Miracle-dz/UniFAR-FTUs huggingface dataset:
DOI:10.1068/a3684 Industrial agglomerations as localised networks: the case of the Portuguese injection mould industry

Despite the growth in transport and communication infrastructure and the possibilities it has opened, there has been a renewed interest in industrial agglomerations or the spatial clustering of firms operating in the same or closely related industries. The vast literature on the subject has emphasised almost obsessively as Hudson (1999) notes, access to and generation of knowledge when firms are spatially close to each other Although some previously important locational factors have been converted into ubiquities, industrial agglomerations seem to maintain a role as enablers of learning processes, and this may help explain the decisions of firms to locate themselves in specific territories (Dupuy and Gilly, 1999). Maskell and Malmberg (1999a, page 168) go as far as arguing that thè`knowledge creation of even the most globally oriented firms or sector is, at least to some extent, influenced by differences in the economic properties of their place of location. '' The relevance of these localised capabilities is often approached through the notion of the territory as``an historically constituted set of inter-linked economic activities [R&D, design, manufacturing, commercialisation] coordinated in a variety of ways by firms, research centres and other economic agencies and by local governments and other such socio-political institutions'' (Dupuy and Gilly, 1999, page 208). According to Lawson (1999), the diverse literatures on industrial agglomerations converge in associating the benefits of agglomerations to the emergence of connections between local actors. These benefits, encompassing both the productivity and the
Neighborhood Watch: Stochastic Gradient Descent with Neighbors

Stochastic Gradient Descent (SGD) is a workhorse in machine learning, yet it is also known to be slow relative to steepest descent. The variance in the stochastic update directions only allows for sublinear or (with iterate averaging) linear convergence rates. Recently, variance reduction techniques such as SVRG and SAGA have been proposed to overcome this weakness. With asymptotically vanishing variance, a constant step size can be maintained, resulting in geometric convergence rates. However, these methods are either based on occasional computations of full gradients at pivot points (SVRG), or on keeping per data point corrections in memory (SAGA). This has the disadvantage that one cannot employ these methods in a streaming setting and that speed-ups relative to SGD may need a certain number of epochs in order to materialize. This paper investigates a new class of algorithms that can exploit neighborhood structure in the training data to share and re-use information about past stochastic gradients across data points. While not meant to be offering advantages in an asymptotic setting, there are significant benefits in the transient optimization phase, in particular in a streaming or singleepoch setting. We investigate this family of algorithms in a thorough analysis and show supporting experimental results. As a side-product we provide a simple and unified proof technique for a broad class of variance reduction algorithms.
Trust Among the Avatars: A Virtual World Experiment, With and Without Textual and Visual Cues

We invited "residents" of a virtual world who vary in real-world age and occupation to play a trust game with stakes comparable to "in-world" wages. In different treatments, the lab wall was adorned with an emotively suggestive photograph, a suggestive text was added to the instructions, or both a photo and text were added. We find high levels of trust and reciprocity that appear still higher for non-student and older subjects. Variation of results by treatment suggests that both photographic and textual cues influenced the level of trust but not that of trustworthiness.
Intimacy and Belonging

There is a paucity of systematic analysis of the relation between sexual activity and mental health. To address this gap, we ask whether sexual activity associates with lower levels of depression among older adults. We hypothesize that sexual activity—especially if it typically incorporates other forms of physical affection—may be a socially meaningful activity and may create intimacy that provides social uplift. We test this hypothesis against alternative hypotheses that relationship characteristics or physical health could account for any association between sex and depression. In addition, we consider whether there are gender dynamics that affect the association between sexual activity and depression. We analyze data from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative survey of adults aged 57 to 85. Given findings of significant gendered aspects of depression, sexual activity, social support, and aging, we estimate separate models for women and men. Although we find differences between models for men and women for many control variables that correspond to gendered differences in depression, sexual activity that typically incorporates other forms of physical intimacy has a robust association with lower depression for both women and men.
00 04 34 6 v 1 2 5 A pr 2 00 0 Cluster Populations in A 115 and A 2283

This paper presents four color narrow-band photometry of clusters A115 (z = 0.191) and A2283 (z = 0.182) in order to follow the star formation history of various galaxy types. Although located at similar redshifts, the two clusters display very different fractions of blue galaxies (i.e. the Butcher-Oemler effect, fB = 0.13 for A115, fB = 0.30 for A2283). A system of photometric classification is applied to the cluster members that divides the cluster population into four classes based on their recent levels of star formation. It is shown that the blue population of each cluster is primarily composed of normal starforming (SFR < 1M⊙ yrs ) galaxies at the high luminosity end, but with an increasing contribution from a dwarf starburst population below M5500 = −20. This dwarf starburst population appears to be the same population of low mass galaxies identified in recent HST imaging (Koo et al. 1997), possible progenitors to present-day cluster dwarf ellipticals, irregulars and BCD’s. Deviations in the color-magnitude relationship for the red galaxies in each cluster suggest that a population of blue S0’s is evolving into present-day S0 colors at this epoch. The radial distribution of the blue population supports the prediction of galaxy harassment mechanisms for tidally induced star formation operating on an infalling set of gas-rich galaxies.
Old flies have a robust central oscillator but weaker behavioral rhythms that can be improved by genetic and environmental manipulations

Sleep–wake cycles break down with age, but the causes of this degeneration are not clear. Using a Drosophila model, we addressed the contribution of circadian mechanisms to this age‐induced deterioration. We found that in old flies, free‐running circadian rhythms (behavioral rhythms assayed in constant darkness) have a longer period and an unstable phase before they eventually degenerate. Surprisingly, rhythms are weaker in light–dark cycles and the circadian‐regulated morning peak of activity is diminished under these conditions. On a molecular level, aging results in reduced amplitude of circadian clock gene expression in peripheral tissues. However, oscillations of the clock protein PERIOD (PER) are robust and synchronized among different clock neurons, even in very old, arrhythmic flies. To improve rhythms in old flies, we manipulated environmental conditions, which can have direct effects on behavior, and also tested a role for molecules that act downstream of the clock. Coupling temperature cycles with a light–dark schedule or reducing expression of protein kinase A (PKA) improved behavioral rhythms and consolidated sleep. Our data demonstrate that a robust molecular timekeeping mechanism persists in the central pacemaker of aged flies, and reducing PKA can strengthen behavioral rhythms.
Computational Assessment of Text Readability: A Survey of Current and Future Research Running title: Computational Assessment of Text Readability

Assessing text readability is a time-honored problem that has even more relevance in today’s information-rich world. This article provides background on how readability of texts is assessed automatically, reviews the current state-of-the-art algorithms in automatic modeling and predicting the reading difficulty of texts, and proposes new challenges and opportunities for future exploration not well-covered by current computational research.
Probable changes in lake chemistry in Canada’s Atlantic Provinces under proposed North American emission reductions

Abstract. Atlantic Canada, located in the extreme north-eastern portion of North America, receives acid precipitation from all major acid emission sources on the eastern part of the continent. The region was glaciated and has thin soils over a generally poorly acid buffering bedrock. Because of regional topography, large groupings of lakes occur in a number of regions. Environment Canada and the Government of New Brunswick have operated lake sampling networks in trend detection studies and have concentrated their work on these lake groupings. The MAGIC model has been applied to these lakes and their catchments to see: a) what initial water chemistry conditions existed before acidification began, b) what the chemistry was like during the worst of regional acid deposition, and c) what it would be like under deposition conditions predicted for new Canadian and US emission reduction proposals. While pH, sulphate, acid neutralisation capacity (ANC) and the sum of the base cations (SBC) of all lakes have been significantly affected by acid deposition, water chemistry conditions are now considerably better than they were in 1975, at the worst of the deposition. However, a 50% reduction in acid deposition from Year 2000 deposition amounts will not return water chemistry to original conditions in most of the region. Keywords: Atlantic Canada, monitoring networks, acidification, predictions, MAGIC
Marginal deformations in string field theory

We describe a method for obtaining analytic solutions corresponding to exact marginal deformations in open bosonic string field theory. For the photon marginal defor- mation we have an explicit analytic solution to all orders. Our construction is based on a pure gauge solution where the gauge field is not in the Hilbert space. We show that the solution itself is nevertheless perfectly regular. We study its gauge transformations and cal- culate some coefficients explicitly. Finally, we discuss howour method can be implemented for other marginal deformations.
Axon Regeneration Genes Identified by RNAi Screening in C. elegans

Axons of the mammalian CNS lose the ability to regenerate soon after development due to both an inhibitory CNS environment and the loss of cell-intrinsic factors necessary for regeneration. The complex molecular events required for robust regeneration of mature neurons are not fully understood, particularly in vivo. To identify genes affecting axon regeneration in Caenorhabditis elegans, we performed both an RNAi-based screen for defective motor axon regeneration in unc-70/β-spectrin mutants and a candidate gene screen. From these screens, we identified at least 50 conserved genes with growth-promoting or growth-inhibiting functions. Through our analysis of mutants, we shed new light on certain aspects of regeneration, including the role of β-spectrin and membrane dynamics, the antagonistic activity of MAP kinase signaling pathways, and the role of stress in promoting axon regeneration. Many gene candidates had not previously been associated with axon regeneration and implicate new pathways of interest for therapeutic intervention.
Domain ontology based object-oriented and relational databases

The paper describes incorporation of ontology in database of decision support system. Implementation of persistent knowledge-base can be done using relational as well as object-oriented database. Creation of database schema according to classes with their specific properties and slots of domain ontology is described for both types of databases. Besides the database maintenance problems, various possibilities of database reasoning are shortly described.
Software Assurance Metrics and Tool Evaluation

The U.S. National Institute of Standards and Technology (NIST) is starting two ambitious projects to (1) develop a taxonomy of software security flaws and vulnerabilities, (2) develop a taxonomy of software assurance (SA) functions and techniques which detect those flaws, (3) perform and maintain a survey of SA tools implementing the functions, (4) develop testable specifications of SA functions and explicit tests, include a standard reference dataset, to evaluate how closely tools implement the functions, and (5) lead efforts to develop metrics for the effectiveness of those functions. The end result is that users will be able to choose a combination of techniques which best suits their needs and will be able to state how much confidence they have in software which has been assessed. This paper details these two projects and presents our justifications and expectations.
Gender-Dependent Effect of GSTM1 Genotype on Childhood Asthma Associated with Prenatal Tobacco Smoke Exposure

It remains unclear whether the GSTM1 genotype interacts with tobacco smoke exposure (TSE) in asthma development. This study aimed to investigate the interactions among GSTM1 genotype, gender, and prenatal TSE with regard to childhood asthma development. In a longitudinal birth cohort in Taiwan, 756 newborns completed a 6-year follow-up, and 591 children with DNA samples available for GSTM1 genotyping were included in the study, and the interactive influences of gender-GSTM1 genotyping-prenatal TSE on childhood asthma development were analyzed. Among these 591 children, 138 (23.4%) had physician-diagnosed asthma at 6 years of age, and 347 (58.7%) were null-GSTM1. Prenatal TSE significantly increased the prevalence of childhood asthma in null-GSTM1 children relative to those with positive GSTM1. Further analysis showed that prenatal TSE significantly increased the risk of childhood asthma in girls with null-GSTM1. Furthermore, among the children without prenatal TSE, girls with null-GSTM1 had a significantly lower risk of developing childhood asthma and a lower total IgE level at 6 years of age than those with positive GSTM1. This study demonstrates that the GSTM1 null genotype presents a protective effect against asthma development in girls, but the risk of asthma development increases significantly under prenatal TSE.
Contracts: specifying behavioral compositions in object-oriented systems

Behavioral compositions, groups of interdependent objects cooperating to accomplish tasks, are an important feature of object-oriented systems. This paper introduces Contracts, a new technique for specifying behavioral compositions and the obligations on participating objects. Refinement and composition of contracts allows for the creation of large grain abstractions based on behavior, orthogonal to those provided by existing class constructs. Using contracts thus provides a basis and vocabulary for Interaction-Oriented design which greatly facilitates the early identification, abstraction and reuse of patterns of behavior in programs. Contracts differ from previous work in that they capture explicitly and abstractly the behavioral dependencies amongst cooperating objects. By explicitly stating these dependencies, contract also provide an effective aid for program understanding and reuse.
Knowledge-based person-centric human-robot interaction using facial and hand gestures

This paper presents a knowledge-based person-centric human-robot interaction system using facial and hand gestures. In the proposed method, face detection and person identification are first made. With the knowledge of the known user face and hand poses are then classified from the later image frame by the subspace method and the gestures are finally recognized. The rules for interpreting the gestures are selected according to each specific user recognized by the facial image. The user's name and gesture commands are sent to the robot through a Software Platform for Agent and Knowledge Management (SPAK) to implement person-centric human-robot interaction. The effectiveness of this method has been demonstrated by interacting with a humanoid robot Robovie.
Noise Removal Algorithm for Polygonal Meshes ∗

In this paper, we present an effective unshrinkage noise removal algorithm to generate smooth geometric models. By introducing the constraints of keeping all triangle barycenters invariant at each smoothing step, the algorithm converts the mesh fairing issue into the minimization of the constrained energy minimization functional, which is then solved efficiently by our iterative method. The experimental results demonstrate that our algorithm can not only quickly remove the noise with good shape preservation, but also be implemented efficiently and robustly.
Hybridizing evolutionary algorithms for creating classifier ensembles

Genetic programming (GP) has been applied to solve data classification problems numerous times in previous studies and the findings in the literature confirm that GP is able to perform well. In more recent studies, researchers have shown that using a team of classifiers can outperform a single classifier. These teams are referred to as ensembles. Previously, several different attempts at creating ensembles have been investigated; some more complex than others. In this study, four approaches have been proposed, in which the ensemble methods hybridize a genetic algorithm with a GP algorithm in different ways. The first three approaches made use of a generational GP model, while the fourth used a steady state GP model. The four approaches were tested on eight public data sets and the findings confirm that the proposed ensembles outperform the standard GP method, and additionally outperform other GP methods found in literature.
Retail Store Execution: An Empirical Study

We describe a methodology by which a retailer can identify action steps that are likely to increase sales and customer satisfaction and demonstrate the methodology using proprietary data from a large retailer with over 500 stores. We use monthly store-level data on a number of operational variables including in-stock rate, store staffing level as measured by payroll and store employee turnover, together with customer responses to satisfaction surveys. We develop a nested three-stage econometric model to analyze the marginal effects of various execution levers on sales, customer satisfaction and the percentage of customers who answer ‘yes’ to the question ‘Did you find everything you were looking for? ’, which we term customer perceived in-stock. Our model explains approximately 75%, 97% and 71%, respectively, of the residual variation in sales, customer satisfaction, and customer perceived in-stock. We find that customer perceived in-stock is primarily driven by actual in-stock and customer rating of employee knowledge; overall customer satisfaction is primarily driven by customer perceived in-stock, payroll level, customer rating of employee knowledge and check-out efficiency; and sales is primarily driven by actual in-stock, overall satisfaction and payroll level. Finally, we estimate relative magnitudes of these effects, propose specific actions to improve sales and estimate the likely sales increase from those actions. Our results suggest that a modest reallocation of the payroll budget among stores could be expected to yield a 2-3% increase in sales with no increase in cost.
A Review of Caveats in Statistical Nuclear Image Analysis

A large body of the published literature in nuclear image analysis do not evaluate their findings on an independent data set. Hence, if several features are evaluated on a limited data set over‐optimistic results are easily achieved. In order to find features that separate different outcome classes of interest, statistical evaluation of the nuclear features must be performed. Furthermore, to classify an unknown sample using image analysis, a classification rule must be designed and evaluated. Unfortunately, statistical evaluation methods used in the literature of nuclear image analysis are often inappropriate. The present article discusses some of the difficulties in statistical evaluation of nuclear image analysis, and a study of cervical cancer is presented in order to illustrate the problems. In conclusion, some of the most severe errors in nuclear image analysis occur in analysis of a large feature set, including few patients, without confirming the results on an independent data set. To select features, Bonferroni correction for multiple test is recommended, together with a standard feature set selection method. Furthermore, we consider that the minimum requirement of performing statistical evaluation in nuclear image analysis is confirmation of the results on an independent data set. We suggest that a consensus of how to perform evaluation of diagnostic and prognostic features is necessary, in order to develop reliable tools for clinical use, based on nuclear image analysis.
boundedness for the Hilbert transform and maximal operator along a class of nonconvex curves

Some sufficient conditions on a real polynomial P and a convex function γ are given in order for the Hilbert transform and maximal operator along (t, P(γ(t))) to be bounded on L p , for all p in (1, ∞), with bounds independent of the coefficients of P. The same conclusion is shown to hold for the corresponding hypersurface in R d+1 (d > 2) under weaker hypotheses on γ.
Estimating limits on colour vision performance in natural scenes

The aim of this work was to estimate some of the basic limits on human colour vision performance over a range of natural scenes. Computational simulations of colour processing were carried out with 50 hyperspectral images of rural and urban scenes under different daylights. Three limits were estimated for each scene: the number of discriminable coloured surfaces under a single daylight, the relative frequency of metamerism across two daylights, and, as a measure of of colour constancy, the mean error in colour matches across two daylights. All three limits were found to vary over scenes by 1–2 orders of magnitude. Some or all of the variation could, however, be explained by a measure of the randomness of the colours in each scene.
Computer Intrusion Detection Based on Bayes Factors for Comparing Command Transition Probabilities

This statistical method can compare in real time the sequence of commands given by each user to a profile of that user’s past behavior. We use a Bayes Factor statistic to test the null hypothesis that the observed command transition probabilities come from a profiled transition matrix. The alternative hypothesis is formed as a Dirichlet mixture of multinomial command probabilities. Based on a population of research users on a single computer, data from some users are inserted into the histories of other users to simulate intrusions. The Bayes factor based on the observation of a block of 100 commands had a false alarm rate of about 6.6% while detecting about 78% of blocks from simulated intrusions. We integrate the test into a detection scheme using control charts.