Miracle-dz/UniFAR-FTUs huggingface dataset:
Negotiating memorial and extra-memorial information: the effect of social information on eyewitness identification decisions

Recognition judgments, such as those involved in eyewitness identification, are often depicted as relatively pure products of memory processes and criterion setting, such as is depicted in the WITNESS model of eyewitness identification behavior. The presence of extra-memorial factors, such as social influence, however, necessitates a negotiation between memorial and extra-memorial information. Participants (N = 450) viewed a short video depicting a person planting a bomb down an airshaft. Before attempting lineup identifications, participants in Experiment 1 learned that an alleged co-witness made a ―not there,‖ plausible, or implausible identification decision with high or low confidence. Cowitness information dramatically influenced identification decisions in the direction of the co-witness‘s decision. Particularly important was the finding that there was a significant effect of co-witness information even for participants who learned that the co-witness identified an implausible lineup member. This latter finding cannot be explained by standard two-parameter models of recognition (such as the WITNESS model). Participants‘ confidence in their identification decisions tended to match that of their co-witness, regardless of whether the co-witness gave a ―not there,‖ plausible, or implausible identification decision. However, this confidence-matching effect was greater for participants who made the same decision as the co-witness than it was for participants who made a different decision than the co-witness. Experiment 2 participants (N=323) viewed the same crime video and then either viewed the lineup first or received the co-witness information (i.e., a ―not there‖ or plausible identification decision) first. As in Experiment 1, co-witness information influenced identification decisions in the direction of the co-witness‘s identification, but the extent of the influence did not vary as a function of the presentation
Comparing pure parallel ensemble creation techniques against bagging

We experimentally evaluate randomization-based approaches to creating an ensemble of decision-tree classifiers. Unlike methods related to boosting, all of the eight approaches considered here create each classifier in an ensemble independently of the other classifiers. Experiments were performed on 28 publicly available datasets, using C4.5 release 8 as the base classifier. While each of the other seven approaches has some strengths, we find that none of them is consistently more accurate than standard bagging when tested for statistical significance.
From Canonical Face to Synthesis - An Illumination Invariant Face Recognition Approach

The need to further develop robust face recognition techniques to meet real world requirements is still an open research challenge. It is widely understood that the two main contributions of poor recognition performances are that caused by variations in face pose and lighting. We will deal with the problem of illumination in this chapter. Approaches addressing the illumination-related problems can be broadly classified into two categories; feature-based approach and exemplaror appearancebased approach. Feature-based approaches aim to define a feature space that exhibits some broad invariance over the lighting variations. Examples of these are (Adini & Ullman, 1997), (Belhumeur et al., 1997) and (Yang et al., 2004) which uses different image representations like 2D Gabor-like filters, first and second derivatives of the image, and the logarithmic transformation. Although these features may exhibit intensity immunity, none of these are found to be reliable to cope with significantly large variations in illumination changes (Manjunath et al.1992) (Yang et al., 2004). Exemplaror appearancebased approaches use a set of sample images taken of a class object (in this case a face) as a basis to compute an intermediary image. The intermediate image can then be used either directly as the probe image or be used to synthesize novel views of the face under different lighting conditions (Mariani, 2002). For example, (RiklinRaviv & Shashua, 2001) reported a method to compute the Quotient Image from a small sample of bootstrap images representing a minimum of two class objects. The illumination invariant signature of the Quotient Image enables an analytic generation of the novel image space with varying illumination. However, this technique is highly dependent on the types of bootstrap images used which has the undesirable effect of generating diversely looking Quotient Images even from the same person. (Sim & Kanade, 2001) used a statistical shapefrom-shading model to estimate the 3D face shape from a single image. The 3D recovery model is based on the symmetric shape-from-shading algorithm proposed by (Zhao & Chellappa, 1999). They used the 3D face model to synthesize novel faces under new illumination conditions using computer graphics algorithms. The approach produce high recognition rate on the illumination subset of the CMU PIE database (Sim et al., 2003). However, it was not evident how their synthesis technique can cope with extreme illumination conditions (Sim & Kanade, 2001). (Debevec et al., 2000) presented a method to
Deep-neural network approaches for speech recognition with heterogeneous groups of speakers including children†

Abstract This paper introduces deep neural network (DNN)–hidden Markov model (HMM)-based methods to tackle speech recognition in heterogeneous groups of speakers including children. We target three speaker groups consisting of children, adult males and adult females. Two different kind of approaches are introduced here: approaches based on DNN adaptation and approaches relying on vocal-tract length normalisation (VTLN). First, the recent approach that consists in adapting a general DNN to domain/language specific data is extended to target age/gender groups in the context of DNN–HMM. Then, VTLN is investigated by training a DNN–HMM system by using either mel frequency cepstral coefficients normalised with standard VTLN or mel frequency cepstral coefficients derived acoustic features combined with the posterior probabilities of the VTLN warping factors. In this later, novel, approach the posterior probabilities of the warping factors are obtained with a separate DNN and the decoding can be operated in a single pass when the VTLN approach requires two decoding passes. Finally, the different approaches presented here are combined to take advantage of their complementarity. The combination of several approaches is shown to improve the baseline phone error rate performance by thirty per cent to thirty-five per cent relative and the baseline word error rate performance by about ten per cent relative.
Determination of Zinc, Cadmium and Lead Bioavailability in Contaminated Soils at the Single-Cell Level by a Combination of Whole-Cell Biosensors and Flow Cytometry

Zinc, lead and cadmium are metallic trace elements (MTEs) that are widespread in the environment and tend to accumulate in soils because of their low mobility and non-degradability. The purpose of this work is to evaluate the applicability of biosensors as tools able to provide data about the bioavailability of such MTEs in contaminated soils. Here, we tested the genetically-engineered strain Escherichia coli pPZntAgfp as a biosensor applicable to the detection of zinc, lead and cadmium by the biosynthesis of green fluorescent protein (GFP) accumulating inside the cells. Flow cytometry was used to investigate the fluorescence induced by the MTEs. A curvilinear response to zinc between 0 and 25 mg/L and another curvilinear response to cadmium between 0 and 1.5 mg/L were highlighted in liquid media, while lead did not produce exploitable results. The response relating to a Zn2+/Cd2+ ratio of 10 was further investigated. In these conditions, E. coli pPZntAgfp responded to cadmium only. Several contaminated soils with a Zn2+/Cd2+ ratio of 10 were analyzed with the biosensor, and the metallic concentrations were also measured by atomic absorption spectroscopy. Our results showed that E. coli pPZntAgfp could be used as a monitoring tool for contaminated soils being processed.
The Dirt on Coming Clean: Perverse Effects of Disclosing Conflicts of Interest

Conflicts of interest can lead experts to give biased and corrupt advice. Although disclosure is often proposed as a potential solution to these problems, we show that it can have perverse effects. First, people generally do not discount advice from biased advisors as much as they should, even when advisors’ conflicts of interest are disclosed. Second, disclosure can increase the bias in advice because it leads advisors to feel morally licensed and strategically encouraged to exaggerate their advice even further. As a result, disclosure may fail to solve the problems created by conflicts of interest and may sometimes even make matters worse.
ADAPTIVE ESTIMATION OF HAZARD FUNCTIONS

Abstract: In this paper we obtain convergence rates for sieved maximum -likelihood estimators of the log-hazard function in a censoring model. We also establish convergence results for an adaptive version of the estimator based on the method of structural risk-minimization. Applications are discussed to tensor p roduct spline estimators as well as to neural net and radial basis function sieves. We obt ain simplified bounds in comparison to the known literature. This allows us to derive several new classes of estimators and to obtain improved estimation rates. Our resul ts extend to a more general class of estimation problems and estimation methods (minim um contrast estimators).
Improving crop disease resistance: lessons from research on Arabidopsis and tomato

One of the great challenges for food security in the 21st century is to improve yield stability through the development of disease-resistant crops. Crop research is often hindered by the lack of molecular tools, growth logistics, generation time and detailed genetic annotations, hence the power of model plant species. Our knowledge of plant immunity today has been largely shaped by the use of models, specifically through the use of mutants. We examine the importance of Arabidopsis and tomato as models in the study of plant immunity and how they help us in revealing a detailed and deep understanding of the various layers contributing to the immune system. Here we describe examples of how knowledge from models can be transferred to economically important crops resulting in new tools to enable and accelerate classical plant breeding. We will also discuss how models, and specifically transcriptomics and effectoromics approaches, have contributed to the identification of core components of the defense response which will be key to future engineering of durable and sustainable disease resistance in plants.
A distributed queueing random access protocol for a broadcast channel

For decades there has been a search for a multiple access protocol for a broadcast channel that would provide a performance that approached that of the ideal M/D/1 queue. This ideal performance would provide immediate access at light loads and then seamlessly move to a reservation system at high offered loads. DQRAP (distributed queueing random access protocol) provides a performance which approaches this ideal. Furthermore it is accomplished using as few as three control minislots which suggests that, aside from establishing new theoretical bounds, DQRAP will be of great practical value.DQRAP requires that channel time be divided into slots each of which consists of one data slot and m control minislots, and that each station maintain two common distributed queues. One queue is called the data transmission queue, or simply TQ, used to organize the order of data transmission, the other queue is the collision resolution queue, or simply RQ, which is used to resolve the collisions and to prevent collisions by new arrivals. The protocol includes data transmission rules, request transmission rules and queuing discipline rules. Modelling and simulation indicate that DQRAP, using as few as 3 minislots, achieves a performance level which approaches that of a hypothetical perfect scheduling protocol, i.e., the M/D/1 system, with respect to throughput and delay. DQRAP could prove useful in packet radio, satellite, broadband cable, cellular voice, WAN, and passive optical networks.
Modelling of the photooxidation of toluene: conceptual ideas for validating detailed mechanisms

Abstract. Toluene photooxidation is chosen as an example to examine how simulations of smog-chamber experiments can be used to unravel shortcomings in detailed mechanisms and to provide information on complex reaction systems that will be crucial for the design of future validation experiments. The mechanism used in this study is extracted from the Master Chemical Mechanism Version 3 (MCM v3) and has been updated with new modules for cresol and g-dicarbonyl chemistry. Model simulations are carried out for a toluene-NOx experiment undertaken at the European Photoreactor (EUPHORE). The comparison of the simulation with the experimental data reveals two fundamental shortcomings in the mechanism: OH production is too low by about 80%, and the ozone concentration at the end of the experiment is over-predicted by 55%. The radical budget was analysed to identify the key intermediates governing the radical transformation in the toluene system. Ring-opening products, particularly conjugated g-dicarbonyls, were identified as dominant radical sources in the early stages of the experiment. The analysis of the time evolution of radical production points to a missing OH source that peaks when the system reaches highest reactivity. First generation products are also of major importance for the ozone production in the system. The analysis of the radical budget suggests two options to explain the concurrent under-prediction of OH and over-prediction of ozone in the model: 1) missing oxidation processes that produce or regenerate OH without or with little NO to NO2 conversion or 2) NO3 chemistry that sequesters reactive nitrogen oxides into stable nitrogen compounds and at the same time produces peroxy radicals. Sensitivity analysis was employed to identify significant contributors to ozone production and it is shown how this technique, in combination with ozone isopleth plots, can be used for the design of validation experiments.
Voltage-Activated K+ Channels and Membrane Depolarization Regulate Accumulation of the Cyclin-Dependent Kinase Inhibitors p27Kip1 and p21CIP1 in Glial Progenitor Cells

Neural cell development is regulated by membrane ion channel activity. We have previously demonstrated that cell membrane depolarization with veratridine or blockage of K+channels with tetraethylammonium (TEA) inhibit oligodendrocyte progenitor (OP) proliferation and differentiation (Knutson et al., 1997); however the molecular events involved are largely unknown. Here we show that forskolin (FSK) and its derivative dideoxyforskolin (DFSK) block K+ channels in OPs and inhibit cell proliferation. The antiproliferative effects of TEA, FSK, DFSK, and veratridine were attributable to OP cell cycle arrest in G1 phase. In fact, (1) cyclin D accumulation in synchronized OP cells was not affected by K+ channel blockers or veratridine; (2) these agents prevented OP cell proliferation only if present during G1 phase; and (3) G1 blockers, such as rapamycin and deferoxamine, mimicked the anti-proliferative effects of K+channel blockers. DFSK also prevented OP differentiation, whereas FSK had no effect. Blockage of K+ channels and membrane depolarization also caused accumulation of the cyclin-dependent kinase inhibitors p27Kip1 and p21CIP1 in OP cells. The antiproliferative effects of K+channel blockers and veratridine were still present in OP cells isolated from INK4a−/− mice, lacking the cyclin-dependent kinase inhibitors p16INK4a and p19ARF. Our results demonstrate that blockage of K+ channels and cell depolarization induce G1 arrest in the OP cell cycle through a mechanism that may involve p27Kip1 and p21CIP1 and further support the conclusion that OP cell cycle arrest and differentiation are two uncoupled events.
Wisdom: Its Nature, Origins, And Development

Preface Part I. Approaches to the Study of Wisdom: 1. Understanding wisdom R. J. Sternberg Part II. Approaches Informed by Philosophical Conceptions of Wisdom: 2. Wisdom through the ages D. N. Robinson 3. The psychology of wisdom: an evolutionary interpretation M. Csikszentmihalyi and K. Rathunde 4. Wisdom as integrated thought: historical and developmental perspectives G. Labouvie-Vief Part III. Approaches Informed by Folk Conceptions of Wisdom: 5. Toward a psychology of wisdom and its ontogenesis P. Baltes and J. Smith 6. Wisdom in a post-apocalyptic age M. J. Chandler and S. Holliday 7. Wisdom and its relations to intelligence and creativity R. J. Sternberg 8. Wisdom and the study of wise persons L. Orwoll and M. Parlmutter Part IV. Approaches Informed by Psychodevelopmental Conceptions of Wisdom: 9. The loss of wisdom J. A. Meacham 10. Wisdom and reflective judgment: knowing in the face of uncertainty K. S. Kitchener and H. G. Brenner 11. Wisdom: the art of problem finding P. K. Arlin 12. An essay on wisdom: towards symbolic processes that make it possible J. Pascual-Leone 13. Conceptualising wisdom: the primacy of affect-cognition relations D. Kramer Part V. Integration of Approaches and Viewpoints: 14. Integration J. E. Birren Author index Subject index.
Portfolio Reallocation and Exchange Rate Dynamics

This paper explains exchange rate dynamics by linking financial customers’ foreign exchange order flow with their dynamic portfolio reallocation. For any currency pair in a particular period, one currency has higher assets return than the other and can be considered the high-return-currency (HRC). Financial institutions attempt to hold more HRC assets when they become more risk-loving or the relative return of the assets is expected to increase. Such a portfolio reallocation generates buy order toward the HRC and the currency appreciates. As the HRC changes over time, the direction that the relative return and risk appetite affect the exchange rate varies in different regimes.
COCHCOMO: An extension of COCOMO II for Estimating Effort for Requirement Changes during Software Development Phase

: - Software undergoes changes at all stages of the software development process. Accepting too many changes will cause expense and delay and rejecting the changes may cause customer dissatisfaction. One of the inputs that help the software project management to decide whether to accept or reject the changes is by having a reliable estimation of the change effort. From a software development perspective, the estimation has to take into account the inconsistent states of software artifacts across project lifecycle i.e., fully developed or partially developed. This inconsistent state requires different ways of estimation such as the fully developed artifacts may have different calculation compared to the partially developed artifacts. Many change effort estimation models have been developed and one of them is using impact analysis. One main challenge of this technique from software development perspective is that this technique is specifically used for software maintenance phase in which all software artifacts have been completely developed. This research introduces a new change effort estimation model that is able to use different estimation techniques for different states of software artifacts. The outcome of this research is a new change effort estimation model for software development phase using the extended version of the static and dynamic analysis techniques from our previous works. The significant achievements of the approach are demonstrated through an extensive experimental validation using several case scenarios.
Regulatory Mode and Risk-Taking: The Mediating Role of Anticipated Regret

We propose that decision maker’s regulatory mode affects risk-taking through anticipated regret. In the Study 1 either a locomotion or an assessment orientation were experimentally induced, and in the Studies 2 and 3 these different orientations were assessed as chronic individual differences. To assess risk-taking we used two behavioral measures of risk: BART and hot-CCT. The results show that experimentally induced assessment orientation–compared to locomotion–leads to decreased risk-taking through increased anticipated regret (Study 1). People chronically predisposed to be in the assessment state take less risk through increased anticipated regret (Study 2 and Study 3). Study 2 results also show a marginally non-significant indirect effect of chronic locomotion mode on BART through anticipated regret. Differently, Study 3 shows that people chronically predisposed to be in the locomotion state take greater risk through decreased anticipated regret, when play a dynamic risk task triggering stronger emotional arousal. Through all three studies, the average effect size for the relationship of assessment with anticipated regret was in the moderate-large range, whereas for risk-taking was in the moderate range. The average effect size for the relationship of locomotion with anticipated regret was in the moderate range, whereas for risk-taking was in the small-moderate range. These results increase our understanding of human behavior under conditions of risk obtaining novel insights into regulatory mode theory and decision science.
Universality of random graphs and rainbow embedding

In this paper we show how to use simple partitioning lemmas in order to embed spanning graphs in a typical member of G(n,p) . Let the maximum density of a graph H be the maximum average degree of all the subgraphs of H. First, we show that for p=ω(Δ12n−1/2dlog3n) , a graph G∼G(n,p) w.h. p. contains copies of all spanning graphs H with maximum degree at most Δ and maximum density at most d. For d
A dataset and evaluation methodology for template-based tracking algorithms

Unlike dense stereo, optical flow or multi-view stereo, template-based tracking lacks benchmark datasets allowing a fair comparison between state-of-the-art algorithms. Until now, in order to evaluate objectively and quantitatively the performance and the robustness of template-based tracking algorithms, mainly synthetically generated image sequences were used. The evaluation is therefore often intrinsically biased.
The evaluation of breast masses in women younger than forty years of age.

BACKGROUND Breast masses in young women are common, but carcinoma is rare. This study was undertaken to determine how often a complaint of mass was found to represent a dominant mass and to define the role of breast imaging and fine-needle aspiration cytology (FNA) in the evaluation of clinically nonworrisome masses. METHODS A retrospective review was made of 605 patients younger than 40 years of age with a breast mass between February 1994 and February 1996. RESULTS Dominant masses were confirmed by surgeon examination in 36% of 484 self-detected masses compared with 29% of physician-detected masses (difference not significant). With pathologic confirmation, 29% of self-detected masses had a dominant mass compared with 19% of physician-detected masses (P = .02). Carcinoma was present in 5% of both groups and not predicted by family history. Imaging studies were not useful in patients with normal examinations but were more likely to identify dominant masses in patients with an examination described as benign (P < .001). FNA did not identify any cancers in normal or benign examinations. CONCLUSIONS Self-examination is as reliable as a general physician examination in detecting breast masses. When an examination by an experienced surgeon is normal, imaging studies and FNA are low yield. When the examination is equivocal, directed ultrasonography is a useful adjunct.