evaluated by transvaginal ultrasonography. Results: The crude recurrence rate within 24 months was significantly lower in cyclic (14.7%) and continuous users (8.2%) compared with nonusers (29%). The recurrence-free survival was significantly lower in nonusers compared with cyclic and continuous users. The mean recurrent endometrioma diameter at first observation was significantly lower in cyclic (2.17 ± 0.45 cm) and continuous users (1.71 ± 0.19 cm) compared with nonusers (2.73 ± 0.56 cm). The mean diameter increase every 6 months of follow-up was significantly reduced in cyclic users (0.31 ± 0.18 cm) and continuous users (0.25 ± 0.09 cm) versus nonusers (0.48 ± 0.3 cm). No significant differences between cyclic users and continuous users in terms of endometrioma recurrence were demonstrated. Conclusions: Long-term cyclic and continuous postoperative use of OCP can effectively reduce and delay endometrioma recurrence.
CLIMATE SCIENCE AND DROUGHT PLANNING: THE ARIZONA EXPERIENCE 1

ABSTRACT: In response to recent severe drought conditions throughout the state, Arizona recently developed its first drought plan. The Governor's Drought Task Force focused on limiting the economic and social impacts of future droughts through enhanced adaptation and mitigation efforts. The plan was designed to maximize the use of new, scientific breakthroughs in climate monitoring and prediction and in vulnerability assessment. The long term objective of the monitoring system is to allow for evaluation of conditions in multiple sectors and at multiple scales. Stakeholder engagement and decision support are key objectives in reducing Arizona's vulnerability in light of the potential for severe, sustained drought. The drivers of drought conditions in Arizona include the El Nino‐Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation.
Mineralogy and composition of the upper mantle

Seismic velocities are calculated for two petrological models of the upper mantle, an olivine-rich assemblage, pyrolite, and a garnet-clinopyroxene rich, olivine bearing, assemblage, piclogite. These are compared with recent seismic profiles for various tectonic provinces. The shield data is most consistent with a cold olivine and orthopyroxene-rich LID (the seismic lithosphere) extending to 150 km followed by a high temperature gradient and/or a change in mineralogy that serves to decrease the velocity. From 200 to 400 km the velocities follow a 1400°C adiabat. The rise-tectonic mantle is much slower, presumably hotter and is likely to be above the solidus to depths of at least 300 km. The high V_p/V_s ratio of the lower oceanic lithosphere in the western Pacific is most consistent with eclogite.
Seismic delineation of the Orion South kimberlite, Fort à la Corne, Canada

ABSTRACTThe Orion South (140/141) kimberlite is a diamondiferous, multiphase volcano-sedimentary complex within the Cretaceous Fort a la Corne kimberlite field of Saskatchewan, Canada. A network of seven high-resolution 2D seismic reflection profiles were acquired to test the utility of using seismic methods in defining the subsurface architecture of the kimberlite complex, and to provide auxiliary constraints on interborehole geologic correlations. The seismic data were interpreted in conjunction with a set of drillhole geologic logs and associated geologic sections and models, and physical rock properties from core measurements and geophysical logs. Core-determined average density values for the kimberlite suite are low (2240±16 kg/m3), but with some kimberlite facies having significantly higher values (2330 to 2540 kg/m3). Sonic velocities for the kimberlites are 2500−3500 m/s as compared with ∼2000 m/s and 3800−4500 m/s for the enveloping shale and sandstone units, respectively. The kimberlite is.
Settling velocities and vertical diffusion of particles in turbulent water

A turbulent flow field that permits study of the kinematics of individual suspended particles has been produced in the laboratory. This paper considers the behavior in the vertical direction of particles 2 mm in diameter that have still-water terminal settling velocities ranging up to 4.0 cm/sec. The particle velocity frequency distributions are approximately Gaussian, and their root-mean-square values prove to be nearly independent of terminal fall velocity. In the majority of cases, particle diffusivity is greater than fluid diffusivity. The average velocity of fall determined by experiment in the various turbulent fields is reduced by as much as 30% below the corresponding still-water terminal fall velocity. A simple theoretical model predicts the fall velocity reduction due to a nonlinearity in the drag force. The model is then extrapolated to describe the behavior of quartz sand under field-scale turbulence conditions. It also predicts the time and distance required for such sand to reach terminal fall velocity in still water.
Negative feedback regulation of auxin signalling by ATHB8/ACL5-BUD2 transcription module

The role of auxin as main regulator of vascular differentiation is well established, and a direct correlation between the rate of xylem differentiation and the amount of auxin reaching the (pro)cambial cells has been proposed. It has been suggested that thermospermine produced by ACAULIS5 (ACL5) and BUSHY AND DWARF2 (BUD2), is one of the factors downstream to auxin contributing to the regulation of this process in Arabidopsis. Here, we provide an in-depth characterization of the mechanism through which ACL5 modulates xylem differentiation. We show that an increased level of ACL5 slows down xylem differentiation by negatively affecting the expression of homeodomain-leucine zipper ( HD-ZIP ) III and key auxin signalling genes. This mechanism involves the positive regulation of thermospermine biosynthesis by the HD-ZIP III protein ARABIDOPSIS THALIANA HOMEOBOX8 tightly controlling the expression of ACL5 and BUD2 . In addition, we show that the HD-ZIP III protein REVOLUTA contributes to the increased leaf vascularization and long hypocotyl phenotype of acl5 likely by a direct regulation of auxin signalling genes such as LIKE AUXIN RESISTANT2 ( LAX2 ) and LAX3 . W e propose that proper formation and differentiation of xylem depends on a balance between positive and negative feedback loops operating through HD-ZIP III genes. Two counteractive regulatory loops are shown. The positive feedback loop consists of auxin flow. Auxin flow induces MP expression, MP induces auxin signalling genes and, in turn, HD-ZIP III genes. Among them REV positively reinforce the auxin flow by regulating LAX2 , LAX3 (this work), YUCCA5 and TAA1 (Brandt et al ., 2012). The negative feedback loop consists of an ATHB8/ACL5-BUD2 module tightly controlling thermospermine biosynthesis. Thermospermine acts as positive regulator of the bHLH SAC51 translation which, in turn, negatively regulates auxin signalling by unknown mechanism. The symbol represents a rheostat adjusting the rate of xylem differentiation as a function of auxin flow (i.e. auxin signalling).
SCR and SCRi ® as After-treatment Systems for Low CO 2 and Low NOx Vehicles

On one hand, latest worldwide emissions legislation developments aim to reduce NOx and Particulate Matter (PM) emissions of all diesel engines, while on the other hand lower fuel consumption diesel engines are still required for lower fl eet average CO2 emissions. As a consequence of the chosen CO2 optimized combustion mode, the raw NOx emission increases and as such Selective Catalytic Reduction (SCR) technology will be the future choice for high effi ciency NOx after-treatment. This paper deals with SCR technology and its derivative SCRi® technology, when diesel particle reduction is required, especially for Heavy Duty applications. Alongside the developed metal catalyst technologies, a complete SCR reducing agent dosing system is presented. Emission results gained with the SCR or SCRi® technologies on European commercial engines illustrate the potential of these technologies for conversion of NOx and PM emissions. This enables drafting of a road map for future emission control solutions, considering the local situation in India, for upcoming legislations. Keyword : SCRi®, DPF, PF, Hydrolysis Catalyst
On the Dynamics of Wind-Driven Lake Currents

Abstract Two time-dependent “vertical cross section models” are analyzed and applied to wind-driven currents in Lake Ontario. The models are: 1) a linear frictionless, two-level model, and 2) a numerical model which includes both friction and nonlinear terms. They predict current and temperature under the assumption that all variables except pressure are independent of the longshore coordinate. The longshore pressure gradient is computed from the condition that the volume transport normal to the cross section is zero. First, the quasi-static response of the linear frictionless model is studied to isolate the effects of topography and stratification on the structure of the coastal currents. It predicts that the vertically averaged longshore current is independent of both rotation and stratification, being in the direction of the wind where the water is shallower than average and opposite the wind in the deep water. Under homogeneous conditions, the strongest currents are confined to a thin (∼3 km wide for .
Ant Colony Optimization Based on Multi-Searching to Estimate the Natural Gas Demand: Case of Turkey

In this paper we propose a new version of the Ant Colony Optimization (ACO) to predict the natural gas demand problem. This heuristic approach will estimate the Turkey's natural gas demand based on economic indicators. The well-known ACO is multi-agent systems in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. In this paper the proposed approach presents that the many ant colonies begin the searching from different random points. Ant Colony Optimization Natural Gas Demand Estimation (ACONGDE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear and quadratic. Quadratic_ACONGDE provided better fit solution due to the fluctuations of the economic indicators. The ACONGDE model plans the natural gas demand of Turkey until 2025 for three scenarios. We also present an estimation of the natural gas demand for Central Anatolia Region of Turkey using population rates.
Prognostic significance of risk group stratification in elderly patients with acute myeloid leukaemia

Prognostic factors were studied in a series of 211 acute myeloid leukaemia (AML) patients over 60 years of age, treated at a single centre. The patients were allocated into three risk groups based on cytogenetics, occurrence of antecedent haematological disorder and leucocyte count. Only 3% had low‐risk features, 39% had intermediate‐ and 58% had adverse‐risk features. Complete remission (CR) was achieved in 43% of all patients. In multivariate analyses, the number of cycles needed to achieve CR and the risk group were significantly associated with the duration of CR. Median survival time for the entire cohort of patients was only 107 d. Advanced age, low induction treatment intensity, treatment during earlier years and adverse‐risk group were associated with shorter overall survival times. Risk group classification may help selection of elderly patients with a good chance of benefiting from intensive treatment to actually receive such treatment, while sparing others with a low probability of survival benefit from toxic treatment. Low intensity induction treatment reduces the chance of obtaining complete remission, produces inferior survival times and should consequently be avoided when the aim is to obtain complete remission. In elderly AML patients, introducing age and re‐evaluation of intermediate and good prognosis patients regarding response to induction treatment may improve the risk group classification.
Low diversity of foot-and-mouth disease serotype C virus in Kenya: evidence for probable vaccine strain re-introductions in the field

SUMMARY Most viruses are maintained by complex processes of evolution that enable them to survive but also complicate efforts to achieve their control. In this paper, we study patterns of evolution in foot-and-mouth disease (FMD) serotype C virus isolates from Kenya, one of the few places in the world where serotype C has been endemic and is suspected to remain. The nucleotide sequences encoding the capsid protein VP1 from eight isolates collected between 1967 and 2004 were analysed for patterns of sequence divergence and evolution. Very low nucleotide diversity (π=0·0025) and remarkably little change (only five segregating sites and three amino-acid changes) were observed in these isolates collected over a period of almost 40 years. We interpret these results as being suggestive of re-introductions of the vaccine strain into the field. The implications of these results for the maintenance of serotype C FMD virus and the use of vaccination as a control measure in Kenya are discussed.