Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Brand Image and Brand Benefit on Customer Loyalty: The Case of Turkey

Purpose - This study aims to investigate the effect of brand image and brand benefit on customer loyalty. Design/methodology/approach - Primary data collection method was used in the study. The survey method was used as the primary data collection. The questionnaire was easily applied to 286 consumer groups living in Bingol through sampling to obtain the necessary data. The results were tested by correlation and regression analysis. Findings - As a result of the tests, only the brand image seems to have an effect on customer loyalty (H1 hypothesis was supported). "Brand benefit, customer loyalty" and "brand image, brand benefit" did not affect (H2 and H3 hypotheses were not supported). Research limitations/implications - It was thought that it would not be possible to reach the population because the research had limitations in terms of time, cost, accessibility and control difficulties. The study was conducted for the consumer group living in Bingol. This limitation can be removed by expanding the population. Originality/value - The hypothesis of "H1: Brand image affects customer loyalty in a significant and positive way" hypothesis was supported (P = 0.004) according to the results of correlation and regression analysis in this study which investigated the effect of brand image and brand benefit on customer loyalty. The other hypotheses were not supported (H2: P = 0,338; H3: P = 0.077):"H2: Brand benefit affects customer loyalty in a significant and positive way" and "H3: There is a significant and positive relationship between brand image and brand benefit. "
Gravitational Collapse of Spherical Interstellar Clouds

In this paper, the gravitational collapse of spherical interstellar clouds is discussed based on hydrodynamical simulations. The evolution is divided into two phases: former runaway collapse phase, in which the central density increases greatly on a finite time scale, and later contraction, associated with accretion onto a newborn star. The initial density distribution is expressed using a ratio of the gravitational force to the pressure force a. The equation of state for a polytropic gas is used. The central, high-density part of the solution converges on a self-similar solution, which was first derived for the runaway collapse by Larson and Penston (LP). In the later accretion phase, gas behaves like a particle, and the infall speed is accelerated by the gravity of the central object. The solution at this stage is qualitatively similar to the inside-out similarity solutions first found by Shu. However, it is shown that the gas-inflow (accretion) rate is time-dependen t, in contrast to the constant rate of the inside-out similarity solutions. For isothermal models in which the pressure is important, 1 < a < 3.35, the accretion rate reaches its maximum when the central part, which obeys the LP solution, contracts and accretes. On the other hand, in isothermal models in which gravity is dominant, a ^ 3.35, the accretion becomes most active at the epoch when the outer part of the cloud falls onto the center. The effect of the non-isothermal equation of state is discussed.
School Year Length and Student Performance: Quasi-Experimental Evidence

This paper investigates the impact of instructional days on student performance. Because school year length is endogenously determined, I estimate the causal impact of school year length through two quasi-experiments that exploit different sources of variation in instructional days. The fi rst approach identifies school year length's effect through weather-related cancellations in Colorado and Maryland. Weather-related cancellations are made up at the end of school years, allowing relatively large fluctuations in instructional days within school districts prior to test administration. Because school cancellations are not recorded for past school years, this data limitation is overcome by using two-sample indirect least squares. The second identi fication strategy takes advantage of state-mandated changes in test-date administration in Minnesota, which moved 5 times in 5 years. The results are similar for either source of instructional day variation: more instructional time prior to test administration increases student performance. The effects are consistent across various thresholds of performance and grade levels.
Testing the Universality of the (u − V ) Color-magnitude Relations for Nearby Clusters of Galaxies

We present a detailed (U − V) color-magnitude relation (CMR) analysis for three local (z < 0.06) clusters of galaxies. From square-degree imaging of the Abell clusters A85, A496, and A754, we select 637 galaxies down to L ∼ 0.1L ⋆ V with spectroscopic membership, which minimizes uncertain field contamination corrections. To characterize the degree of CMR uniformity among nearby clusters, we use a maximum likelihood technique to quantify the CMR properties of the red galaxies in each cluster. We find that these clusters have similar CMRs with a mean color of (U − V) = 1.40 at M V = −20 + 5 log 10 h, and narrow limits of intrinsic color scatter [0.047,0.079] and slope [-0.094,-0.075]. If we restrict our analysis to the core cluster population of red galaxies, the resultant CMRs are in close agreement with that of the Coma Cluster, the only local cluster with a rest-frame (U − V) CMR determination of comparable precision. Therefore, the CMR uniformity of present-day clusters spans a fairly wide range of cluster masses. We test how sensitive the CMR uniformity is to variations in color aperture size and sample selection, and we find at most slightly wider limits of scatter [0.047,0.112] and slope [-0.104,-0.054]. This upper limit for (U − V) scatter is consistent with the bulk of the stellar populations of red cluster galaxies forming before z = 1.2, with a maximum age spread of 5.2 Gyr. In addition, we note that using colors from apertures containing equal fractions of galactic light does not remove the CMR slope and that none of the slopes exhibit a break as claimed by Metcalf et al. Our findings expand the single Coma data point and provide a much-needed z = 0 baseline for comparisons to high redshift cluster CMRs at the same rest-frame wavelengths. The range in CMR scatter that we find among nearby clusters is consistent with the values reported for clusters at higher redshifts, further suggesting that there has been little evolution in the stellar populations of red-sequence cluster galaxies out to at least z ∼ 1. To identify the most recently accreted cluster galaxies, we divide each cluster's membership into three galaxy populations based on (U −V) color relative to the well-defined CMR. Blue and moderately blue galaxies make up 18 − 23% by number of each cluster population more luminous than 0.1L ⋆. Our color-magnitude division should …
Compressive Sensing Ensemble Average Propagator Estimation via L1 Spherical Polar Fourier Imaging

In diffusion MRI (dMRI) domain, many High Angular Resolution Diffusion Imaging (HARDI) methods were proposed to estimate Ensemble Average Propagator (EAP) and Orientation Distribution Function (ODF). They normally need many samples, which limits their applications. Some Compressive Sensing (CS) based methods were proposed to estimate ODF in Q-Ball Imaging (QBI) from limited samples. However EAP estimation is much more difficult than ODF in QBI. Recently Spherical Polar Fourier Imaging (SPFI) was proposed to represent diffusion signal using Spherical Polar Fourier (SPF) basis without specific assumption on diffusion signals and analytically obtain EAP and ODF via the Fourier dual SPF (dSPF) basis from arbitrarily sampled signal. Normally the coefficients of SPF basis are estimated via Least Square with weighted L2 norm regularization (L2-SPFI). However, L2-SPFI needs a truncated basis to avoid overfitting, which brings some estimation errors. By considering the Fourier relationship between EAP and signal and the Fourier basis pair provided in SPFI, we propose a novel EAP estimation method, named L1-SPFI, to estimate EAP from limited samples using CS technique, and favorably compare it to the classical L2-SPFI method. L1-SPFI estimates the coefficients in SPFI using least square with weighted L1 norm regularization. The weights are designed to enhance the sparsity. L1-SPFI significantly accelerates the ordinary CS based Fourier reconstruction method. This is performed by using SPF basis pair in CS estimation process which avoids the numerical Fourier transform in each iteration step. By considering high order basis in L1 optimization, L1-SPFI improves EAP reconstruction especially for the angular resolution. The proposed L1-SPFI was validated by synthetic, phantom and real data. The CS EAP and ODF estimations are discussed in detail and we show that recovering the angular information from CS EAP requires much less samples than exact CS EAP reconstruction. Various experiments on synthetic, phantom and real data validate the fact that SPF basis can sparsely represent DW-MRI signals and L1-SPFI largely improves the CS EAP reconstruction especially the angular resolution.
An Uncommon Feature of Chronic Granulomatous Disease in a Neonate

Chronic Granulomatous Disease (CGD) represents recurrent life-threatening bacterial and fungal infections and granuloma formation with a high mortality rate. CGD's sign and symptoms usually appear in infancy and children before the age of five; therefore, its presentation in neonatal period with some uncommon features may be easily overlooked. Here we describe a case of CGD in a 24-day-old boy, presenting with a diffuse purulent vesiculopustular rash and multiple osteomyelitis.
Trade Policy and Sectoral Manufacturing Specialization

Trade liberalization leads to significant changes in countries’ economic structures. The implied variation in the level and nature of specialization has important consequences for liberalizing economies. Thus, adjustments costs associated with those structural changes may be substantial. Furthermore, the changing specialization profile of countries may affect growth potential, welfare, income distribution, and the macroeconomic environment. It is therefore extremely relevant for those countries pursuing trade liberalization initiatives to know their current specialization profiles and how they would look like under lower trade costs, because this will allow them to anticipate their effects on the potential for development as well as to accordingly define policy strategies. This study examines manufacturing production specialization patterns in ten Latin American countries (Argentina, Brazil, Bolivia, Chile, Colombia, Ecuador, Mexico, Peru, Uruguay and Venezuela) over the period 1990-2001, and explicitly assesses the impact of trade policy and, in particular, the implications of a free trade area with the United States. A theory-consistent measure of specialization is derived from the standard international trade theory: the share of the industry in the country’s GDP. The role of trade policy in shaping the distribution of these shares is then investigated using a simultaneous equation approach on sectoral value added and tariff and factor endowment data.
Response to Reviewer Comments

We thank both referees for their time to review this manuscript as well as their constructive critiques and suggestions. Both referees write that the manuscript is suitable for publication in ACP. The two major suggestions were (1) to expand the introduction to include material that was only presented in the discussion (referee #1), and (2) to explicitly discuss the thermodynamically favored morphology (referee #2). The requested material has been added to the manuscript. Below are itemized responses explaining how all of the referees’ critiques were addressed.
Consensus and Divergence in Perceptions of Cognitive Strategic Groups: Evidence from the Health Care Industry

We examined the extent to which consensus existed among hospital administrators' cognitive strategic groups and explored task and institutional factors that might influence these perceptions. We elicited perceived strategic groups from hospital administrators in a distinct geographic market using the full context form of the repertory grid. Our evidence indicates that beliefs are shared by a majority of administrators in the region, that differences in perception are associated with strategic position, and that cognitive groups focus managerial attention. These findings highlight the roles of both task and institutional environments on cognitive strategic group formation and suggest an important role for these groups in strategic decision-making.
Integrating 2-D Video Actors into 3-D Augmented-Reality Systems

In this paper, we discuss the integration of 2-D video actors into 3-D augmentedreality (AR) systems. In the context of our research on narrative forms for AR, we have found ourselves needing highly expressive content that is most easily created by human actors. We discuss the feasibility and utility of using video actors in an AR situation and then present our Video Actor Framework (including the VideoActor editor and the Video3D Java package) for easily integrating 2-D videos of actors into Java 3D, an object-oriented 3-D graphics programming environment. The framework is based on the idea of supporting tight spatial and temporal synchronization between the content of the video and the rest of the 3-D world. We present a number of illustrative examples that demonstrate the utility of the toolkit and editor. We close with a discussion and example of our recent work implementing these ideas in Macromedia Director, a popular multimedia production tool.
Service Rating Prediction by Exploring Social Mobile Users’ Geographical Locations

Recently, advances in intelligent mobile device and positioning techniques have fundamentally enhanced social networks, which allows users to share their experiences, reviews, ratings, photos, check-ins, etc. The geographical information located by smart phone bridges the gap between physical and digital worlds. Location data functions as the connection between user's physical behaviors and virtual social networks structured by the smart phone or web services. We refer to these social networks involving geographical information as location-based social networks (LBSNs). Such information brings opportunities and challenges for recommender systems to solve the cold start, sparsity problem of datasets and rating prediction. In this paper, we make full use of the mobile users’ location sensitive characteristics to carry out rating prediction. We mine: 1) the relevance between user's ratings and user-item geographical location distances, called as user-item geographical connection, 2) the relevance between users’ rating differences and user-user geographical location distances, called as user-user geographical connection. It is discovered that humans’ rating behaviors are affected by geographical location significantly. Moreover, three factors: user-item geographical connection, user-user geographical connection, and interpersonal interest similarity, are fused into a unified rating prediction model. We conduct a series of experiments on a real social rating network dataset Yelp. Experimental results demonstrate that the proposed approach outperforms existing models.
A New Model of Trend Ination

This paper introduces a new model of trend (or underlying) ination. In contrast to many earlier approaches, which allow for trend ination to evolve according to a random walk, ours is a bounded model which ensures that trend ination is constrained to lie in an interval. The bounds of this interval can either be xed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of ination. The bounds placed on trend ination mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend ination model. In an empirical exercise with CPI ination we nd the model to work well, yielding more sensible measures of trend ination and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.
Quartet-net Learning for Visual Instance Retrieval

Recently, neuron activations extracted from a pre-trained convolutional neural network (CNN) show promising performance in various visual tasks. However, due to the domain and task bias, using the features generated from the model pre-trained for image classification as image representations for instance retrieval is problematic. In this paper, we propose quartet-net learning to improve the discriminative power of CNN features for instance retrieval. The general idea is to map the features into a space where the image similarity can be better evaluated. Our network differs from the traditional Siamese-net in two ways. First, we adopt a double-margin contrastive loss with a dynamic margin tuning strategy to train the network which leads to more robust performance. Second, we introduce in the mimic learning regularization to improve the generalization ability of the network by preventing it from overfitting to the training data. Catering for the network learning, we collect a large-scale dataset, namely GeoPair, which consists of 68k matching image pairs and 63k non-matching pairs. Experiments on several standard instance retrieval datasets demonstrate the effectiveness of our method.
The metabolic theory of ecology and algal bloom formation

Rose and Caron (2007) have compiled a comprehensive data set of individual growth rates of planktonic protists in an attempt to answer a fundamental question in marine ecology: ‘‘Why are blooms of phytoplankton such common events in the ocean? ’’. They reach the interesting conclusion that, because the temperature dependence of the growth rate of heterotrophic protists is much stronger than that of autotrophic protists, the growth rates of algal grazers will be much lower than that of their prey when water temperatures are low. They conclude that this reduced predator growth will result in a lower grazing pressure, allowing frequent algal blooms to develop in polar regions. Most importantly, they speculate that this difference in the temperature dependence of heterotrophic and autotrophic growth might be due to their differing metabolic pathways. Here I try to link their results to the metabolic theory of ecology (MTE) (Brown et al. 2004), and I argue that the conclusion of Rose and Caron (2007) is very similar to one of the predictions of MTE. MTE predicts a different temperature dependence for heterotrophic processes (mostly driven by adenosine triphosphate synthesis) and autotrophic rates (controlled by Rubisco carboxylation) (Allen et al. 2005). To describe the effects of temperature on metabolic processes, MTE uses the Van’t Hoff–Arrhenius equation (Arrhenius 1915), closely related to Boltzmann’s factor (Gillooly et al. 2001, 2002; Brown et al. 2004; Allen et al. 2005):
Multiple defaults and contagion risks

We study multiple defaults where the global market information is modelled as progressive enlargement of filtrations. We shall provide a general pricing formula by establishing a relationship between the enlarged filtration and the reference default-free filtration in the random measure framework. On each default scenario, the formula can be interpreted as a Radon-Nikodym derivative of random measures. The contagion risks are studied in the multi-defaults setting where we consider the optimal investment problem in a contagion risk model and show that the optimization can be effectuated in a recursive manner with respect to the default-free filtration.
Prolonged feeding with guanidinoacetate, a methyl group consumer, exacerbates ethanol-induced liver injury

AIM To investigate the hypothesis that exposure to guanidinoacetate (GAA, a potent methyl-group consumer) either alone or combined with ethanol intake for a prolonged period of time would cause more advanced liver pathology thus identifying methylation defects as the initiator and stimulator for progressive liver damage. METHODS Adult male Wistar rats were fed the control or ethanol Lieber DeCarli diet in the absence or presence of GAA supplementation. At the end of 6 wk of the feeding regimen, various biochemical and histological analyses were conducted. RESULTS Contrary to our expectations, we observed that GAA treatment alone resulted in a histologically normal liver without evidence of hepatosteatosis despite persistence of some abnormal biochemical parameters. This protection could result from the generation of creatine from the ingested GAA. Ethanol treatment for 6 wk exhibited changes in liver methionine metabolism and persistence of histological and biochemical defects as reported before. Further, when the rats were fed the GAA-supplemented ethanol diet, similar histological and biochemical changes as observed after 2 wk of combined treatment, including inflammation, macro- and micro-vesicular steatosis and a marked decrease in the methylation index were noted. In addition, rats on the combined treatment exhibited increased liver toxicity and even early fibrotic changes in a subset of animals in this group. The worsening liver pathology could be related to the profound reduction in the hepatic methylation index, an increased accumulation of GAA and the inability of creatine generated to exert its hepato-protective effects in the setting of ethanol. CONCLUSION To conclude, prolonged exposure to a methyl consumer superimposed on chronic ethanol consumption causes persistent and pronounced liver damage.
Traffic Estimation in Mobile Ad Hoc Network Using Probe Packets

This paper presents a new method for estimating of traffic in mobile ad hoc by using probe packets. Probing based approaches involves sending test transactions over the network to monitor the path and performance of network. These test transactions are called probes. Probes are used to monitor a wide array of performance parameters including delay, loss, available bandwidth, traffic composition, routing behavior. It relies on Self-induced congestion, and repeatedly samples of traffic in network path with sequence of probe packets, Send randomized rates. This method requires little computation at each iteration, and add small of probe traffic. It maintains current estimates, which is incrementally improved with each new measurement with each new measurement of inter packet time separation in sequence of probe packet pairs and also provide quality of service by transferring data on path with best available bandwidth. We compare the performance of traffic estimation with that of Ad-Hoc Distance Vector Routing Protocol in OMNET 3.3 network simulators.
Working through Walls: Mediating Cooperation in Dynamic Spaces

An important part of supporting cooperative work is to support the work rather than becoming an obstacle between the people and their task. We are striving to achieve this kind of invisible support by developing systems that provide interaction via modalities other than keyboard and mouse. We present two prototype systems that we have developed that use speech and pen based interaction. One system—OfficeMATE— provides portable connections to embedded data to help a visitor interact more successfully in a new environment. The other system—EMCE—provides meeting support that includes both the more obvious collaborative support within a meeting as well as external support to link to the user’s stationary desktop machine. OfficeMATE can also act within the EMCE environment as a more personalised access to the meeting. We feel that OfficeMATE and EMCE are both examples of computer supported cooperative work (CSCW) systems that encourage a seamless transition between desktop and meeting.