Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-modal alignment for wildlife recognition

We propose an unsupervised framework for recognizing animals in videos using subtitles. In this framework, the alignment between animals and their names is performed using an Expectation Maximization algorithm which is adapted to two very different circumstances- 1) when the bounding boxes are available and 2) when the frame as a whole is used instead of bounding boxes. With the goal of maximizing precision, recall and F-measure, the experiments compare a multitude of natural language processing approaches and visual features when associating animal names in the subtitles with visual patterns. The proposed unsupervised methods obtain 83.1% F1 using bounding boxes and 65.7% F1 without bounding boxes in a fully automated pipeline.
Wear of polymer composites

Abstract The use of polymers and polymer composites in various tribological situations has become state of the art. Nevertheless, new developments are still under way to explore new fields of application for these materials and to tailor their properties for more extreme loading conditions. Some of these developments can be followed when searching through the 56 references given at the end of this review. The present overview describes, in particular, some of the authors' approaches in designing polymeric composites in order to operate under low friction and low wear against steel counterparts. Special emphasis is focused on thermoplastics and thermosets reinforced with special fillers (including nanoparticles). An attempt is made to predict their wear properties and to carry out systematic parameters studies by the use of artificial neural networks. Further information will be given on the fibre orientation dependence of wear of continuous carbon fibre-polymer matrix composites, and on attempts to predict their load-bearing capacity and related wear mechanisms by the use of finite elements. In addition, some new steps towards the development of functionally graded tribomaterials are illustrated.
Relationship of falls and fear of falling to activity limitations and physical inactivity in Parkinson's disease.

AIM To investigate the relationships between falls, fear of falling, and activity limitations in individuals with Parkinson's disease (PD). DESIGN/METHODS Cross-sectional study of individuals with mild to moderate PD (N = 83). Associations among demographic data, fall frequency, disease severity, motor impairment, ability to perform activities of daily living (ADL), Activities Balance Confidence Scale, Iowa Fatigue Scale, Comorbidity Index, and Physical Activity Scale for Elders were studied. RESULTS Frequent fallers had more ADL limitations than nonfallers (p < .001) and rare fallers (p = .004). Frequent fallers reported a lower percentage of ability to perform ADL than nonfallers (p = .003). Frequent fallers and rare fallers were less physically active than nonfallers (p = .015 and p = .040, respectively). Frequent fallers and rare fallers reported a higher level of fear of falling than nonfallers (p = .031 and p = .009, respectively). CONCLUSIONS Falls and fear of falling were associated with more ADL limitations and less physical activity after adjusting for physical impairments.
Constrained generalized predictive control using relaxation with quadratic penalization

In this paper an iterative algorithm will be derived to find a numerical solution for the generalized predictive control of linear systems with constraints on controlled and manipulated variables. The algorithm uses the relaxation method with quadratic penalization. Conditions are proposed for the convergence of the iterative solution and results of the application to a second order linear system are presented.
Estimating Ambiguity Aversion in a Portfolio Choice Experiment

We report a laboratory experiment that enables us to estimate parametric models of ambiguity aversion at the level of the individual subject. We use two main specifications, a “kinked” specification that nests Maxmin Expected Utility, Choquet Expected Utility, α-Maxmin Expected Utility, and Contraction Expected Utility and a “smooth” specification that nests the various theories referred to collectively as Recursive Expected Utility. Our subjects solved a series of portfolio-choice problems. The assets are Arrow securities corresponding to three states of nature, where the probability of one state is known and the remaining two are ambiguous. The sample exhibits considerable heterogeneity in preferences, as captured by parameter estimates. Nonetheless, there exists a strong tendency to equalize the demands for the securities that pay off in the ambiguous states, a feature more easily accommodated by the kinked specification than by the smooth specification. We also find that a large number of subjects are well described by the ambiguity-neutral Subjective Expected Utility model.
Determinants of inflammatory markers in a bi-ethnic population.

BACKGROUND Inflammation is a common pathophysiological pathway for a number of chronic diseases, and is strongly influenced by sociodemographic factors and lifestyle. Less is known about factors that may influence the inflammatory response in individuals of distinct ethnic backgrounds. Therefore, this study examined the relationship between ethnicity and blood levels of inflammatory markers in a sample of non-smoking church-goers. METHODS In a cross-sectional investigation, 508 men and women (> 35 years old, 62% White, 38% Black) participated in the Biopsychosocial Religion and Health substudy of the Adventist Health Study 2. The contribution of socioeconomic status (education level and difficulty meeting expenses for basic needs) and health covariates (exercise, vegetarian or other type of diet, body mass index, and presence of inflammatory conditions) toward serum levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-alpha) was assessed with linear regression models. Levels of interleukin-10 (IL-10), an anti-inflammatory marker, were also assessed. RESULTS Blacks showed higher levels of CRP and IL-6 than Whites. Controlling for sociodemographic and health variables attenuated the ethnic difference in CRP while IL-6 levels remained higher in Blacks than in Whites (beta = .118; 95% confidence interval = .014-.206; P = .025). Ethnic differences in IL-10 and TNF-alpha were not found. Vegetarian diet was associated with lower CRP levels while exercise frequency was associated with higher IL-10 levels. CONCLUSION Higher susceptibility of Blacks to inflammatory diseases may reflect higher IL-6, which could be important in assessing health disparities among Blacks and Whites. Vegetarian diet and exercise may counteract effects of disparities.
Feature sets for nonstationary signals derived from moments of the singular value decomposition of Cohen-Posch (positive time-frequency) distributions

This article presents a new method for determining the principal features of a nonstationary time series process based on the singular value decomposition (SVD) of the Cohen-Posch (1985) positive time-frequency distribution. This new method uses density functions derived from the SVD singular vectors to generate moments that are associated with the principal features of the nonstationary process. Since the SVD singular vectors are orthonormal, the vectors whose elements are composed of the squared elements of the SVD vectors are discrete density functions. Moments generated from these density functions are the principal features of the nonstationary time series process. The main reason for determining features of a time series process is to characterize it by a few simple descriptors.
A bandwidth-efficient architecture for a streaming media processor

Media processing applications, such as three-dimensional graphics, video compression, and image processing, currently demand 10–100 billion operations per second of sustained computation. Fortunately, hundreds of arithmetic units can easily fit on a modestly sized lcm2 chip in modern VLSI. The challenge is to provide these arithmetic units with enough data to enable them to meet the computation demands of media applications. Conventional storage hierarchies, which frequently include caches, are unable to bridge the data bandwidth gap between modern DRAM and tens to hundreds of arithmetic units. A data bandwidth hierarchy, however, can bridge this gap by scaling the provided bandwidth across the levels of the storage hierarchy. The stream programming model enables media processing applications to exploit a data bandwidth hierarchy effectively. Media processing applications can naturally be expressed as a sequence of computation kernels that operate on data streams. This programming model exposes the locality and concurrency inherent in these applications and enables them to be mapped efficiently to the data bandwidth hierarchy. Stream programs are able to utilize inexpensive local data bandwidth when possible and consume expensive global data bandwidth only when necessary. This thesis presents the architecture of the Imagine streaming media processor which delivers a peak performance of 20 billion floating-point operations per second. Imagine efficiently supports 48 arithmetic units with a three-tiered data bandwidth hierarchy. At the base of the hierarchy, the streaming memory system employs memory access scheduling to maximize the sustained bandwidth of external DRAM. At the center of the hierarchy, the global stream register file enables streams of data to be recirculated directly from one computation kernel to the next without returning data to memory. Finally, local distributed register files that directly feed the arithmetic units enable temporary data to be stored locally so that it does not need to consume costly global register bandwidth. The bandwidth hierarchy enables Imagine to achieve up to 96% of the performance of a stream processor with infinite bandwidth from memory and the global register file. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
DOLPHIN: integrated meeting support across local and remote desktop environments and LiveBoards

This paper describes DOLPHIN, a fully group aware application designed to provide computer support for different types of meetings: face-to-face meetings with a large interactive electronic whiteboard with or without networked computers provided for the participants, extensions of these meetings with remote participants at their desktop computers connected via computer and audio/video networks, and/or participants in a second meeting room also provided with an electronic whiteboard as well as networked computers. DOLPHIN supports the creation and manipulation of informal structures (e.g., freehand drawings, handwritten scribbles), formal structures (e.g., hypermedia documents with typed nodes and links), their coexistence, and their transformation.
Evolutionary Induction of Sparse Neural Trees

This paper is concerned with the automatic induction of parsimonious neural networks. In contrast to other program induction situations, network induction entails parametric learning as well as structural adaptation. We present a novel representation scheme called neural trees that allows efficient learning of both network architectures and parameters by genetic search. A hybrid evolutionary method is developed for neural tree induction that combines genetic programming and the breeder genetic algorithm under the unified framework of the minimum description length principle. The method is successfully applied to the induction of higher order neural trees while still keeping the resulting structures sparse to ensure good generalization performance. Empirical results are provided on two chaotic time series prediction problems of practical interest.
Systems with correlations in the variance: Generating power law tails in probability distributions

We study how the presence of correlations in physical variables contributes to the form of probability distributions. We investigate a process with correlations in the variance generated by i) a Gaussian or ii) a truncated Lévy distribution. For both i) and ii), we find that due to the correlations in the variance, the process “dynamically” generates power law tails in the distributions, whose exponents can be controlled through the way the correlations in the variance are introduced. For ii), we find that the process can extend a truncated distribution beyond the truncation cutoff, which leads to a crossover between a Lévy stable power law and the present “dynamically generated” power law. We show that the process can explain the crossover behavior recently observed in the S&P500 stock index.
OreDesk: A Tool for Retrieving Data History Based on User Operations

During day-to-day activities, a user refers to various data items on a PC, such as documents, images, and audio clips. However, when the number of items in the history increases, locating the data becomes more complicated. We propose a novel system called "OreDesk" to retrieve particular data items from the history. OreDesk calculates the "active index" and "relation index" values for each data item based on the user operations. Active index indicates the interest of a user in the data. Relation index indicates how closely one data item is related to another. By using these indices, data can be retrieved on the basis of the association of user experiences. OreDesk also provides users with facilities such as "searching tool for related data" and "timeline viewer"
Validation of instruments to evaluate primary healthcare from the patient perspective: overview of the method.

UNLABELLED Patient evaluations are an important part of monitoring primary healthcare reforms, but there is little comparative information available to guide evaluators in the choice of instruments or to determine their relevance for Canada. OBJECTIVE To compare values and the psychometric performances of validated instruments thought to be most pertinent to the Canadian context for evaluating core attributes of primary healthcare. METHOD AMONG VALIDATED INSTRUMENTS IN THE PUBLIC DOMAIN, WE SELECTED SIX: the Primary Care Assessment Survey (PCAS); the Primary Care Assessment Tool - Short Form (PCAT-S); the Components of Primary Care Index (CPCI); the first version of the EUROPEP (EUROPEP-I); the Interpersonal Processes of Care Survey, version II (IPC-II); and part of the Veterans Affairs National Outpatient Customer Satisfaction Survey (VANOCSS). We mapped subscales to operational definitions of attributes. All were administered to a sample of adult service users balanced by English/French language (in Nova Scotia and Quebec, respectively), urban/rural residency, high/low education and overall care experience. The sample was recruited from previous survey respondents, newspaper advertisements and community posters. We used common factor analysis to compare our factor resolution for each instrument to that of the developers. RESULTS Our sample of 645 respondents was approximately balanced by design variables, but considerable effort was required to recruit low-education and poor-experience respondents. Subscale scores are statistically different by excellent, average and poor overall experience, but interpersonal communication and respectfulness scores were the most discriminating of overall experience. We found fewer factors than did the developers, but when constrained to the number of expected factors, our item loadings were largely similar to those found by developers. Subscale reliability was equivalent to or higher than that reported by developers. CONCLUSION These instruments perform similarly in the Canadian context to their original development context, and can be used with confidence. Interpersonal and respectfulness scores are most discriminating of excellent, average or poor overall experience and are crucial dimensions of patient evaluations.
Online Music, Sales Displacement, and Internet Search: Evidence from YouTube

Digital content services have become an important means of enjoying music, and considerable debate exists over the performance rights of sound recordings. In this paper, we exploit the removal of Warner Music content from YouTube in January 2009, and its restoration in October 2009, as a plausible experimental design to investigate the impact of online content availability on music sales and Internet search. To this end, we obtained weekly sales figures for Billboard top 200 albums from Nielsen SoundScan and constructed a globally consistent index of artist keyword search using Google Trends. We find that the blackout had both statistically and economically significant positive effects on album sales, specifically the best-selling albums in a week as effects taper off into insignificance as the top 50 albums are dropped. We find no evidence that the blackout had any causal effects on Internet search for artists. JEL Classification: D12, L86 O34
Reflectance spectra from free-swimming sticklebacks (Gasterosteus): Social context and eye-jaw contrast

Summary The color patterns of many organisms change rapidly with social context but such dynamic signals have been little studied with current methods. In this study we applied objective spectrophotometry techniques to the color displays of unrestrained male threespine sticklebacks, to assess the ine uence of social context on coloration. Analyzing our data with a color space model based on stickleback visual physiology, we found that unrestrained males enhanced saturation of both their blue eye and red jaw color in response to the presence of a mature male or female conspecie c. Divergence between the eye and the jaw lead to enhanced contrast, likely increasing conspicuousness. We found little relationship between measures of color saturation and condition, but the color of males in better condition varied more with social context. This study is the e rst to evaluate contrast between stickleback color pattern elements quantitatively and the e rst in which ree ectance spectra were collected from freeswimming e sh. The methods presented here could be used in future studies of sticklebacks and could potentially be adapted to other animals.
Applying DNA barcoding for the study of geographical variation in host–parasitoid interactions

Studies on the biogeography of host–parasitoid interactions are scarce, mainly because of technical difficulties associated with rearing and species identification. DNA barcoding is increasingly recognized as a valuable tool for taxon identification, allowing to link different life history stages of a species. We evaluate the usefulness of a protocol based on cytochrome oxidase I (COI) sequencing for the study of geographical variation of host–parasitoid interactions. Larvae of Acroclita subsequana (Lepidoptera: Tortricidae) were collected in Macaronesia and dissected to search for parasitoid larvae. Both hosts and parasitoids were sequenced and assigned to molecular operational taxonomic units (MOTUs) based on pairwise genetic distances, tree‐based and similarity‐based methods. Hosts were grouped into six MOTUs, usually with an allopatric distribution, while parasitoids clustered into 12 MOTUs, each of which was mostly found attacking a single host MOTU. Available COI sequence databases failed to provide identification to species level for these MOTUs. Three challenges related to the applicability of DNA barcoding in this type of studies are identified and discussed: (i) more suitable primers need to be developed for both parasitoids and hosts; (ii) the most commonly used approaches for inferring MOTUs have different limitations (e.g. arbitrary nature of defining a threshold to separate MOTUs) and need to be improved or replaced by other techniques; and (iii) for the identification of MOTUs, it is imperative to increase the range of sequenced taxa in the currently available reference databases. Finally, in spite of these difficulties, we discuss how DNA barcoding will help ecological and biogeographical studies of host–parasitoid interactions.
Construction of Immunoglobulin Fusion Proteins

Recombinant DNA technology has allowed the preparation of chimeric genes encoding proteins with novel properties. This unit describes the construction and subsequent testing of genes encoding immunoglobulin chimeras. The first protocol details fusion of a protein (or protein fragment) of interest onto an immunoglobulin constant region using a modified version of the expression vector pCDM8. The resulting fusion protein generally retains the functional properties of both the protein of interest and the immunoglobulin constant region; this can be demonstrated as described here.
Applying Decision Science to the Prioritization of Healthcare-Associated Infection Initiatives

Supplemental digital content is available in the text. Objectives Improving patient quality remains a top priority from the perspectives of both patient outcomes and cost of care. The continuing threat to patient safety has resulted in an increasing number of options for patient safety initiatives, making choices more difficult because of competing priorities. This study provides a proof of concept for using low-cost decision science methods for prioritizing initiatives. Methods Using multicriteria decision analysis, we developed a decision support model for aiding the prioritization of the four most common types of healthcare-associated infections: surgical site infections, central line–associated bloodstream infections, ventilator-associated events, and catheter-associated urinary tract infections. In semistructured interviews, we elicited structure and parameter values of a candidate model, which was then validated by six participants with different roles across three urban teaching and nonteaching hospitals in the Baltimore, Maryland area. Results Participants articulated the following structural attributes of concern: patient harm, monetary costs, patient mortality, reputational effects, and patient satisfaction. A quantitative decision-making model with an associated uncertainty report for prioritizing initiatives related to the four most common types of healthcare-associated infections was then created. Conclusions A decision support methodology such as our proof of concept could aid hospital executives in prioritizing the quality improvement initiatives within their hospital, with more complete data. Because hospitals continue to struggle in improving quality of care with tighter budgets, a formal decision support mechanism could be used to objectively prioritize patient safety and quality initiatives.
Intrusion detection in VANETs through verification of vehicle movement data

Many Intrusion Detection approaches for Vehicular ad hoc networks (VANETs) are proposed. However, not moving fake vehicles and vehicles with a plausible mobility model are not considered in other approaches. In this paper we propose an innovative signature based intrusion detection method that verifies vehicle movement data by applying a plausibility model. With our approach a single fake vehicle can be identified based on the plausibility model even if it simulates an autonomously valid movement. The results from the intrusion detection can be used to detect on the one hand road side attackers simulating faked traffic congestions and on the other hand attackers that try to deny real congestions by inserting moving vehicles into the network.