Miracle-dz/UniFAR-FTUs huggingface dataset:
Winner-Take-All Multiple Category Boosting for Multi-view Face Detection

“Divide and conquer” has been a common practice to address complex learning tasks such as multi-view object detection. The positive examples are divided into multiple subcategories for training subcategory classifiers individually. However, the subcategory labeling process, either through manual labeling or through clustering, is suboptimal for the overall classification task. In this paper, we propose multiple category boosting (McBoost), which overcomes the above issue through adaptive labeling. In particular, a winner-take-all McBoost (WTA-McBoost) scheme is presented in detail. Each positive example has a unique subcategory label at any stage of the training process, and the label may switch to a different subcategory if a higher score is achieved by that subcategory classifier. By allowing examples to self-organize themselves in such a winner-takeall manner, WTA-McBoost outperforms traditional schemes significantly, as supported by our experiments on learning a multi-view face detector.
Dual Kalman--Bucy Filters and Interactive Entropy Production

This paper investigates partially observed linear Gaussian systems in continuous time from an information-theoretic viewpoint. It identifies information supply, storage, and dissipation processes that quantify various dependencies between the unobservable and observable components of the state variables of such systems, which we call the signal and observation processes. The storage is that information in the past of the observation useful for estimating the present and future of the signal. It is so called because it is the information "stored" in the state variable of the Kalman--Bucy filter. The optimal properties of the Kalman--Bucy filter bring about a particular symmetry in its joint dynamics with the signal. This enables a dual system, with the same structure as the original, to be derived by time reversal. The information supply and dissipation processes of this dual problem are those of the original, with roles interchanged. The same symmetry enables us to define an entropic measure of the local time-asymmetry of the interaction between the signals and filters, which we call the rate of interactive entropy production. This is shown to be directly connected with the rates of information supply and dissipation. It is also intimately connected with the entropy production of an abstract statistical mechanical system at or near a stationary nonequilibrium state.
VIBRATION BASED CONDITION MONITORING IN ROTATING MACHINERIES

In Chapters 15 and 16, the measurement and signal processing techniques, transducers, signal conditioners and signal analysis equipments are described, which are used in the rotating machinery condition monitoring. It is very important to display the measured signal in convenient form so as to be useful for the interpretation of the condition of rotating machinery. In the present chapter, by looking at various forms of measured signal possible condition of machinery is provided. It also looks into correlation of a particular signature with a particular failure in more details regarding, which helps in assigning a particular failure. Every faults have a specific signature in the measured signal and it is most convenient and cheapest way to identify possible fault in a machinery. Now very advanced signal processing techniques (Wavelet transform, Genetic algorithms, Neural network, fuzzy logic and machine support vectors) are being applied in laboratory test set ups to detect, locate and quantify the faults and based on this even the life of the machinery is also being predicted. A brief review to application these techniques for rotating machinery condition monitoring is provided since detailed treatment to these newly emerging methods is beyond the scope of the present book. Proactive action to prevent a failure is the better the detection of failure. The next chapter will be dealt with introduction of the active control of rotors by magnetic bearings, which is still a research and applied area in the field of rotor dynamics.
The cyclopentenone prostaglandin 15-deoxy-Delta(12,14)-prostaglandin J(2) attenuates the development of acute and chronic inflammation.

Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear hormone receptor superfamily of ligand-activated transcription factors that are related to retinoid, steroid, and thyroid hormone receptors. The PPAR-gamma receptor subtype seems to play a pivotal role in the regulation of cellular proliferation and inflammation. Recent evidence also suggests that the cyclopentenone prostaglandin (PG) 15-deoxyDelta(12,14)-PGJ(2) (15d-PGJ(2)), which is a metabolite of prostaglandin D(2), functions as an endogenous ligand for PPAR-gamma. We postulated that 15d-PGJ(2) would attenuate inflammation. In the present study, we have investigated the effects of 15d-PGJ(2) of acute and chronic inflammation (carrageenan-induced pleurisy and collagen-induced arthritis, respectively) in animal models. We report for the first time, to our knowledge, that 15d-PGJ(2) (given at 10, 30, or 100 microg/kg i.p. in the pleurisy model or at 30 microg/kg i.p every 48 h in the arthritis model) exerts potent anti-inflammatory effects (e.g., inhibition of pleural exudate formation, mononuclear cell infiltration, delayed development of clinical indicators, and histological injury) in vivo. Furthermore, 15d-PGJ(2) reduced the increase in the staining (immunohistochemistry) for nitrotyrosine and poly (ADP-ribose) polymerase and the expression of inducible nitric-oxide synthase and cyclooxygenase-2 in the lungs of carrageenan-treated mice and in the joints from collagen-treated mice. Thus, 15d-PGJ(2) reduces the development of acute and chronic inflammation. Therefore, the cyclopentenone prostaglandin 15d-PGJ(2) may be useful in the therapy of acute and chronic inflammation.
GEOMETRIC MODELLING AND CALIBRATION OF A HIGH RESOLUTION PANORAMIC CAMERA

In photogrammetric applications the use of a digital panoramic camera with 360° field of view may provide an interesting alternative to conventional methods. As the image geometry does not obey a central perspective it was necessary to establish a geometric model for digital panoramic cameras. This model was tested using a camera prototype produced by KST (Kamera & System Technik). Several mechanical and optical characteristics of the physical camera system cause deviations from the basic model. These deviations were geometrically modeled using additional parameters. The model was implemented in a spatial resection and a spatial intersection to calculate the exterior and interior orientation, to analyse the effect of additional parameters and to verify the accuracy potential of the camera. FIG. 1. Camera EYESCAN M3 with glass-fibre illumination system and its basic parameters
A guide to conducting a task analysis of psychotherapeutic change

Abstract The epistemological and methodological underpinnings of task analysis are discussed and the steps and concrete procedures for its implementation are described and exemplified in a task analysis of the resolution of unfinished business. Task analysis, a method for studying the process of change, consists of two main phases: a discovery-oriented phase based on rational–empirical model building and a validation phase based on hypothesis testing. The goals of the approach are to (a) build an observationally based model of how therapeutic change occurs for a particular type of affective–cognitive problem, (b) validate the model of change, and (c) relate the process of change to outcome. Benefits and strengths of the approach are presented and factors that have impeded the use of this approach in the study of change processes are discussed.
An Immunocompetent Mouse Model for MLL/AF9 Leukemia Reveals the Potential of Spontaneous Cytotoxic T-Cell Response to an Antigen Expressed in Leukemia Cells

Leukemia differs substantially with respect to stromal milieu from tumors that progress locally as solid masses, and the physiological importance of immunosurveillance in leukemia remains unclear. However, currently available mouse leukemia models have critical limitations in the context of analyzing immunological regulation of leukemia development. In this study, we transferred mouse MLL/AF9 leukemia-initiating cells into immunocompetent recipient mice without any pre-conditioning such as irradiation, and then analyzed the spontaneous T cell response to an immunogenic antigen expressed in leukemia cells. When the minimum numbers of leukemia-initiating cells for engraftment were transferred, leukemia cells were eradicated by the adaptive immune response in most, if not all, wild-type mice, but not in Rag2 -/- recipient mice, which lack adaptive immunity. By contrast, mice transplanted with larger numbers of leukemia cells always developed leukemia. In mice with advanced leukemia, antigen-specific CTLs were also expanded, but were unresponsive to antigen stimulation and expressed high levels of PD-1 and LAG-3. These results provide the first clear demonstration that the spontaneous CTL response to a tumor-cell antigen has the potential to eradicate leukemia, whereas antigen-specific CTLs are exhausted in animals with advanced leukemia. This immunocompetent mouse leukemia model provides a useful platform for developing effective immunotherapies against leukemia.
Predicting the Effect of Muscle Length on Fatigue during Electrically Stimulated Isometric Contractions

The objectives of our study were to 1) determine the knee angle (40 ° or 90 ° ) that best identifies model parameters, and 2) test the predictive accuracy of the model within each subject at 20 ° , 40 ° , 65 ° , and 90 ° of knee flexion. The existing model was modified by scaling the equation for the force-length relationship with the parameter representing the magnitude of force. Experiments were conducted using a computer-controlled stimulator that sent trains of pulses to surface electrodes on the thighs of five subjects while forces were measured at the ankle. Model parameters were identified using non-linear optimization, which minimized the sum of squares error. The accuracy of the model predictions was assessed using linear regression analysis for the force-time integral. Model accuracy was slightly greater when model parameters were identified at 90 ° rather than 40 ° . Following parameter identification at 90 ° , the average r-squared values for the force-time integrals were >0.75, indicating that at least 75% of the variability in the measurements was explained by the model. Because the force model depends explicitly on angle and the fatigue model depends explicitly on force, the dependence of fatigue on knee angle was implicit. The force-fatigue model can now be expanded to predict fatigue during dynamic contractions.
Mutagenesis data in the automated prediction of transmembrane helix dimers

We present a molecular modeling protocol that selects modeled protein structures based on experimental mutagenesis results. The computed effect of a point mutation should be consistent with its experimental effect for correct models; mutations that do not affect protein stability and function should not affect the computed energy of a correct model while destabilizing mutations should have unfavorable computed energies. On the other hand, an incorrect model will likely display computed energies that are inconsistent with experimental results. We added terms to our energy function which penalize models that are inconsistent with experimental results. This creates a selective advantage for models that are consistent with experimental results in the Monte Carlo simulated annealing protocol we use to search conformational space. We calibrated our protocol to predict the structure of transmembrane helix dimers using glycophorin A as a model system. Inclusion of mutational data in this protocol compensates for the limitations of our force field and the limitations of our conformational search. We demonstrate an application of this structure prediction protocol by modeling the transmembrane region of the BNIP3 apoptosis factor. © 2007 Wiley‐Liss, Inc.
On 'systematic' reviews of research literatures: A 'narrative' response to Evans & Benefield

The production of 'systematic' reviews of research findings has recently come to be treated as a priority in the field of education, and other areas too. Such reviews are believed to play an important role in making evidence from research available in a usable form to policy-makers and practitioners. This article examines the assumptions about research, and about the task of reviewing, which are built into the concept of systematic review. In addition, attention is given to the likely consequences of the priority now being given to this type of review.
Enforcement, Compliance, and Disputes in Welfare-to-Work Programs

Mandatory welfare-to-work programs are a cornerstone of current welfare reform efforts, but achieving compliance has been difficult for these programs, in part because the organizational issues facing welfare-to-work programs have not been considered. In this analysis of case management practices in four of California's Greater Avenues to Independence programs, we demonstrate how organizational arrangements influence client compliance with program requirements. Compliance is associated with an ideology that does not stigmatize welfare recipients, goals that stress education and skill training, a service technology that is people-changing, and dispute management strategies that emphasize lenience and professional treatment.
Work group demography, social integration, and turnover.

The authors gratefully acknowledge the assistance of Blake Frank for his help in obtaining the turnover data for this study and the University of California Institute of Industrial Relations for research support. Using 20 actual work units with 79 respondents, this study explores the relationships among group demography, social integration of the group, and individual turnover. Results suggest that heterogeneity in group tenure is associated with lower levels of group social integration which, in turn, is negatively associated with individual turnover. Models of these effects using individual-level integration measures are not significant. Further, the results suggest that it is the more distant group members who are more likely to leave. Both individual-level and group-level age demography directly affect turnover and are not moderated by social integration. The findings suggest a process by which group demography affects outcomes and support the usefulness of organizational demography for understanding group and individual functioning. '
Exciting the magnetosphere of the magnetar CXOU J164710.2-455216 in Westerlund 1

We describe XMM-Newton observations taken 4.3 days prior to and 1.5 days subsequent to two remarkable events that were detected with Swift on 2006 September 21 from the candidate magnetar CXOU J164710.2-455216: (1) a 20 ms burst with an energy of 1e37 erg (15-150 keV), and (2) a rapid spin-down (glitch) with a fractionap period change of 1e-4. We find that the luminosity of the pulsar increased by a factor of 100 in the interval between observations, from 1e33 to 1e35 erg/s (0.5-8.0 keV), and that its spectrum hardened. The pulsed count rate increased by a factor of 10 (0.5-8.0 keV), but the fractional rms amplitude of the pulses decreased from 65 to 11 per cent, and their profile changed from being single-peaked to exhibiting three peaks. Similar changes have been observed from other magnetars in response to outbursts, such as that of 1E 2259+586 in 2002 June. We suggest that a plastic deformation of the neutron star's crust induced a very slight twist in the external magnetic field, which in turn generated currents in the magnetosphere that were the direct cause of the X-ray outburst.
Evaluating Behavioral Self-Monitoring With Accuracy Training for Changing Computer Work Postures

The primary purpose of this study was to replicate and extend a study by Gravina, Austin, Schroedter, and Loewy (2008). A similar self-monitoring procedure, with the addition of self-monitoring accuracy training, was implemented to increase the percentage of observations in which participants worked in neutral postures. The accuracy training required the three participants to practice self-monitoring with the experimenter at least 20 times and to meet the criteria of 90% accuracy for the last 10 monitors. Feedback was delivered after each monitor. Two postures for each of the three participants were targeted by the intervention, and all six improved with an average effect size of 4.7 (range: 3.4 to 8.2) compared to Gravina et al., in which effect sizes averaged 1.9 (range: −.1 to 3.2). In addition, participant self-monitoring was more accurate overall (77%) when compared to Gravina et al. (44%).
Performance Accomplishment Information as Predictors of Self-Efficacy as a Function of Skill Level in Amateur Golf

The predictive capabilities of different types of performance accomplishment information (PAI) towards self-efficacy for amateur golfers were compared as a function of skill level. Male golfers (N = 197; skilled n = 84, lesser skilled n = 113) recorded self-efficacy levels before and after competitive golf performance. Multiple regression analyses revealed that handicap was the most significant predictor of PAI towards pre-round self-efficacy for skilled golfers while practice satisfaction was the most significant predictor for lesser skilled. Handicap achievement was a significant predictor of post-round self-efficacy for both skilled and lesser skilled golfers. The findings imply athletes of varying skill level utilize different information when developing efficacy beliefs. Further study of the relationship between PAI and self-efficacy is therefore warranted in the sports domain.
Challenging the UK rules on the rights of EU8 workers

Following the enlargement of the European Union in 2004, the UK implemented a relatively open labour market policy that allowed migrants from the eight central and eastern European accession states to take up work in the UK providing that they complied with registration requirements. At the same time, however, the UK sought to prevent EU8 migrants who found themselves without work from accessing benefits in its territory. This article analyses the House of Lords decision in Zalewska v Department for Social Development [2008] UKHL 67 in which the UK rules were challenged. Although the majority of the House of Lords upheld the decision that the UK's rules of registration are compatible with the Accession treaties and broader provisions of Community law on free movement and citizenship, it is submitted here that the opinions of the minority represent a more accurate application of the relevant Community law principles, notably proportionality, as interpreted by the European Court of Justice. Overall, the article emphasises how individuals' access to rights enshrined in provisions of Community law depends largely upon the goodwill of the national courts.
Network reconfiguration using a genetic approach for loss and reliability optimization in distribution systems

This paper presents a new method to improve reliability and also minimize losses in radial distribution systems (RDS), trough a process of network reconfiguration, using a genetic algorithm approach. The methodology adopted to enhance reliability, uses the Monte Carlo simulation and an historical data of the network such as the level of reliability and the severity of potential contingencies in each branch. The method analyses the RDS in two perspectives. A first perspective of optimization considering no investment, therefore using only the switches presented in the network, and a second perspective of optimization where is given the possibility to place a limited number of tie-switches and thus get better results. Here, the number of tie-switches and the branches that can receive them are defined by a decision agent. The effectiveness of the proposed method is demonstrated through the analysis of a 69 bus RDS.
Pricing Barrier Options with Square Root Constant Elasticity of Variance Process

The square root constant elasticity of variance (CEV) process has been paid little attention in previous research on valuation of barrier options. In this paper we derive analytical option pricing formulae of up-and-out options with this process using the eigenfunction expansion technique. We develop an efficient algorithm to compute numerical results from the formula. The numerical results are compared with the corresponding model prices under the Black-Scholes model. We find that the differences in the model prices between the square root CEV model and the Black-Scholes model can be significant as the time to maturity and volatility increase.
sFPGA2 - A scalable GALS FPGA architecture and design methodology

The interconnection networks used by current fine grain FPGAs are not scalable for very big array sizes. To address this issue, we apply the GALS (Globally Asynchronous and Locally Synchronous) paradigm to build scalable FPGAs. The logic resources are divided into locally synchronous tiles and asynchronous communications among different tiles. To route the asynchronous communications, we build a serial network-on-chip. Targeting streaming applications, we propose a design flow that maps user applications to our new FPGA architecture. To validate our architecture and design flow, we build an emulation prototype and develop a JPEG baseline encoder as the case study. We have successfully demonstrated the concept and predict a maximum frequency of 224MHz for designs mapping to sFPGA2 architecture.
Hierarchical Bayesian Approach and Genetic Algorithm in Illustrating Customer Preference and Market Segmentation

Nowadays, enterprises need to consider not only if the products or services they provided can conform to the needs of most consumers, but also how to satisfy the demand of a specific market segment and appeal them to repurchase as well due to the severe market competition. Besides, in an enterprise, the capability to both generate and collect data has also been expanded enormously and provides us with huge amount of data. It is noted that the number of such databases keeps growing rapidly because of the availability of powerful and affordable database management systems. To compete effectively in such an environment, business managers have changed their thoughts and treat the heterogeneity of customer as an important issue. Moreover, some enterprises start to study the customer heterogeneity when they have different brand choices. The main objective of this study is to explore the identification of customer heterogeneity and classification by using the Hierarchical Bayesian Model (HBM). Moreover, in order to resolve the efficiency issues regarding the reference estimates of the Hierarchical Bayesian model, we have integrated the genetic algorithm (GA) technology to expedite the speed of convergence amid the Markov Chain Monte Carlo (MCMC). Based on actual application results, we have discovered that the proposed method contains obvious supportive functions.