Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Semantic Image Representations at a Large Scale

I present my work towards learning a better computer vision system that learns and generalizes object categories better, and behaves in ways closer to what human behave. Specifically, I focus on two key components of such a system: learning better features, and revisiting existing problem statements. For the first component, I propose and analyze novel receptive field learning and dictionary learning methods, mathematically justified by the \nystrom sampling theory, that learn more compact and effective features for object recognition tasks. For the second component, I propose to combine otherwise independently developed computer vision and cognitive science studies, and present the first large-scale system that allows computers to learn and generalize closer to what a human learner will do. I also provide a large-scale human behavior database, which will hopefully enable further research along this research direction.Following the recent success of convolutional neural networks, I present and release a well-engineered framework for general deep learning research, and provide an extensive analysis on the generality of deep features learned from the state-of-the-art CNN pipeline: whether they serve as a general-purpose visual descriptor that could be adopted in various applications, and future research directions made possible by such general features.
Saliency Detection: A Spectral Residual Approach

The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent behavior still remains a challenge. This paper presents a simple method for the visual saliency detection. Our model is independent of features, categories, or other forms of prior knowledge of the objects. By analyzing the log-spectrum of an input image, we extract the spectral residual of an image in spectral domain, and propose a fast method to construct the corresponding saliency map in spatial domain. We test this model on both natural pictures and artificial images such as psychological patterns. The result indicate fast and robust saliency detection of our method.
Influence Maximization with Bandits

We consider the problem of \emph{influence maximization}, the problem of maximizing the number of people that become aware of a product by finding the `best' set of `seed' users to expose the product to. Most prior work on this topic assumes that we know the probability of each user influencing each other user, or we have data that lets us estimate these influences. However, this information is typically not initially available or is difficult to obtain. To avoid this assumption, we adopt a combinatorial multi-armed bandit paradigm that estimates the influence probabilities as we sequentially try different seed sets. We establish bounds on the performance of this procedure under the existing edge-level feedback as well as a novel and more realistic node-level feedback. Beyond our theoretical results, we describe a practical implementation and experimentally demonstrate its efficiency and effectiveness on four real datasets.
The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling model

Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods.
Shareholder Wealth Maximization and Social Welfare: A Utilitarian Critique

ABSTRACT: Many scholars and managers endorse the idea that the primary purpose of the firm is to make money for its owners. This shareholder wealth maximization objective is justified on the grounds that it maximizes social welfare. In this article, the first of a two-part set, we argue that, although this shareholder primacy model may have been appropriate in an earlier era, it no longer is, given our current state of economic and social affairs. To make our case, we employ a utilitarian moral standard and examine the apparent logical sequence behind the link between shareholder wealth maximization and social welfare. Upon close empirical and conceptual scrutiny, we find that utilitarian criteria do not support the shareholder model; that is, shareholder wealth maximization is only weakly linked to social welfare maximization. In view of the dubious validity of this sequential argument, we outline some of the features of a superior corporate objective—a variant of normative stakeholder theory. In the second article, we will advance and defend our preferred alternative and then discuss some institutional arrangements under which it could be implemented.
Resolving the Fe XXV Triplet with Chandra in Centaurus X-3

We present the results of a 45 ks Chandra observation of the high-mass X-ray binary Cen X-3 at orbital phases between 0.13 and 0.40 (in the eclipse post-egress phases). Here we concentrate on the study of discrete features in the energy spectrum at energies between 6 and 7 keV, that is, on the iron Kα line region, using the High Energy Transmission Grating Spectrometer (HETGS) on board the Chandra satellite. We clearly see a Kα neutral iron line at ~6.40 keV and were able to distinguish the three lines of the Fe XXV triplet at 6.61, 6.67, and 6.72 keV, with equivalent widths of 6, 9, and 5 eV, respectively. The equivalent width of the Kα neutral iron line is 13 eV, an order of magnitude lower than previous measures. We discuss the possibility that the small equivalent width is due to a decrease of the solid angle subtended by the reflector.
The Clifford Algebra Approach to Quantum Mechanics B: The Dirac Particle and its relation to the Bohm Approach

In this paper we present for the first time a complete description of the Bohm model of the Dirac particle. This result demonstrates again that the common perception that it is not possible to construct a fully relativistic version of the Bohm approach is incorrect. We obtain the fully relativistic version by using an approach based on Clifford algebras outlined in two earlier papers by Hiley and by Hiley and Callaghan. The relativistic model is different from the one originally proposed by Bohm and Hiley and by Doran and Lasenby. We obtain exact expressions for the Bohm energy-momentum density, a relativistic quantum Hamilton-Jacobi for the conservation of energy which includes an expression for the quantum potential and a relativistic time development equation for the spin vectors of the particle. We then show that these reduce to the corresponding non-relativistic expressions for the Pauli particle which have already been derived by Bohm, Schiller and Tiomno and in more general form by Hiley and Callaghan. In contrast to the original presentations, there is no need to appeal to classical mechanics at any stage of the development of the formalism. All the results for the Dirac, Pauli and Schroedinger cases are shown to emerge respectively from the hierarchy of Clifford algebras C(13),C(30), C(01) taken over the reals as Hestenes has already argued. Thus quantum mechanics is emerging from one mathematical structure with no need to appeal to an external Hilbert space with wave functions.
Empirical Calibration of the near-IR Ca II triplet – IV . The stellar population synthesis models

We present a new evolutionary stellar population synthesis model, which predicts SEDs for single-age single-metallicity stellar populations, SSPs, at resolution 1. 5Å (FWHM) in the spectral region of the near-IR Ca ii triplet feature. The main ingredient of the model is a new extensive empirical stellar spectral library that has been recently presented in Cenarro et al. (2001a,b; 2002), which is composed of more than 600 stars with an unprecedented coverage of the stellar atmospheric parameters. Two main products of interest for stellar population analysis are presented. The first is a spectral library for SSPs with metallicities −1.7<[Fe/H]<+0.2, a large range of ages (0.1-18 Gyr) and IMF types. They are well suited to model galaxy data, since the SSP spectra, with flux-calibrated response curves, can be smoothed to the resolution of the observational data, taking into account the internal velocity dispersion of the galaxy, allowing the user to analyze the observed spectrum in its own system. We also produce integrated absorption line indices (namely CaT∗, CaT and PaT) for the same SSPs in the form of equivalent widths. We find the following behaviour for the Ca ii triplet feature in old-aged SSPs: i) the strength of the CaT∗ index does not change much with time for all metallicities for ages larger than ∼3 Gyr, ii) this index shows a strong dependence with metallicity for values below [M/H] ∼ −0.5 and iii) for larger metallicities this feature does not show a significant dependence either on age or on the metallicity, being more sensitive to changes in the slope of power-like IMF shapes. The SSP spectra have been calibrated with measurements for globular clusters of Armandroff & Zinn (1988), which are well reproduced, probing the validity of using the integrated Ca ii triplet feature for determining the metallicities of these systems. Fitting the models to two early-type galaxies of different luminosities (NGC 4478 and NGC 4365), we find that the Ca ii triplet measurements cannot be fitted unless a very dwarf-dominated IMF is imposed, or if the Ca abundance is even lower than the Fe abundance. More details can be found in Cenarro et al. (2003).
Comparison of the Martian thermospheric density and temperature from IUVS/MAVEN data and general circulation modeling

The Mars Atmosphere and Volatile Evolution (MAVEN) Mission, which operates for slightly over one year to date, has been specifically designed for investigating the upper atmosphere. The Imaging Ultraviolet Spectrograph (IUVS) onboard MAVEN measures spectra of mid- and far UV atmospheric emission, which are used for retrieving vertical density profiles of CO2 and other species. Newly released IUVS/MAVEN measurements of CO2 density in the Martian thermosphere have been used for comparison with the predictions of the Max Planck Institute Martian General Circulation Model (MPI-MGCM). In this study, we focus on the October 2014 campaign in which a total of 122 density profiles were obtained for the period between 18 and 22 October (Ls=216.68-218.94). IUVS nicely covers the thermosphere in the altitude range of 130-220 km. The MGCM demonstrated the sensitivity of simulated density and temperature profiles on (i) solar flux, (ii) atomic oxygen, and (iii) small-scale gravity waves (GWs). It is the only MGCM to date that includes a parameterization of effects of subgrid-scale GWs with broad spectra. The simulations reproduced (within one standard deviation) the available zonal mean density and derived temperature above 130 km. The comparison shows a great role of gravity waves in the thermosphere, and in bringing the simulated density and
Multimodal Expressions of Stress during a Public Speaking Task: Collection, Annotation and Global Analyses

Databases of spontaneous multimodal expressions of affective states occurring during a task are few. This paper presents a protocol for eliciting stress in a public speaking task. Behaviors of 19 participants were recorded via a multimodal setup including speech, video of the facial expressions and body movements, balance via a force plate, and physiological measures. Questionnaires were used to assert emotional states, personality profiles and relevant coping behaviors to study how participants cope with stressful situations. Several subjective and objective performances were also evaluated. Results show a significant impact of the overall task and conditions on the participants' emotional activation. The possible future use of this new multimodal emotional corpus is described.
Narratives in Political Advertising: An Analysis of the Political Advertisements in the 2014 Midterm Elections

This study examined the use of narrative political advertisements during the 2014 midterm elections. A content analysis of 243 ads identified three narratives types: autobiographical, voter stories, and testimonials. Narrative ads were mostly positive and focused almost equally on issues and candidates’ characters. Negative attack ads and anonymous announcers were primarily used by candidates who lost the election, whereas winners employed more often autobiographical spots and included family members in the ads. The growing use of narratives in political advertising as found in the present study suggests that future research should further examine the effects of narrative political ads on individuals.
Use of multiple alignments in protein secondary structure prediction

Using a new database of 20 proteins not included in any of the previously used training datasets, we have incorporated multiple alignment information from homologous proteins into two well-characterized prediction methods: COMBINE (a jury method) and the Q-L (or quadratic-logistic) method. It is found that the increase in accuracy from the use of related proteins is similar for both methods (5.8% and 6.3%, respectively) yielding a per residue prediction accuracy (Q3) of 68.7% and 69.0%, respectively, for a three state prediction. Most of the improvement came from consideration of averaging, profiling or consensus predictions. Of this improvement, a small amount (0.5%) came from recognition that "gap-permissive" positions in the alignment are most frequently in the coil state. Our finding is consistent with the hypothesis of a common secondary structure for the aligned family, and that improved accuracy is due to reduced noise in the prediction. <<ETX>>
Global cancer statistics

The global burden of cancer continues to increase largely because of the aging and growth of the world population alongside an increasing adoption of cancer‐causing behaviors, particularly smoking, in economically developing countries. Based on the GLOBOCAN 2008 estimates, about 12.7 million cancer cases and 7.6 million cancer deaths are estimated to have occurred in 2008; of these, 56% of the cases and 64% of the deaths occurred in the economically developing world. Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females, accounting for 23% of the total cancer cases and 14% of the cancer deaths. Lung cancer is the leading cancer site in males, comprising 17% of the total new cancer cases and 23% of the total cancer deaths. Breast cancer is now also the leading cause of cancer death among females in economically developing countries, a shift from the previous decade during which the most common cause of cancer death was cervical cancer. Further, the mortality burden for lung cancer among females in developing countries is as high as the burden for cervical cancer, with each accounting for 11% of the total female cancer deaths. Although overall cancer incidence rates in the developing world are half those seen in the developed world in both sexes, the overall cancer mortality rates are generally similar. Cancer survival tends to be poorer in developing countries, most likely because of a combination of a late stage at diagnosis and limited access to timely and standard treatment. A substantial proportion of the worldwide burden of cancer could be prevented through the application of existing cancer control knowledge and by implementing programs for tobacco control, vaccination (for liver and cervical cancers), and early detection and treatment, as well as public health campaigns promoting physical activity and a healthier dietary intake. Clinicians, public health professionals, and policy makers can play an active role in accelerating the application of such interventions globally. CA Cancer J Clin 2011. © 2011 American Cancer Society, Inc.
Detail preserving median based filter for impulse noise removal in digital images

In this paper, a new nonlinear filter called detail preserving median based filter for removing salt and pepper noise and random valued impulse noise with edge and detail preservation is presented. The proposed method first detects the impulse pixel based on threshold values and then the corrupted pixels are replaced by the median value of the uncorrupted pixels in the filtering window. Since the proposed algorithm takes a decision whether the pixel under test is corrupted or not, it works well upto a noise density as high as 70% with much lower computation time compared to the other standard techniques. Experimental results clearly indicate that the proposed method outperforms many of the existing methods such as standard median filter, weighted median filter, center weighted median filter, recursive weighted median filter, progressive switching median filter, and recently proposed decision based algorithm in terms of visual quality and quantitative measures.
DNA Microarray Platform for Detection and Surveillance of Viruses Transmitted by Small Mammals and Arthropods

Viruses transmitted by small mammals and arthropods serve as global threats to humans. Most emergent and re-emergent viral agents are transmitted by these groups; therefore, the development of high-throughput screening methods for the detection and surveillance of such viruses is of great interest. In this study, we describe a DNA microarray platform that can be used for screening all viruses transmitted by small mammals and arthropods (SMAvirusChip) with nucleotide sequences that have been deposited in the GenBank. SMAvirusChip was designed with more than 15,000 oligonucleotide probes (60-mers), including viral and control probes. Two SMAvirusChip versions were designed: SMAvirusChip v1 contains 4209 viral probes for the detection of 409 viruses, while SMAvirusChip v2 contains 4943 probes for the detection of 416 viruses. SMAvirusChip was evaluated with 20 laboratory reference-strain viruses. These viruses could be specifically detected when alone in a sample or when artificially mixed within a single sample. The sensitivity of SMAvirusChip was evaluated using 10-fold serial dilutions of dengue virus (DENV). The results showed a detection limit as low as 2.6E3 RNA copies/mL. Additionally, the sensitivity was one log10 lower (2.6E2 RNA copies/mL) than quantitative real-time RT-PCR and sufficient to detect viral genomes in clinical samples. The detection of DENV in serum samples of DENV-infected patients (n = 6) and in a whole blood sample spiked with DENV confirmed the applicability of SMAvirusChip for the detection of viruses in clinical samples. In addition, in a pool of mosquito samples spiked with DENV, the virus was also detectable. SMAvirusChip was able to specifically detect viruses in cell cultures, serum samples, total blood samples and a pool of mosquitoes, confirming that cellular RNA/DNA did not interfere with the assay. Therefore, SMAvirusChip may represent an innovative surveillance method for the rapid identification of viruses transmitted by small mammals and arthropods.
Fast detection of extrasynaptic GABA with a whole-cell sniffer

Gamma-amino-butyric acid (GABA) is the main inhibitory transmitter of the brain. It operates by binding to specific receptors located both inside and outside synapses. The extrasynaptic receptors are activated by spillover from GABAergic synapses and by ambient GABA in the extracellular space. Ambient GABA is essential for adjusting the excitability of neurons. However, due to the lack of suitable methods, little is known about its dynamics. Here we describe a new technique that allows detection of GABA transients and measurement of the steady state GABA concentration with high spatial and temporal resolution. We used a human embryonic kidney (HEK) cell line that stably expresses GABAA receptors composed of α1, β2, and γ2 subunits. We recorded from such a HEK cell with the whole-cell patch-clamp technique. The presence of GABA near the HEK cell generated a measurable electric current whose magnitude increased with concentration. A fraction of the current did not inactivate during prolonged exposition to GABA. This technique, which we refer to as a “sniffer” allows the measurement of ambient GABA concentration inside nervous tissue with a resolution of few tens of nanomolars. In addition, the sniffer detects variations in the extrasynaptic GABA concentration with millisecond time resolution. Pilot experiments demonstrate that the sniffer is able to report spillover of GABA induced by synaptic activation in real time. This is the first report on a GABA sensor that combines the ability to detect fast transients and to measure steady concentrations.
Collaborative writing in Arabic as a second language (ASL) classrooms: A mixed-method study

ABSTRACT The study reported in this article investigated the processes and the effects of collaborative writing on 64 students’ writing skills in two Arabic as a second language (ASL) teachers’ classrooms. The authors employed a mixed methods approach that integrated a qualitative case study and a quasi-experimental design. The data collected included classroom observations and audiotapes of verbal interactions. Pre- and post-test scores of students in collaborative (experimental) writing groups and in traditional (control) groups were compared. The findings indicated variations in interaction patterns during collaborative writing activities in both groups. The findings also suggest that there was a statistically significant difference between the scores of the experimental and the control groups which may be attributed to the collaborative writing intervention.