Miracle-dz/UniFAR-FTUs huggingface dataset:
The trade-off between costs and carbon emissions from lot-sizing decisions

textabstractLogistics decisions can have a significant impact on carbon emissions, a driver of global warming. One possible way to reduce emissions is by adapting a lower delivery frequency, which enables better vehicle utilization or the usage of relatively effcient large vehicles. We study the situation in which a decision maker decides on the amount to be shipped in each period, where he/she can order items in each period and keep items on inventory. If the shipped quantity is large, vehicle capacity is well utilized, but many products have to be stored. Existing studies in this field of research, called lot-sizing, have introduced models for incorporating carbon emissions in the decision making, but do not focus on realistic values of the emission parameters. Therefore, we conduct a survey of empirical studies in order to establish the possible marginal emissions from holding inventory and performing a shipment with a truck. We consider a case study based on real-life considerations and on the findings of the survey study, and introduce a novel bi-objective lot-sizing model to find the Pareto optimal solutions with respect to costs and emissions. In our initial experiments, we consider various demand scenarios and other relevant factors, such as product properties and driven distances. We find that it is often costly to reduce carbon emissions from the cost optimal solution, compared to carbon prices in the market. The cases in which carbon emissions can be reduced most cost-effciently are those in which carbon emissions are large relative to costs, typically because costs are the results of past investments and can be considered sunk.
Coupled field models in electromagnetic solids

Purpose – To develop new and existing coupled thermal and mechanical models of electromagnetic solids for the simulation of coupled field problems based on a consistent theoretical and computational framework.Design/methodology/approach – The finite element computational models we describe involve the combination of classical electrodynamics, continuum mechanics, and thermodynamics. In order to create consistent coupled models, we employ the fundamental principles of thermodynamics as a common framework.Findings – Our procedure requires the necessary thermodynamical considerations for building consistent multiphysics models and develops some novel implementation issues that are important from the designers' point of view. Additionally, efficient numerical algorithms for solving the arising static and dynamic nonlinearities are discussed.Research limitations/implications – The paper targets the simulation of coupled problems in macroscopic electromagnetic continua.Practical implication – The application ar.
Upmixing stereo music signals based on dereverberation mechanism

We present a reverberation extraction method for upmixing stereo music signals that is based on our previously proposed dereverberation algorithm. This method utilizes multi-step linear prediction and decomposes the input signals into reverberation and the dereverberated signals. In the paper, we first analyze the behavior of the dereverberation algorithm using a stereo music signal model that consists of a reverberant center vocal signal and background signals in each channel. The background signals have no interand intra-channel correlation, and can be considered a simplification of a mixture of various music signals. Based on a mathematical analysis, we show that the algorithm simultaneously deals with a center vocal signal and background signals, and has potential to perform the efficient dereverberation of music signals. In the experiment, we apply the proposed reverberation extraction method to real stereo music signals, and confirm its effectiveness.
Plausible Generalization: Extending a Model of Human Plausible Reasoning

Transcripts of people answering questions or carrying on dialogues about everyday matters are filled with plausible inferences - inferences that are not certain, but that make sense. The same patterns of inferences occur in many different contexts. Often, in forming these inferences, people make generalizations that are equally uncertain but nevertheless are useful guides to reasoning. This article describes some important extensions to our earlier description of a core theory of plausible reasoning, based in large part on a new protocol study. The extensions are both data driven and theory driven. The primary focus here is on the inductive inference patterns people use to form plausible generalizations, that is, weakly held beliefs based on few examples but annotated with the same forms of certainty and similarity information that supported the inferential patterns described in our earlier work. We also provide examples of qualitative reasoning with inequalities and extend our formalism to cover that typ.
Highly confined photonic nanojet from elliptical particles

Elliptically shaped particles with different size and refractive indices have been studied under plane wave illumination using simulation tools such as 2D-FDTD, 2D-MMP, and 3D-MMP. Owing to careful manipulation, the power distribution in the vicinity of the particles opposite boundary resulted in a tightly focused photonic nanojet. Their waists are significantly smaller than the diffraction limit while propagating over several optical wavelengths without significant divergence. In this paper, we report on the manipulation of the particles elliptical shapes and the underlying refractive indices with respect to a maximally confined power distribution in the resulting nanojet which has been parameterized according to both, the beam waist and the beam divergence. The result that elliptical particles (i.e. oblate spheroids) turned out to be superior to spherical ones was underpinned within a highly accurate and fast 3D-MMP simulation using ring multipoles.
Some Further Remarks Concerning "A General Approach to the Estimation of Variance Components"

The estimates of Koch [1967a] have the undesirable property that they may change in value if the same constant is added to each of the observations. In this paper, an alternative procedure based on the same generd principles is developed and applied to a variety of models. As before, the estimators obtained are unbiased and consistent. They are also reasonably easy to compute. Finally, in the case of balanced experiments, they coincide with those obtained from the analysis of variance. On the other hand, their structure is more complex than that of the estimators considered in the previous paper. In particular, the derivation of their covariance matrix is much more complicated, and hence no attempt has been made here to study its properties.
Vapor-deposited emittance-catalysis coatings for superalloys in heat-shield applications

Statically oxidized Inconel 617 and MA 956 superalloys were prepared with vapor deposited aluminosilicate layers and exposed to temperatures which simulated reentry conditions. The aluminosilicate layers were 1-2 microns thick. The trials consisted of exposures to 1500-2300 F heat while surface temperatures were monitored with pyrometers. Analyses were then performed of the catalytic activity, oxidation phenomena, and radiative properties after thermal cycling the specimens for 8 hr. Both alloys were found to be catalytic to the recombination processes of dissociated species in the reentry environment. The coatings reduced the catalytic activity by 40 percent for both alloys but did not change the emittance. An enhanced Cr depletion zone was detected in the Inconel samples, implying that the coating did not prevent diffusion loss of Cr. The coated MA 956, on the other hand, gained weight over the course of the trials.
An Algorithm Based on Compound Anisotropic Diffusion for Image Denoising

In this paper we present a compound anisotropic diffusion filter algorithm to apply edge sensitive ICOV operator in NCD model. According to the correlation coefficient of the ICOV operator, we obtain effective nonlinear denoising. The experiment have validated that our algorithm have better effect in smoothing and better ability in edge preservation.
Comparative Analysis of Swarm Intelligence Techniques for Data Classification

This paper investigates the effectiveness of employing two relatively new swarm intelligence (SI) metaheuristic techniques in determining the accuracy of data classification problem. The SI metaheuristics analyzed are Grey wolf optimizer and firefly algorithm (FA). In this work, Grey wolf optimizer and firefly algorithm (FA) are used in training feed-forward neural networks (FNN) for the purpose of data classification. In experiments, the iris data has been used to evaluate the performance of the proposed algorithms. The experimental results obtained from these techniques are compared with that of a similar population-based technique, namely, particle swarm optimizer (PSO). Results obtained show that both GWO and Firefly algorithms provide superior solutions for the case studied.
Application of simulated annealing in a rectangular fin with variable heat transfer coefficient

This work deals with the inverse prediction of unknown parameters in a rectangular fin geometry subjected to a variable surface heat transfer coefficient. The unknowns which have been estimated are the thermal conductivity, the heat transfer coefficient at the base of the fin and the exponent for variable heat transfer coefficient. The estimations are done for satisfying a predefined temperature distribution obtained using some known fin properties from a forward method based on the decomposition scheme. Then, using the temperature information only at three locations, through the simulated annealing-based inverse algorithm, the unknowns are estimated. Due to correlated nature of the unknowns, many feasible combinations of the three unknowns have been found, which is proposed to offer the designer flexibility in selecting the fin material. The present inverse algorithm is proposed to be useful in situations where only few discrete temperatures are available, as it helps to find out the possible unknown properties which are required to satisfy a given temperature distribution.
A design for estimating visibility bias in aerial surveys

In aerial census data, "visibility bias" is present because the failure to observe all animals can result in severely biased population density estimates. Assuming that the aircraft can accommodate two observers situated on the same side, we present a design for estimating the magnitude of visibility bias, i.e., the probability of not observing an animal. The magnitude of visibility bias depends strongly on the propensity for animals to occur in groups and, thus, the design considers each possible group size separately. Two related methods of inference for the visibility bias parameters and the population total are described. We also discuss the application of the basic design and the associated survey methodology to an aerial survey of white-tailed deer in west-central Alberta.
90prime: a prime focus imager for the Steward Observatory 90-in. telescope

Steward Observatory is currently commissioning a prime focus wide-field imager for the 90-inch telescope located at Kitt Peak. The camera's focal plane array is populated with a mosaic of four thinned Lockheed 4096 x 4096 pixel CCDs. The f/2.98 system provides a plate scale of 0.45"/pixel and a total field-of-view of 1.16° x 1.16°. The optical design includes a four element corrector and six position filter wheel. The first science run was conducted in November 2003. We will describe the design of the "90prime" instrument and results from the commissioning runs.
Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS

Abstract A question that has received a great deal of attention in evaluating new treatments in acquired immune deficiency syndrome (AIDS) clinical trials is that of finding a good surrogate marker for clinical progression. The identification of such a marker may be useful in assessing the efficacy of new therapies in a shorter period. The number of CD4-lymphocyte counts has been proposed as such a potential marker for human immune virus (HIV) trials because of its observed correlation with clinical outcome. But to evaluate the role of CD4 counts as a potential surrogate marker, we must better understand the relationship of clinical outcome to an individual's CD4 count history over time. The Cox proportional hazards regression model is used to study the relationship between CD4 counts as a time-dependent covariate and survival. Because the CD4 counts are measured only periodically and with substantial measurement error and biological variation, standard methods for estimating the parameters in the Cox mod.
Exploring Roughness Perception in Car Engine Noises through Complex Cepstrum Analysis

Car engine noises have been analyzed from a psycho-acoustical point of view since early 90's. Classical psycho-acoustic parameters as loudness, sharpness and roughness have been used for this task, resulting in significant improvements in the annoyance caused in humans, especially for diesel engine noises. However, roughness sensation has been well defined and measured in modulated narrowband signals, but not in broadband noises. Here a new model of engine noise production is proposed in order to relate some of its features with the roughness perceived. The model is based on complex cepstrum analysis of the real engine noise, a technique widely used in speech processing, but not explored yet for psycho-acoustic sensations. A noise synthesizer is build for performing subjective tests and detect model parameters related to roughness perception. Results have shown that peak amplitudes range (represented by a certain amplitude modulation index of the impulses) is linearly related to roughness perceived, whereas frequency modulation index of the same impulse train has a weak influence on roughness sensation.
On a parameter identification problem in linear elasticity

Abstract We present numerical results concerning the identification of the Lamé constants λ and μ in linear elasticity from measured deformation of a test body. For the numerical solution of the identification problem deterministic Gauss – Newton and multi-parameter regularization approaches are compared with evolutionary algorithms. Furthermore we deal with practical questions such as the experimental design for obtaining sufficient data for recovering the unknown parameters.
VLA observations at 7 mm of the planetary nebula IC 4997

We present high angular resolution (0.1 arcsec) VLA observations at 7-mm wavelength towards the bipolar planetary nebula IC 4997. The 7-mm emission in IC 4997 is dominated by a bright, compact core, the flux density of which at this wavelength is about six times brighter than at 2.0 and 3.6 cm. We model the centimetre and millimetre continuum spectrum in terms of free–free emission from an ionized core–halo source. In this model a dense (2.6 × 106 cm−3), optically thick inner core dominates the millimetre emission, while a low-density (1 × 104 cm−3), optically thin halo dominates the centimetre emission. The spectral index of the core (between 2 cm and 7 mm) is α≃ 1.6 ± 0.1(Sν∝να), which is consistent with optically thick free–free emission. An upper limit for the mass-loss rate that created this inner core is ∼ 3 × 10−6 M⊙ yr−1, suggesting that this core may have been formed at the end of the superwind phase.
THE ROLE OF TERRESTRIAL AND MARINE PROTECTED AREAS IN DEVELOPING TOURISM INDUSTRY ( CASE STUDY : A SELECTION OF THE WORLD ' S HISTORICAL COUNTRIES )

Tourism industry has a special place in today’s world as one of the largest and cleanest industry in the glob. In the meantime, cultural and natural tourism as two major subfields of tourism may open new windows for better understanding of societies. The main objective of this research is to examine the role of terrestrial and marine protected areas in developing tourism industry in a selection of the world’s historical countries. The variables of terrestrial protected areas, marine protected areas, tourism per capita income, gross domestic product (GDP), governance quality, rail lines and number of arrivals international tourists is used to construct and identify a model for empirical part. A research gravity model has been estimated by using panel data technique for twelve most selected historical countries of the world, during the (1996-2012) period. The findings indicate positive and significant effects on the tourism industry for marine protected areas, terrestrial protected areas, gross domestic product (GDP) and rail lines variables. While, the results of the study show a negative and significant impact on the tourism industry for tourism per capita income variable. In between, governance quality coefficient is not significant.
XOP v2.4: recent developments of the x-ray optics software toolkit

XOP v2.4 consists of a collection of computer programs for calculation of radiation characteristics of X-ray sources and their interaction with matter. Many of the programs calculate radiation from undulators and wigglers, but others, such as X-ray tube codes, are also available. The computation of the index of refraction and attenuation coefficients of optical elements using user-selectable databases containing optical constants is an important part of the package for calculation of beam propagation. Coupled computations are thus feasible where the output from one program serves as the input to another program. Recent developments including enhancements to existing programs are described.
A Comparative Study of Artificial Boundary Conditions in ABAQUS

Viscous boundary, viscous spring boundary, infinite boundary have been widely used during the last decades to solve the wave propagation in the infinite ground. In this paper we evaluate the performance of the three boundary conditions focusing on their solution precision. The comparison is performed on a two dimensional finite element model built by ABAQUS. The results show that viscous spring boundary outperforms the other boundary conditions, and viscous boundary is better than infinite element.
State of the Art on : Deep Learning for Video Games AI Development

With the recent advancements in machine learning and, specifically, deep learning techniques, video games applications for AI research are becoming more and more popular, as they prove to be very useful testbeds for general AI algorithms evaluation [1]. At the same time, the need for a step forward in AI development, considering that the videogame industry has now reached an audience comparable to that of music and movies, is strongly perceived by both game developers and players. The former aim at building more complex and entertaining experiences, which in terms brings the latter to push for a higher believability and coherency of the game worlds they explore. Thanks to the amount of data that is being gathered on many video games, experiments showed how promising deep learning proves to be in this direction [2].
Trial of Galileon gravity by cosmological expansion and growth observations

Galileon gravity is a robust theoretical alternative to general relativity with a cosmological constant for explaining cosmic acceleration, with interesting properties such as having second order field equations and a shift symmetry. While either its predictions for the cosmic expansion or growth histories can approach standard ΛCDM, we demonstrate the incompatibility of both doing so simultaneously. Already current observational constraints can severely disfavor an entire class of Galileon gravity models that do not couple directly to matter, ruling them out as an alternative to ΛCDM.
The polarizer-analyzer correction problem in neutron polarization analysis experiments

The equations for correcting the instrumental depolarization effects in neutron polarization analysis experiments are presented in matrix form. It is proved that, when no approximations are made, it is always possible to solve for individual flipper efficiencies but is only sometimes possible to solve for polarizer and analyzer efficiencies. For certain experiments it is necessary to know these quantities to correctly analyze data. This is not a serious problem when the elements are very efficient, but has important ramifications when the efficiency is poor and/or time dependent, as is often the case with the helium-3 neutron polarizing method. Methods of solving for the polarizer and analyzer efficiencies are presented.
AN ANALYSIS METHOD FOR NONLINEAR BEHAVIOR OF RIGID PLATE ON SOIL UNDER CYCLIC LOAD

In this paper, a model with a rigid plate connected by discrete nonlinear springs to linearly elastic soil body is used to simulate the nonlinear load-settlement behavior of steel plate under cyclic loads in loading test. The nonlinearity of actual soil is considered in the springs of which the internal forces are proportional to the square roots of their displacements and the hysteretic characteristics fulfill Masing Law. At the same time, the internal forces of springs are limited by the bearing capacity due to soil shear failure. While, the soil in this model is a linearly elastic body, which is expressed by Boussinesq solution. Parameters of elastic modulus, bearing capacity and nonlinear coefficient of spring are back-calculated from test data. This hybrid model is used to predict the behavior of steel plate under cyclic vertical loads. Analyses are carried out for both circular and square plates on cohesive and cohesionless soils. Comparisons show that the analyses are in good agreement with test data.