Miracle-dz/UniFAR-FTUs huggingface dataset:
Suppliers Dynamic Approach to Invest in R&D with Sunk Costs in Indian Contexts

In this paper we test for the presence of sunk costs in suppliers’ R&D activities by analyzing the persistence of these activities using supplier level panel data. We develop and estimate a dynamic discrete choice model where each supplier’s current R&D expenditure is a function, among other factors, of its previous experience in performing R&D activities. The data used is a panel data of Indian suppliers, for the period 2003 - 2013. We find that prior R&D experience significantly affects the current decision to invest in R&D, and that, although important, the effect of prior R&D experience depreciates fairly quickly over time.
Habitat Use and MoveMent Patterns of bUtler ’ s Gartersnake ( Thamnophis buTleri ) in soUtHwestern ontario , Canada

—Butler’s Gartersnake (Thamnophis butleri) is listed as Endangered in Canada. Data on its spatial ecology are sparse and information on habitat use, movement patterns, and home range size are needed to prevent further declines. We captured snakes using coverboard refuges and implanted transmitters into 13 individuals (12 females, one male), to track movement and habitat use in southwestern Ontario. Home ranges were distributed nonrandomly in the study area, and habitat use at this scale showed a preference for open habitats with few trees and grass as the predominant ground cover. Daily movement rates of tracked snakes were short and localized (about 14 m/day) but increased in length in late summer. Based on the coverboard capture data, maximum distances moved between recapture events of marked individuals were typically < 100 m for males and females, although males made longer movements on average. Female home range size was estimated to be 0.9 ha from the telemetry data. This study is the first to document Butler’s Gartersnake hibernacula in Ontario, and likely live-birthing areas from locations of gravid females. Knowledge of the spatial ecology of endangered Butler’s Gartersnake obtained from this study will help facilitate habitat management and recovery of this species.
MetaMorphosed Marbled salaManders ( AmbystomA opAcum )

—In terrestrial habitats with a history of mining activity, understanding the effects of soil acidification on the ecology of amphibians is an important part of the restoration process and of the conservation of local amphibian populations. After metamorphosis, pond-breeding amphibians spend much of their life in direct contact with the soil in upland habitat adjacent to aquatic breeding sites. Given the thin, permeable skin of amphibians, abiotic soil characteristics likely affect their physiology, behavior, and fitness. We reared recently metamorphosed Marbled Salamanders (Ambystoma opacum) in the laboratory at four pH levels (pH 4, 5, 6 and 7) to evaluate the effect of soil acidity on determinants of fitness, such as growth and survival. A pH of 4 was lethal to recent metamorphs, but there were no significant differences in survival among the three higher pH treatments. Among animals surviving the higher pH treatments, individuals reared on substrates of pH 5 were shorter in both total length and snoutvent-length by the end of the experiment than individuals reared on substrates of pH 6 and pH 7. We suggest that substrate acidity can affect the fitness of A. opacum through direct mortality and through a decrease in the growth rate of salamanders subsequent to metamorphosis. Thus, negative effects of post-mining acidification likely extend into terrestrial habitats for pond breeding amphibians.
Electric Spot Prices and Wind Forecasts: A dynamic Nordic/Baltic Electricity Market Analysis using Nonlinear Impulse-Response Methodology

This paper uses nonlinear impulse response methodologies to analyse the relationship between the contemporaneous Nordic/Baltic electric spot prices and wind forecasts. The main objective of the analysis is step-ahead spot price movements from wind forecast information. Dynamic impulse response analysis is a technique for analysing the step-ahead characteristics of a nonparametric estimate of the one-step-ahead conditional density. From strictly stationary processes we build a bivariate price/wind semi-parametric density model. The model estimates report a significant negative non-linear covariance between spot prices and wind forecasts movements in the Nordic/Baltic electricity market. The impulse-response analysis shows that the stepahead contemporaneous co-variance between spot prices and wind forecasts are one important predictor for the spot price mean movements and volatilities. A dynamic nonlinear impulse-response analysis can therefore offer market participants access to dynamic step-ahead spot price mean and volatility strategies. Classification:
An ExpErimEntAl ApproAch to UndErstAnding ElEvAtion limits in thE northErn grAy-chEEkEd sAlAmAndEr , Plethodon montanus

—As global temperatures rise, there is an urgency to understand the limiting factors of ranges of species and how those factors vary across the range to develop predictions of shifts in spatial distributions. A long-standing hypothesis postulates that, for Northern Hemisphere species, abiotic factors, such as temperature, limit northern or higher elevation extents, while biotic factors like competition limit the southern or lower elevation range edges. Recent evidence, however, suggests that salamanders may follow the opposite of this general trend, although experimental tests of this hypothesis are lacking. Therefore, we determined the role of origin population (i.e., where individuals were captured) and transplant location (i.e., where individuals were placed) on survival, growth, and reproduction using a reciprocal transplant experiment across an elevational gradient with the Northern Graycheeked Salamander (Plethodon montanus). We collected juveniles from each of three elevations and transplanted them within mesocosms such that each origin population was represented within each transplant location. We found that individuals transplanted to low elevations had lower survival and growth rates compared to those moved to mid or high elevations regardless of origin location; whereas, individuals originating from low elevations had the highest survival regardless of their transplant location. Our study provides experimental support that conditions found at lower elevations limit the distribution of P. montanus but populations at the lower edge may feature adaptive traits that increase survival. Although climate change is predicted to reduce environmental suitability for this species especially at lower elevations, these traits may be important to mitigating extirpations.
Bayesian inference in high-dimensional models

Models with dimension more than the available sample size are now commonly used in various applications. A sensible inference is possible using a lower-dimensional structure. In regression problems with a large number of predictors, the model is often assumed to be sparse, with only a few predictors active. Interdependence between a large number of variables is succinctly described by a graphical model, where variables are represented by nodes on a graph and an edge between two nodes is used to indicate their conditional dependence given other variables. Many procedures for making inferences in the high-dimensional setting, typically using penalty functions to induce sparsity in the solution obtained by minimizing a loss function, were developed. Bayesian methods have been proposed for such problems more recently, where the prior takes care of the sparsity structure. These methods have the natural ability to also automatically quantify the uncertainty of the inference through the posterior distribution. Theoretical studies of Bayesian procedures in high-dimension have been carried out recently. Questions that arise are, whether the posterior distribution contracts near the true value of the parameter at the minimax optimal rate, whether the correct lower-dimensional structure is discovered with high posterior probability, and whether a credible region has adequate frequentist coverage. In this paper, we review these properties of Bayesian and related methods for several high-dimensional models such as many normal means problem, linear regression, generalized linear models, Gaussian and non-Gaussian graphical models. Effective computational approaches are also discussed.
Combined Effects of Brand Co-Creation, Customization on Brand Trust and Word-of-Mouth: Mediating Role of Perceived Brand authenticity and Moderating Role of Need for Uniqueness A study from Islamic Perspective

Received: 5 April 2018 Accepted: 25 June 2018 Abstract. The concept of authenticity in brands is the call of hour. Despite the recent attempts towards conceptualization of Perceived Brand Authenticity (PBA), researchers seem unwilling to study the predecessors and impact of PBA on other variables and constructs in marketing research. In this regard, Morhart, Malär, Guèvremont, Girardin, and Grohmann (2015) called for research on the antecedents and consequences of PBA. Researchers may study customization and co-creation engagement in relation to the PBA (Fritz, Schoenmueller, & Bruhn, 2017; Morhart et al., 2015). This study is relational/ causal study. It is based on the responses of variables within the natural settings of the respondents. The survey questionnaire is filled by customers using different brands and is part of brand fan pages. Study collected data from 200 customers using branded products through online survey. From Islamic perspective, results of the study are completely aligned with the teachings of Islam in terms of which one should not spread news that has no proof. The study suggests that the participants of customization and co-creation process have the proof and evidence to speak truth regarding a brand/product. This study provides useful implication for researchers and managers; it fills the theoretical gap, and urges managers for co-creation and customization.
A Web Based Tool For the Detection and Analysis of Avian Inﬂuenza Outbreaks From Internet News Sources

A BSTRACT : There is an ever increasing amount of publicly available data available relating to disease outbreaks on the Internet. However it is almost impossible for an individual to keep up with all of this data anymore. This paper introduces an automated system that takes in RSS news feeds related to avian inﬂuenza and automatically geocodes them. These articles are then stored in a spatially enabled database and served to the Internet using open standard web mapping protocols. A custom client with mapping and time bar facilities is provided to allow non-expert users easy access to the data. Real-time RSS feeds coupled with a mapping interface allow for up-to-date data that depicts active disease spreading. By utilizing frequently updated ofﬁcial and unofﬁcial sources through the acquisition of RSS feeds, origins and dispersal patterns of diseases such as Avian Inﬂuenza can be analyzed and hopefully aid in containing the disease, treating those affected, and improving future prevention methods.
Business Models and Competitive Advantage: A Dynamic Approach

Objetivo: Demonstrar como o modelo de negócio Canvas pode se tornar dinâmico a partir de uma perspectiva conceitual. Metodologia / abordagem: Este estudo é de natureza qualitativa, descritiva e exploratória, com abordagem teórica, baseada nos principais teóricos. Originalidade / Relevância: Este estudo pressupõe o fortalecimento da literatura de modelo de negócio na perspectiva da competitividade dinâmica. Ele define modelo de negócio dinâmico e o diferencia de um modelo estático. Isso permite avaliar os fatores que fazem com que um modelo de negócio se torne estático e, portanto, não esteja preparado para uma lógica de negócios que crie valor e gere vantagem competitiva. Principais resultados: No final do ensaio, foi possível entender, a partir de uma perspectiva teórica, que o Modelo de Negócio Dinâmico contribui para a criação de valor e a geração de vantagem sustentável em ambientes de alta mudança. Contribuições teórico-metodológicas: Este estudo identificou três pressupostos conceituais que constituem o modelo de negócio dinâmico. Primeiro, o desenho dos modelos de negócios - interdependência e conexão entre seus elementos constitutivos. Em segundo lugar, os modelos de negócios ligados a capacidades dinâmicas. E por fim, a busca pela captura de valor e geração de vantagens competitivas sustentáveis pelas empresas. A partir dessas conclusões, foi possível avaliar o modelo de negócio Canvas na perspectiva de um modelo dinâmico. Palavras-chave: Modelos de negócio; Vantagem Competitiva; Canvas; Abordagem Dinâmica
EfficiEnt Estimation of amphibian clutch sizE using imagE analysis of comprEssEd globular Egg massEs

—Clutch size estimation for amphibians is a time intensive task where researchers often opt to hand count eggs one at a time, limiting the application of clutch size information in research. Contemporary methods seek to build a standard curve from a representative hand counted sample, then estimate the remaining samples based on measures such as displacement or dry weight. These methods, however, often result in the mortality of sampled egg masses while limiting the scalability and application of research connected to amphibian clutch size. Here we demonstrate the feasibility of an efficient and nondestructive survey method that integrates photographs taken in the field of compressed amphibian egg masses in an ovagram with open source computer software to automate counting in the lab. We compared manual counts to automated counts from compressed egg mass photographs of Lithobates sylvaticus (Wood Frog), L. pipiens (Northern Leopard Frog), and Ambystoma maculatum (Spotted Salamander), which were turned into black and white images with two ImageJ processes and then analyzed. We found that automated counts were much quicker than manual counts for all species and were more accurate for L. sylvaticus and A. maculatum than for L. pipiens. The main factor limiting accuracy in photograph counts was the resolution of individual eggs in an egg mass, suggesting future work should focus on greater attention to photographic conditions in the field.
Comment: A nonparametric super-efficient estimator of the average treatment effect

We congratulate Benkeser, Cai and van der Laan on their valuable and timely article which contributes an improved approach to estimate the average treatment effect (ATE) in observational studies. While the traditional semiparametric doubly-robust methods—the one-step and the targeted minimum loss estimation (TMLE)—are locally efficient when the relevant nuisance parameters are consistently estimated, they could exhibit finite-sample bias and excess variability in challenging scenarios when the propensity score distribution has a long tail. Using the adaptive propensity score, defined as the conditional probability of assignment given the conditional mean outcome, in the construction of the semiparametric estimators, the authors demonstrated super-efficiency over their locally efficient counterparts. As the adaptive propensity score may be inconsistent to the true propensity score, the proposed collaborative estimators trade off the double robustness property for greater stability and efficiency. In this discussion, we would like to contribute our thoughts on alternative methods that may improve the finite-sample behaviour of the semiparametric estimators, in challenging scenarios when there is lack of overlap and the causal estimand is only weakly identifiable. For inverse probability weighting (IPW), a common remedy for lack of overlap is to trim observations with extreme propensity scores and restrict the analysis to the subpopulation where the average causal effect is better identified. To avoid arbitrary selection of the trimming threshold, Crump et al. (2009) developed the optimal symmetric trimming rule where the asymptotic variance of the weighted estimator is minimized among all symmetric trimming rules. By continuously down-weighting influential observations at the propensity tails, Li, Morgan and Zaslavsky (2018) introduced the overlap weights which target the average causal effect among the subpopulation with substantial equipoise. The overlap weights are also efficient in a sense that they minimize the asymptotic variance of the weighted estimator among the larger family of balancing weights. While these alternative weighting schemes address limitations of IPW, it is less clear whether they could improve the performance of the doublyrobust estimators in challenging scenarios. In what follows, we introduce these two weighting schemes to the one-step and TMLE framework for stabilization purposes, and evaluate their operating characteristics under lack of overlap.
The Variables Most Closely Associated With Academic Achievement: A Review of the Research Literature

The Learning Community (LC) of Douglas and Sarpy Counties currently bases its decisions about how to allocate funding for academic achievement on formulae that have not been validated through research. The main purpose of this literature review is to provide the LC with science-based information about the relative strength of the association between the out-of-school variables to which it has access, and academic achievement—information it can use to identify and target the populations of elementary school children with the greatest need for academic assistance. The research demonstrates that socioeconomic status (SES) is the strongest predictor of academic achievement. Of the various measures of SES, composite measures are better predictors of academic achievement than single measures. Of the composite Karen Abrams, MPH is a researcher with the Progressive Research Institute of Nebraska (PRI) and Fanying Kong, Ph.D. is a professor of sociology at Bellevue University, Bellevue, NE 68005. PRI Progressive Research Institute of Nebraska PRI LITERATURE REVIEW September 2012 2 measures of SES, family SES is the most commonly used. The best family SES measures across the literature include three variables: parent income, parent occupation and parent education level. We found that school SES is also a strong predictor of academic achievement. The research demonstrates that neighborhood SES is a less precise predictor of achievement than either family or school SES. We also found evidence that two of the variables currently used by the LC to allocate funding across the region— English language learners and school mobility—are most likely inadequate predictors of academic achievement. An important finding from the research is that several of the variables we examined predict children’s academic achievement differently depending on whether the children are white or minority. In our conclusion, we discuss the relative merit of the variables we examined, and rank them; we also discuss ways in which the Learning Community might use the results of this review.
Ab Initio atomistic thermodynamics modeling of adsorption of oxygen on gold and gold-silver surfaces

A theoretical study of oxygen adsorption on gold and gold-silver surfaces by means of density functional theory (DFT) calculations with an atomistic thermodynamic model is performed. The (111) and (211) facets of gold and gold-silver alloy surfaces are considered, and their stabilization is discussed upon adsorption of oxygen depending on O and Ag coverage. The details of how the DFT-based atomistic thermodynamic model can apply to the transition metal surface are also presented in this work.
A Novel Hybrid Approach to Visual Concept Detection Using Image Annotation

Millions of images are being uploaded on the internet without proper description (tags) about these images. Image retrieval based on image tagging approach is much faster than Content Based Image Retrieval (CBIR) approach but requires an entire image collection to be manually annotated with proper tags. This requires a lot of human efforts and time, and hence not feasible for huge image collections. An efficient method is necessary for automatically tagging such a vast collection of images. We propose a novel image tagging method, which automatically tags any image with its concept. Our unique approach to solve this problem involves manual tagging of small exemplar image set and low-level feature extraction of all the images, hence called a hybrid approach. This approach can be used to tag a large image dataset from manually tagged small image dataset. The experiments are performed on Wang’s Corel Dataset. In the comparative study, it is found that, the proposed concept detection system based on this novel tagging approach has much less time complexity of classification step, and results in significant improvement in accuracy as compared to the other tagging approaches found in the literature. This approach may be used as faster alternative to the typical Content Based Image Retrieval (CBIR) approach for domain specific applications.
The evaluation of real-time indoor environment parameters measured in 297 Chilean dwellings

People spend the majority of their time in their own homes and so the indoor environmental conditions are an important determinant of population health and wellbeing and have economic consequences. Chile is undergoing rapid economic growth and is managing its national energy demand to minimize its greenhouse gas emissions. Its housing stock is growing rapidly, and is responsible for 15% of national energy demand. Accordingly, there is a need to understand the performance of the stock by measuring parameters that indicate air quality, thermal comfort, and energy demand. This study is a preliminary examination of real-time indoor and outdoor measurements of air temperature made in 297 dwellings during 2016 and 2017 as part of the Red Nacional de Monitoreo de Viviendas (ReNaM) program, implemented by The Ministry of Housing and Urbanism of Chile. Indoor temperatures are generally found to be cold when compared to the European adaptive model of thermal comfort, EN 15251. However, they are above temperature thresholds found to affect negatively the health of vulnerable groups for 78% of the time. There are significant seasonal differences in indoor air temperature but modest differences between day and night time temperatures. The winter temperatures are low, indicating limited effective heating, and households of low socio-economic status are colder than those of mid and high status. There is no evidence of mechanical cooling in the summer.