Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Foodie Segmentation

Previous research studies have explored the activities, motivations, and outcomes for the culinary tourist, and researchers have theorized certain segments of culinary travelers (Boniface, 2003; Mitchell, Hall & McIntosh, 2000). Contrasting to this, investigation into “the foodie” and his or her activities at home has been strikingly infrequent. Exploring the foodie ‘at home’ or the foodie’s everyday behavior is critical to understanding different types of foodies, how to market to foodies, and their decision-making processes for culinary travel. The purpose of this study is to test, via an online survey, a scale that distinguishes between different types of foodies, and determine if their home-foodie habits are the same while traveling. The study includes five samples: all of the populations were selected to attempt to get a variety of respondents; some settings were food-focused and some were not. Factor analysis was used to group like respondents together; factors that overlapped across samples includes Sustainable Food Activist, Cooking, Cooking Competitor/Do-It-Yourself, Trendy Traveler, Gardening, and Drinking activity dimensions. Food-related businesses and tourism marketers would benefit from greater distinction between types of foodies so as to develop and market specific products to them, to create new packages with complementary activities, and to convert ‘crossover’ markets who visit for one reason but who could be convinced to ‘cross over’ to participate in other activities.
Computation of densities and fluxes of nonlinear differential‐difference equations

Direct methods to find conserved densities and fluxes of differential‐difference equations are presented and illustrated for the Kac‐van Moerbeke (KvM) and modified Volterra lattices. A Miura map which connects both lattices is explicitly constructed based on homotopic deformation. The map is used recursively to compute conserved densities of the KvM lattice. The algorithms presented could be implemented in computer algebra systems and could be used to investigate the integrability of semi‐discrete lattices.
Diving into the Unknown World of Soft Substrate Snails Students :

Current knowledge of soft substrate gastropod assemblages of Lake Tanganyika is extremely limited compared to our knowledge of the lake’s rocky substrate assemblages. Literature regarding Lake Tanganyika’s soft substrate gastropod species is restricted to two studies and a Lake Tanganyika gastropod diagnostic field guide (West et al. 2003). The soft substrate molluscan studies include a preliminary Nyanza Project, which examined the distribution of soft substrate molluscs with changing bathymetry off the Luiche platform (Kinyanjui 2002) and a paper that examined the affects of sediment disturbance on aquatic animal biodiversity, including four soft substrate gastropod species (Alin et al. 1999). This paper examines two separate aspects of a paired stream comparison with an underlying goal to document and better the current understanding of living soft substrate gastropod communities of Lake Tanganyika.
On the Formulation of Characteristic Mode Theory With Fast Multipole Algorithms

To enhance the capability of the characteristic mode analysis (CMA) for electrically large problems, fast multipole algorithms (FMAs) are incorporated into this increasingly popular technique in antenna community. In this communication, an improvement formulation of CMA with FMAs is presented and studied. Numerical results show that the proposed formulation has a better convergence behavior than the previous formulation when it is used for electrically large antenna platforms.
Gradient-Based Multi-Objective Feature Selection for Gait Mode Recognition of Transfemoral Amputees

One control challenge in prosthetic legs is seamless transition from one gait mode to another. User intent recognition (UIR) is a high-level controller that tells a low-level controller to switch to the identified activity mode, depending on the user’s intent and environment. We propose a new framework to design an optimal UIR system with simultaneous maximum performance and minimum complexity for gait mode recognition. We use multi-objective optimization (MOO) to find an optimal feature subset that creates a trade-off between these two conflicting objectives. The main contribution of this paper is two-fold: (1) a new gradient-based multi-objective feature selection (GMOFS) method for optimal UIR design; and (2) the application of advanced evolutionary MOO methods for UIR. GMOFS is an embedded method that simultaneously performs feature selection and classification by incorporating an elastic net in multilayer perceptron neural network training. Experimental data are collected from six subjects, including three able-bodied subjects and three transfemoral amputees. We implement GMOFS and four variants of multi-objective biogeography-based optimization (MOBBO) for optimal feature subset selection, and we compare their performances using normalized hypervolume and relative coverage. GMOFS demonstrates competitive performance compared to the four MOBBO methods. We achieve a mean classification accuracy of 97.14%±1.51% and 98.45%±1.22% with the optimal selected subset for able-bodied and amputee subjects, respectively, while using only 23% of the available features. Results thus indicate the potential of advanced optimization methods to simultaneously achieve accurate, reliable, and compact UIR for locomotion mode detection of lower-limb amputees with prostheses.
Using Public Engagements to Provide Input and Insights into Policy, Legal, Ethical, and Other Impacts of Science

Fueled in part by governmental regulatory requirements and in part because of science’s own interest, public engagements are used to provide input about the policy, ethical, legal, social, and other impacts of science and technology. While public engagements show promise for ensuring that public values are incorporated into science and technology policy, current models of public engagement are disconnected from empirical evidence, are too general to guide decisions about public engagement in specific contexts or for specific purposes, and fail to adequately explain why public engagement outcomes differ across studies. In this paper we briefly review prior models, as well as an approach to building new models that we are currently employing in our research. We describe preliminary results from an experimental study conducted using our approach, which varies the cognitive goals emphasized by an engagement concerning nanotechnology, and the social context for giving input. Results suggest that variations in these factors do matter: Compared to individual input, group discussion of input questions resulted in less-focused, less argumentative, and more active and selfregulated forms of engagement; and emphasis on cognitive learning goals did appear to support learning to a greater extent than emphasis on critical thinking goals. We conclude that future experimental research is warranted and necessary to populate a social science of public engagement with models that answer questions of which public engagements work under what conditions, for what purposes, and why.
The Economic Dilution of Employee Stock Options: Diluted Eps for Valuation and Financial Reporting

In this paper, we derive a measure of diluted EPS that incorporates the economic implications of the dilutive effects of employee stock options. We show that the existing FASB treasury‐stock method of accounting for the dilutive effects of outstanding options systematically understates the options' dilutive effect, and thus overstates reported EPS. Using firm‐wide data on 731 employee stock option plans, our proposed measure suggests that economic dilution from options is, on average, 100 percent greater than dilution in reported diluted EPS using the FASB treasury‐stock method. We examine the implications of our analysis for stock price valuation, the price‐earnings relation, and the return‐earnings relation. We demonstrate analytically that when firms have options outstanding, empirical applications of equity valuation models that use reported per‐share earnings as an input (e.g., Ohlson 1995) yield upwardly biased estimates of the market value of common stock. We predict that when the difference betwee.
Response of Pacific Loons (Gavia pacifica) to Impoundments at Prudhoe Bay, Alaska

Reproductive success and foraging effort of Pacific loons ( Gavia pacifica ) were compared between impoundments and natural ponds in the Prudhoe Bay oil field, Alaska, in 1992 and 1993. Pacific loons successfully reproduced on both impoundments and ponds. Though success tended to be lower on impoundments, no significant differences were detected between the two water body types. The principal cause of reproductive failure on both impoundments and ponds in 1993 appears to have been predation by arctic foxes ( Alopex lagopus ) during incubation. Predation losses on impoundments often were associated with large water-level drawdowns, which apparently increased opportunities for predation of stranded clutches. I found no differences in chick mortality or adult foraging effort between impoundments and ponds. Over 99% of the prey items delivered to chicks were invertebrates captured in freshwater wetlands. Reproductive output of Pacific loons may be improved by increasing the stability of water levels at impoundments used for nesting. I found no evidence that draining impoundments would improve habitat for loons (or invertebrate-eating waterfowl species) at Prudhoe Bay. Key words: Pacific loon, Gavia pacifica , Prudhoe Bay, impoundments, impact assessment, Alaska
Dropping out of high school in Cyprus: do parents and the family matter?

This paper presents a comparison of family circumstances, aspirations and school involvement of parents in Cyprus whose children were at risk of dropping out of high school and parents whose children were not at risk. The data were collected through a questionnaire survey constructed within the framework of the European project Drop-Out Open Door. The results showed a broad range of differences in the resources, expectations, perceptions and practices of pupils' families who are at risk of dropping out of school and those who are not. The findings illustrate the necessity for schools to identify families' different circumstances and needs and provide them, especially those with pupils at risk, with facilities, support and training for enhancing their children's development and school success through everyday family practices.
Welfare Effects of Housing Transaction Taxes: A Quantitative Analysis with an Assignment Model

We evaluate the welfare cost of housing transaction taxes with a new assignment model based framework, where welfare effects are driven by distortions in the matching of houses and households. We calibrate the model with data from the Helsinki metropolitan region to assess the impact of a reform where an ad valorem transaction tax is replaced with a revenue equivalent property tax. The aggregate welfare gain from this reform increases rapidly with the initial transaction tax rate, with the Laffer curve peaking at about 10%. The proportion of households that lose out from the reform is nevertheless increasing in the tax rate. We compare our model-based counterfactual aggregate welfare results with welfare calculations based on reduced-form estimates from previous policy evaluation studies; they are broadly in line, despite the latter using data from different housing markets at various levels and changes of the tax rate.
From Discursive Practice to Logic? Remarks on Brandom’s LogicalExpressivism

This paper investigates Robert Brandom's programme of logical expressivism and in the process attempts to clarify his use of the term practice, by means of a comparison with the works of sociologist and anthropologist Pierre Bourdieu. The key claim of logical expressivisim is the idea that logical terms serve to make explicit the inferential relations between statements which already hold implicitly in a discursive practice that lacks such terms in its vocabulary. Along with this, it is claimed that the formal validity of an argument is derivative on so-called material inference, in that an inference is taken to be logically valid only if it is a materially good inference and cannot be made into a bad inference by substituting nonlogical for nonlogical vocabulary in its premises and conclusion. We note that no systematic account of logical validity employing this substitutional method has been offered to date; rather, proposals by e.g. Lance and Kremer, Piwek, Kibble and Brandom himself have followed the more conventional path of developing a formally defined system which is informally associated with natural language examples. We suggest a number of refinements to Brandom’s account of conditionals and of validity, supported by analysis of linguistic examples including material from the SNLI and MultiNLI corpora and a review of relevant literature. The analysis suggests that Brandom’s expressivist programme faces formidable challenges once exposed to a wide range of linguistic data, and may not in fact be realisable owing to the pervasive context-dependence of linguistic expressions, including 'logical' vocabulary. A further claim of this paper is that a purely assertional practice may not provide an adequate basis for conditional reasoning, but that a more promising route is provided by the introduction of imperatives, as in so-called "pseudo-imperatives" such as "Get individuals to invest their time and the funding will follow". We conclude the resulting dialogical analysis of conditional reasoning is faithful to Brandom's Sellarsian intuition of linguistic practice as a game of giving and asking for reasons, and conjecture that language is best analysed not as a system of rules but as a Wittgensteinian repertoire of evolving micro-practices.
Probing Protein Folding Dynamics Using Multivariate Statistical Techniques

Abstract Abstract The study of protein folding and its ramifications in biological contexts is at the heart of computational biology. In this paper, we discuss a number of tools in systems engineering that would provide an analysis framework to help explain the observed dynamic behavior of the protein, ultimately making the connection between protein structure and functionality. A case study of villin headpiece folding using principal components analysis as well as clustering demonstrates the potential of these tools in responding to this challenge.
When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators

The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of nine improved covariance estimation procedures using daily returns of 90 highly capitalized US stocks for the period 1997–2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between the estimation period T and the number of stocks N, on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than that obtained with the sample covariance method. This is particularly true when T/N is close to one. Moreover, many estimators reduce the fraction of negative portfolio weights, while little improvement is achieved in the degree of diversification. On the contrary, when short selling is not allowed and T > N, the considered methods are unable to outperform the sample covariance in terms of realized risk, but can give much more diversified portfolios than that obtained with the sample covariance. When T < N, the use of the sample covariance matrix and of the pseudo-inverse gives portfolios with very poor performance.
Aggregate Fluctuations and International Migration

Traditional theories of integration such as the optimum currency area approach attribute a prominent role to international labour mobility in coping with relative economic fluctuations between countries. However, recent studies on international migration have overlooked the role of short-run factors in explaining international migration flows. This paper aims to fill that gap. We first derive a model of optimal migration choice based on an extension of the traditional Random Utility Model. Our model predicts that an improvement in the economic activity in a potential destination country relative to any origin country may trigger some additional migration flows on top of the impact exerted by long-run factors such as the wage differential or the bilateral distance. Compiling a dataset with annual gross migration flows between 30 developed origin and destination countries over the 1980-2010 period, we empirically test the magnitude of the effect of short-run factors on bilateral flows. Our econometric results indicate that relative aggregate fluctuations and employment rates affect the intensity of bilateral migration flows. We also provide compelling evidence that the Schengen agreements and the introduction of the euro significantly raised the international mobility of workers between the member countries.
Hidden Features: Experiments with Feature Transfer for Fine-Grained Multi-Class and One-Class Image Categorization

Can we apply out-of-the box feature transfer using pre-trained convolutional neural networks in fine-grained multiclass image categorization tasks? What is the effect of (a) domain-specific fine-tuning and (b) a special-purpose network architecture designed and trained specifically for the target domain? How do these approaches perform in one-class classification? We investigate these questions by tackling two biological object recognition tasks: classification of “cryptic” plants of genus Coprosma and identification of New Zealand moth species. We compare results based on out-of-the-box features extracted using a pre-trained state-of-the-art network to those obtained by fine-tuning to the target domain, and also evaluate features learned using a simple Siamese network trained only on data from the target domain. For each extracted feature set, we test a number of classifiers, e.g., support vector machines. In addition to multiclass classification, we also consider one-class classification, a scenario that is particularly relevant to biosecurity applications. In the multi-class setting, we find that out-of-the-box low-level features extracted from the generic pre-trained network yield high accuracy $(90.76\%)$ when coupled with a simple LDA classifier. Fine-tuning improves accuracy only slightly (to $91.6\%)$. Interestingly, features extracted from the much simpler Siamese network trained on data from the target domain lead to comparable results (90.8%). In the one-class classification setting, we note high variability in the area under the ROC curve across feature sets, opening up the possibility of considering an ensemble approach.
Measurement of the Young's modulus and shear modulus of in-plane quasi-isotropic medium-density fiberboard by flexural vibration

The Young’s modulus and the in-plane shear modulus of medium-density fiberboard (MDF) were obtained by conducting a flexural vibration test under the free-free condition based on Timoshenko’s vibration theory using specimens with various depth/length ratios and performing a subsequent numerical analysis. The results obtained by the experiment and numerical analysis revealed that the Young’s modulus was independent of the specimen configuration. In contrast, the in-plane shear modulus was significantly dependent on the specimen configuration and could not be measured properly based on Timoshenko’s theory when the specimen had a small depth/length ratio. The numerical analysis also revealed that the Poisson’s ratio has a significant influence on the measurement of shear modulus as well as the specimen configuration. A statistical analysis on the results experimentally obtained suggested that the length of the specimen must be less than 7.5 times the depth to measure the in-plane shear modulus appropriately.
Genetic Population Structure and Cryptic Speciation of Ghost Shrimp (Neotrypaea californiensis) in North American West Coast Estuaries

GENETIC POPULATION STRUCTURE AND CRYPTIC SPECIATION OF GHOST SHRIMP (NEOTRYPAEA CALIFORNIENSIS) IN NORTH AMERICAN WEST COAST ESTUARIES by Daphne A. Gille Many marine species produce larvae that disperse and develop into post-larvae in the open ocean over a period of weeks to months. However, the patterns and potential of larvae to disperse across long geographic distances are poorly understood. Here genetic variation found at the mitochondrial locus, cytochrome C oxidase subunit I, in adult ghost shrimp, Neotrypaea californiensis, was used as a proxy to infer dispersal potential of ghost shrimp larvae found in estuaries along the west coast of the United States. Multiple haplotypes were shared among 346 adult ghost shrimp specimens collected from estuaries in Washington, Oregon, and California indicated that larvae of this species are transported across great distances during the pelagic dispersal phase of development. Interestingly, extreme population structure (FST ranged from 0.062 to 0.98) was observed among sampling sites located in close proximity to one another. Phylogenetic analyses and analysis of molecular variance revealed that the cause of population structure was in part attributed to the presence of three putative cryptic species that were deeply divergent from N. californiensis. Qualitative and quantitative morphological measurements commonly employed for shrimp species identification were inconsistent among putative cryptic species groups but did show that the newly identified cryptic species were not undiagnosed individuals of the closest relative of N. californiensis, N. gigas.
Evolution and inheritance of a rock coast: western Galicia, northwestern Spain

There is increasing evidence that shore platforms and other elements of rock coasts may be inherited, at least in part, from interglacial stages when sea level was similar to today's. Most of this evidence, which includes ancient beaches and datable terrestrial deposits, has been obtained from areas of resistant, slowly eroding rock, where the platforms often appear to be much too wide to have developed since the sea reached its present level. It is much more difﬁcult to demonstrate that inheritance has occurred in areas of weaker rock, which generally lack any datable material. The coast of western Galicia in northwestern Spain has shore platforms in igneous and metamorphic rocks that were deeply weathered during the Tertiary. These platforms are closely associated with ancient beaches from the last interglacial stage, and associated periglacial and ﬂuvio‐nival deposits that covered and fossilized most of the Eemian platforms and cliffs during the late middle and late Weichselian glacial stage. The sedimentary processes and the thickness and facies of the sediments were determined by the height, aspect and gradient of the coastal mountains, and their distance from the coast. Radiocarbon dating, sedimentary analysis and platform morphology indicate that the shore platforms of Galicia have been inherited from at least the last interglacial stage. They were fossilized in places beneath thick Weichselian deposits and then exhumed during the Holocene transgression. The abundant evidence for inheritance in Galicia has important implications for other coasts in fairly weak rocks where such evidence is generally lacking. Copyright © 2003 John Wiley & Sons, Ltd.