Miracle-dz/UniFAR-FTUs huggingface dataset:
DEVELOPMENT OF A LEXICON FOR BEEF FLAVOR IN INTACT MUSCLE: BEEF FLAVOR LEXICON

ABSTRACT A lexicon describing the flavor characteristics of beef across different cuts, grades, and cooking temperatures and methods was developed. Four major cuts of the United States Department of Agriculture (USDA) quality grade beef were cooked to five endpoint temperatures using braising, broiling (oven broiling and electric charbroiling), roasting and grilling (indoor and outdoor grilling). Six highly trained panelists identified and defined a total of 38 aroma and flavor characteristics in 176 beef samples. Beef identity, brown/roasted, bloody/serumy, metallic, fat-like, overall sweet, sour aromatics and five tastes were present in practically all samples. Other attributes were present only in certain samples, depending on either the sample group or the cooking method/endpoint temperature combination used. This lexicon potentially offers the beef industry a standard tool to identify and quantify flavor attributes as impacted by temperature, cooking method, aging process, storage time, diet regime, packaging, USDA quality grades, etc. PRACTICAL APPLICATIONS Until now, the beef industry's main focus has been to assess beef tenderness and juiciness, with an emphasis on ways to improve beef texture. Meat companies and academic institutions have been using the 1995 American Meat Science Association guidelines to assess the flavor of beef, which are not comprehensive. Recent work has focused on flavor, and the industry needs a standardized flavor lexicon that can be used for many projects. It is important for the industry to be able to systematically identify and quantify flavor attributes that drive consumer acceptance.
Experimental design of stand-alone field oriented control for WECS in variable speed DFIG-based on hysteresis current controller

This paper presents the experimental design of a stand-alone field-oriented control (FOC) for wind turbine based on a doubly fed induction generator (DFIG). The control law is synthesized using a hybrid FOC-Hysteresis current controller (HCC) in Rotor side converter (RSC) and the stator is connected to the resistive load via rectifier (nonlinear load). The regulation is achieved below the synchronous speed (Hypo-synchronous mode). The implementation is realized using dSPACE1104 single board control and acquisition interface. The obtained results of the proposed control present high performance in steady and transient states.
Traditional Versus New-Keynesian Phillips Curves: Evidence from Output Effects

The issue of the backward-looking versus the forward-looking Phillips curve is still an open question in the macroeconomics profession. We identify a crucial difference between the two hypotheses concerning the real output effects of monetary policy shocks. The backward-looking Phillips curve predicts a strict intertemporal trade-off in the case of monetary shocks: a positive short run response of output is followed by a period where output is below the baseline. The resulting cumulative output effect is exactly zero. In contrast, the forward-looking model implies that the cumulative output effect of temporary monetary shocks is positive. The empirical evidence on the cumulated output effects of money are consistent with the forward-looking model.
An assessment of the methods that are used to recruit college students into the Turkish Hezbollah.

AN ASSESSMENT OF THE METHODS THAT ARE USED TO RECRUIT COLLEGE STUDENTS INTO THE TURKISH HEZBOLLAH. By Tuncay Unal, PhD. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University Virginia Commonwealth University, 2010 Major Director: William W. Newmann, Ph.D., Professor of Political Science, L. Douglas Wilder School of Government and Public Affairs This study aims to identify tactics used by the Turkish Hezbollah to recruit college students into joining their terrorist organization. This study based on the assumptions that social networks and institutional structures are two main tools that are used effectively by the Turkish Hezbollah to recruit college educated students. In this sense, the researcher claims that Social Learning theory and Social Control Theories can be used to provide theoretical explanation to the Hezbollah‟s recruitment strategy. Parallel to these theories assumptions, while having militants within social networks increases the likelihood of being recruited through social learning theory assumptions, college students who are away from their families are more likely to be recruited through social control theory assumptions. The researcher uses individual level secondary data related to members of the Turkish Hezbollah. The data comprised of self reports that each member submitted to the Turkish Hezbollah as part of their recruitment process. The data are derived from the
Análisis bibliométrico sobre depresión infantil en España

Resumen: En este articulo se presentan los datos obtenidos del analisis bibliometrico referente a los trabajos sobre depresion infantil en Espana desde 1875 hasta junio de 2002. El numero de trabajos encontrados es de 208, de los cuales el 88% ha sido publicado en las dos ultimas decadas (1983 a 2002), mientras que en los restantes 107 anos, desde 1875 hasta 1982, solo el 12%. Destacamos a Aquilino Polaino como gran productor con 34 publicaciones, seguido de Domenech Llobeira, Victoria del Barrio y Conde Lopez. Ballesteros Alcalde tiene el indice de colaboracion mas alto con una puntuacion de 1,88, mientras que Josep Toro presenta un indice de colaboracion cero. El numero de trabajos firmados por un autor es de 105, es decir, el 50,48%. El contenido de los trabajos es fundamentalmente teorico, un 54%, y de estos un 18% se refiere al diagnostico y clasificacion de la depresion infantil y tan solo el 8% el estudio de factores de riesgo y prevencion.
A High-Throughput Processor for Cryptographic Hash Functions

—This paper presents a high throughput ApplicationSpecific Instruction-set Processor (ASIP) for cryptographic hash functions. The processor is obtained via hardware/software codesign methodology and accelerates SHA (Secure Hash Algorithm) and MD5 hash functions. The proposed design occupies 0.28 mm (66 kgates) in 65 nm CMOS process including 4.5 KB single port memory and 52 kgates logic. The throughput of the proposed design reaches 15.8 Gb/s, 12.5 Gb/s, 12.2 Gb/s, and 19.9 Gb/s for MD5, SHA-1, SHA-512, and SHA3-512, respectively under the clock frequency of 1.0 GHz. The proposed design is evaluated with state-of-the-art VLSI designs, which reveals its high performance, low silicon cost, and full programmability.
Divergent Selection and the Evolution of Signal Traits and Mating Preferences

Mating preferences are common in natural populations, and their divergence among populations is considered an important source of reproductive isolation during speciation. Although mechanisms for the divergence of mating preferences have received substantial theoretical treatment, complementary experimental tests are lacking. We conducted a laboratory evolution experiment, using the fruit fly Drosophila serrata, to explore the role of divergent selection between environments in the evolution of female mating preferences. Replicate populations of D. serrata were derived from a common ancestor and propagated in one of three resource environments: two novel environments and the ancestral laboratory environment. Adaptation to both novel environments involved changes in cuticular hydrocarbons, traits that predict mating success in these populations. Furthermore, female mating preferences for these cuticular hydrocarbons also diverged among populations. A component of this divergence occurred among treatment environments, accounting for at least 17.4% of the among-population divergence in linear mating preferences and 17.2% of the among-population divergence in nonlinear mating preferences. The divergence of mating preferences in correlation with environment is consistent with the classic by-product model of speciation in which premating isolation evolves as a side effect of divergent selection adapting populations to their different environments.
Comparison of different impact analysis methods and programmer's opinion: an empirical study

In change impact analysis, obtaining guidance from automatic tools would be highly desirable since this activity is generally seen as a very difficult program comprehension problem. However, since the notion of an 'impact set' (or dependency set) of a specific change is usually very inexact and context dependent, the approaches and algorithms for computing these sets are also very diverse producing quite different results. The question 'which algorithm finds program dependencies in the most efficient way? ' has been preoccupying researchers for a long time, but there are still very few results published on the comparison of the different algorithms to what programmers think are real dependencies. In this work, we report on our experiment conducted with this goal in mind using a compact, easily comprehensible Java experimental software system, simulated program changes, and a group of programmers who were asked to perform impact analysis with the help of different tools and on the basis of their programming experience. We show which algorithms turned out to be the closest to the programmers' opinion in this case study. However, the results also certified that most existing algorithms need to be further enhanced and an effective methodology to use automated tools to support impact analysis still needs to be found.
Journal of Applied Animal Welfare Science Hediger Revisited: How Do Zoo Animals See Us?

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Heat Transfer in Underground Rail Tunnels

Department of Mathematics, Imperial College London, London SW7 2AZ, UnitedKingdomAbstractThe transfer of heat between the air and surrounding soil in underground tunnels insinvestigated, as part of the analysis of environmental conditions in underground railsystems. Using standard turbulent modelling assumptions, ow pro les are obtainedin both open tunnels and in the annulus between a tunnel wall and a moving train,from which the heat transfer coecient between the air and tunnel wall is computed.The radial conduction of heat through the surrounding soil resulting from changesin the temperature of air in the tunnel are determined. An impulse change andan oscillating tunnel air temperature are considered separately. The correlationsbetween uctuations in heat transfer coecient and air temperature are found toincrease the mean soil temperature. Finally, a model for the coupled evolution ofthe air and surrounding soil temperature along a tunnel of nite length is given.Key words: tunnel ventilation, heat conduction
The effectiveness of semantic web based preschool cognitive skills tutoring system: An empirical study

Two groups had participated in a study on the effectiveness of Semantic Web based mobile application for preschool cognitive skills learning. The first group had the traditional method with textbooks and teacher's teaching. The second group worked with the proposed application at school along with the classroom sessions. A quasi experimental pre and post tests model was conducted to measure the learning gain for classification and relatedness cognitive skills. The results had shown significant gain by the second group over the first one and hence support the use of the proposed application in practice. The conclusion is that proposed application can be used as teaching support along with formal school learning.
Phonetic vocoding with speaker adaptation

This paper describes a phonetic vocoding scheme which relies on speaker adaptation to capture important speaker characteristics. These are typically lost in phonetic vocoders which transmit only information about the phones which are recognized, together with some prosodic information. In our scheme, however, additional speaker characteristics are transmitted in vowel regions (average values of LSP coefficients for each phone). This additional information yielded potentially good speaker recognizability results, in informal listening tests, while still achieving a rather low average bit rate, suitable for many transmission and storage applications. This work extends our previous phonetic vocoding scheme described in [5]. The vocoder is now fully quantized and the number of transmitted parameters had been significantly reduced.
A Seamless Quality-Driven Multi-Hop Data Delivery Scheme for Video Streaming in Urban VANET Scenarios

The inherent characteristics of vehicular networks, such as dynamic topology and high mobility, pose significant challenges for the deployment of delay-sensitive applications, e.g., video streaming, in urban Vehicular Ad-hoc Networks (VANET). In this paper, we propose an integrated network-layer scheme for seamless delivery of video packets in VANET. First, we propose a new quality-driven routing scheme for delivering video streams from a fixed network to a destination vehicle via multihop communications. The routing scheme aims to optimize the visual quality of the transmitted video frames by minimizing the distortion, the start-up delay, and the frequency of the streaming freezes. We further propose an efficient network mobility management scheme, which introduces a novel adaptation of Proxy Mobile IPv6 (PMIPv6) for multi-hop VANET scenarios, and incorporates a handover prediction mechanism. Numerical results are given to demonstrate that our integrated scheme can achieve a better performance for the video quality metrics, the handover delay and the signalling cost.
Structured clinical interview for DSM-IV axis II personality disorders : SCID-II

The Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II) is an efficient, user-friendly instrument that will help researchers and clinicians make standardized, reliable, and accurate diagnoses of the 10 DSM-IV Axis II personality disorders as well as depressive personality disorder, passive-aggressive personality disorder, and personality disorder not otherwise specified. Now compatible with DSM-IV, the interview questions have been redesigned to reflect the subject's inner experience. This instrument begins with a brief overview that characterizes the subject's typical behavior and relationships and elicits information about the subject's capacity for self-reflection. It then considers each of the personality disorders in detail. The Questionnaire is a single-use personality questionnaire to be completed by the patient that can be used as a screening tool to shorten the interview. Bound separately, it is sold only with the Interview booklet. The Interview is a single-use booklet that is bound separately but used in conjunction with the Questionnaire. It contains the interview questions and provides space to record responses. At the conclusion of the Interview, the clinician completes the Summary Score Sheet and computes a dimensional score for each personality disorder. This is a package of 5.
Hand movements reveal the temporal characteristics of visual attention

This thesis applied a choice reaching task (CRT) to different visual search settings to investigate the temporal characteristics of visual attention. The initiation latency (IL) and maximum deviation (MD) of the reach trajectory provided the greatest insight into early and ongoing competition for selection. We replicated priming of pop-out (PoP) effects on IL and MD before using the PoP paradigm to examine motor system involvement in generating movement-relevant predictions. Predictable repetition of the target colour recruited the motor cortex but only when the colour signalled the target of an overt movement. We also demonstrated that reaches are affected by global-to-local scene processing presenting a novel dissociation of IL and MD. IL reflected global configural biases (bottom-up), whilst MD reflected local positional biases (top-down). Finally, we examined the influence of irrelevant features (IFs) on target selection. Attentional capture by the IF affected the entire selection process when the target colour and IF presence were unpredictable. When the IF could coincide with multiple search items performance was modulated by early proximity and late similarity grouping. Overall, the results demonstrate the ability of the CRT to investigate the time course of attentional processing above and beyond that provided by key-press response tasks.
Individualized treatment rules: Generating candidate clinical trials

Individualized treatment rules, or rules for altering treatments over time in response to changes in individual covariates, are of primary importance in the practice of clinical medicine. Several statistical methods aim to estimate the rule, termed an optimal dynamic treatment regime, which will result in the best expected outcome in a population. In this article, we discuss estimation of an alternative type of dynamic regime—the statically optimal treatment rule. History‐adjusted marginal structural models (HA‐MSM) estimate individualized treatment rules that assign, at each time point, the first action of the future static treatment plan that optimizes expected outcome given a patient's covariates. However, as we discuss here, HA‐MSM‐derived rules can depend on the way in which treatment was assigned in the data from which the rules were derived. We discuss the conditions sufficient for treatment rules identified by HA‐MSM to be statically optimal, or in other words, to select the optimal future static treatment plan at each time point, regardless of the way in which past treatment was assigned. The resulting treatment rules form appropriate candidates for evaluation using randomized controlled trials. We demonstrate that a history‐adjusted individualized treatment rule is statically optimal if it depends on a set of covariates that are sufficient to control for confounding of the effect of past treatment history on outcome. Methods and results are illustrated using an example drawn from the antiretroviral treatment of patients infected with HIV. Specifically, we focus on rules for deciding when to modify the treatment of patients infected with resistant virus. Copyright © 2007 John Wiley & Sons, Ltd.
Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering

We present a fully automatic method employing convolutional neural networks based on the 2D U-net architecture and random forest classifier to solve the automatic liver lesion segmentation problem of the ISBI 2017 Liver Tumor Segmentation Challenge (LiTS). In order to constrain the ROI in which the tumors could be located, a liver segmentation is performed first. For the organ segmentation, an ensemble of convolutional networks is trained to segment a liver using a set of 179 liver CT datasets from liver surgery planning. Inside of the liver ROI a neural network, trained using 127 challenge training datasets, identifies tumor candidates, which are subsequently filtered with a random forest classifier yielding the final tumor segmentation. The evaluation on the 70 challenge test cases resulted in a mean Dice coefficient of 0.65, ranking our method in the second place.
White-throated sparrows calibrate their magnetic compass by polarized light cues during both autumn and spring migration

SUMMARY The interaction and hierarchy of celestial and magnetic compass cues used by migratory songbirds for orientation has long been the topic of an intense debate. We have previously shown that migratory Savannah sparrows, Passerculus sandwichensis, use polarized light cues near the horizon at sunrise and sunset to recalibrate their magnetic compass. Birds exposed to a ±90 deg. shifted artificial polarization pattern at sunrise or sunset recalibrated their magnetic compass, but only when given full access to celestial cues, including polarized light cues near the horizon. In the current study, we carried out cue conflict experiments with white-throated sparrows, Zonotrichia albicollis, during both spring and autumn migration in a transition zone between the species' breeding and wintering areas on the south shore of Lake Ontario. We show that white-throated sparrows also recalibrate their magnetic compass by polarized light cues at sunrise and sunset. Sunrise exposure to an artificial polarization pattern shifted relative to the natural magnetic field or exposure to a shift of the magnetic field relative to the natural sky both led to recalibration of the magnetic compass, demonstrating that artificial polarizing filters do not create an anomalous, unnatural orientation response. Our results further indicate that there is no evidence for a difference in compass hierarchy between different phases of migration, confirming previous work showing that polarized light cues near the horizon at sunrise and sunset provide the primary calibration reference both in the beginning and at the end of migration.
Guaranteed Classification via Regularized Similarity Learning

Learning an appropriate (dis)similarity function from the available data is a central problem in machine learning, since the success of many machine learning algorithms critically depends on the choice of a similarity function to compare examples. Despite many approaches to similarity metric learning that have been proposed, there has been little theoretical study on the links between similarity metric learning and the classification performance of the resulting classifier. In this letter, we propose a regularized similarity learning formulation associated with general matrix norms and establish their generalization bounds. We show that the generalization error of the resulting linear classifier can be bounded by the derived generalization bound of similarity learning. This shows that a good generalization of the learned similarity function guarantees a good classification of the resulting linear classifier. Our results extend and improve those obtained by Bellet, Habrard, and Sebban (2012). Due to the techniques dependent on the notion of uniform stability (Bousquet & Elisseeff, 2002), the bound obtained there holds true only for the Frobenius matrix-norm regularization. Our techniques using the Rademacher complexity (Bartlett & Mendelson, 2002) and its related Khinchin-type inequality enable us to establish bounds for regularized similarity learning formulations associated with general matrix norms, including sparse L1-norm and mixed (2,1)-norm.