Miracle-dz/UniFAR-FTUs huggingface dataset:
Antecedents of Failure for Newly Chartered Banks in the U.S. Banking Industry

In the United States, newly chartered banks are subject to increased regulatory scrutiny during their early years of operation to ensure their long-term viability. As the record number of bank failures in 2009 has shown, this additional regulation does not guarantee success. To better understand the internal factors in this environment that result in organizational distress, an antecedent failure state, the authors focus on the group-level characteristics of the banks’ founding teams, specifically ownership concentration and four explicit types of founding experience. Using a sample of 129 banks based in Florida, they find that increased ownership concentration, prior industry experience, heterogeneous occupational experience and joint prior founding experience and prior shared experience decreases organizational distress. Their results provide direction on characteristics that may help firms avoid organizational distress.
On the sensitivity of the coupled discrete-time Lyapunov equation

The sensitivity of coupled discrete-time Lyapunov equations is analyzed through three types of norms of the inverse Lyapunov-like operator. This analysis leads to bounds on the relative perturbation of the solution. These results extend the results for standard Lyapunov equation presented by Gahinet et al. (1990).
Smart Grid Solution for Charging and Discharging Services Based on Cloud Computing Scheduling

Smart Grid (SG) technology represents an unprecedented opportunity to transfer the energy industry into a new era of reliability, availability, and efficiency that will contribute to our economic and environmental health. On the other hand, the emergence of electric vehicles (EVs) promises to yield multiple benefits to both power and transportation industry sectors, but it is also likely to affect the SG reliability, by consuming massive energy. Nevertheless, the plug-in of EVs at public supply stations must be controlled and scheduled in order to reduce the peak load. This paper considers the problem of plug-in EVs at public supply stations (EVPSS). A new communication architecture for SG and cloud services is introduced. Scheduling algorithms are proposed in order to attribute priority levels and optimize the waiting time to plug-in at each EVPSS. To the best of our knowledge, this is one of the first papers investigating the aforementioned issues using new network architecture for SG based on cloud computing. We evaluate our approach via extensive simulations and compare it with two other recently proposed works, based on real supply energy scenario in Toronto. Simulation results demonstrate the effectiveness of the proposed approach when considering real EVs charging–discharging loads at peak-hours period.
MRI Image-to-Image Translation for Cross-Modality Image Registration and Segmentation

We develop a novel cross-modality generation framework that learns to generate predicted modalities from given modalities in MR images without real acquisition. Our proposed method performs image-to-image translation by means of a deep learning model that leverages conditional generative adversarial networks (cGANs). Our framework jointly exploits the low-level features (pixel-wise information) and high-level representations (e.g. brain tumors, brain structure like gray matter, etc.) between cross modalities which are important for resolving the challenging complexity in brain structures. Based on our proposed framework, we first propose a method for cross-modality registration by fusing the deformation fields to adopt the cross-modality information from predicted modalities. Second, we propose an approach for MRI segmentation, translated multichannel segmentation (TMS), where given modalities, along with predicted modalities, are segmented by fully convolutional networks (FCN) in a multi-channel manner. Both these two methods successfully adopt the cross-modality information to improve the performance without adding any extra data. Experiments demonstrate that our proposed framework advances the state-of-the-art on five MRI datasets. We also observe encouraging results in cross-modality registration and segmentation on some widely adopted datasets. Overall, our work can serve as an auxiliary method in clinical diagnosis and be applied to various tasks in medical fields. Keywords: Image-to-image, cross-modality, registration, segmentation, MRI
Rate-Distortion Optimization of Rate Control for H.264 With Adaptive Initial Quantization Parameter Determination

A rate-distortion (R-D) optimization rate control (RC) algorithm with adaptive initialization is presented for H.264. First, a linear distortion-quantization (D-Q) model is introduced and thus a close-form solution is developed to derive optimal quantization parameters (Qp)for encoding each macroblock. Then we exploit to determine the initial Qp efficiently and adaptively according to the content of video sequences. The experimental results demonstrate that the proposed algorithm can achieve better R-D performance than that of other two RC algorithms including the algorithm JVT-G012 which is the current recommended RC scheme implemented in the H.264 reference software JM9.5.
Performance analysis with LMMSE for MIMO LTE on the High Altitude Platform Station

High Altitude Platform Station (HAPs) is a new communications infrastructure that uses air balloon to carry high data rate service and wide bandwidth. One technique to make it happen is Long Term Evolution (LTE), LTE support capacity increasing, expand coverage area, data rate increasing, low latency, multi-antenna, and can be integrated with other systems. To improve the performance of LTE in capacity building, coverage area and data rate, it can use the multi-antenna techniques both on receiver or transmitter or often called multiple input multiple output (MIMO). To ensure reliability and good performance in achieving high transmission rate, it can use coherent detection which requires knowledge of the channel for accurate channel estimation. In this study, estimation that has been used is the Linear Minimum Mean Square Error (LMMSE). Channel estimation is used to find out information about the channel condition between the transmitter and the receiver so that the performance of Bit Error Rate (BER) increase and expand the coverage area of the same BER compared without estimation. In addition, modulation level, train velocity and Signal to Noise Ratio (SNR) can also affect the amount of BER at the receiver.
An information theoretic approach for privacy metrics

Organizations often need to release microdata without revealing sensitive information. To this scope, data are anonymized and, to assess the quality of the process, various privacy metrics have been proposed, such as k-anonymity, l-diversity, and t-closeness. These metrics are able to capture different aspects of the disclosure risk, imposing minimal requirements on the association of an individual with the sensitive attributes. If we want to combine them in a optimization problem, we need a common framework able to express all these privacy conditions. Previous studies proposed the notion of mutual information to measure the different kinds of disclosure risks and the utility, but, since mutual information is an average quantity, it is not able to completely express these conditions on single records. We introduce here the notion of one-symbol information (i.e., the contribution to mutual information by a single record) that allows to express and compare the disclosure risk metrics. In addition, we obtain a relation between the risk values t and l, which can be used for parameter setting. We also show, by numerical experiments, how l-diversity and t-closeness can be represented in terms of two different, but equally acceptable, conditions on the information gain.
Identifying syntactic differences between two programs

Programmers frequently face the need to identify the differences between two programs, usually two different versions of a program. Text‐based tools such as the UNIXr̀ utility diff often produce unsatisfactory comparisons because they cannot accurately pinpoint the differences and because they sometimes produce irrelevant differences. Since programs have a rigid syntactic structure as described by the grammar of the programming language in which they are written, we develop a comparison algorithm that exploits knowledge of the grammar. The algorithm, which is based on a dynamic programming scheme, can point out the differences between two programs more accurately than previous text comparison tools. Finally, the two programs are pretty‐printed ‘synchronously’ with the differences highlighted so that the differences are easily identified.
Lightning Surge Propagation on a Single Conductor in Free Space

This paper introduces an analysis of lightning surge propagation on a conductor without any returning current path. The conductor can be either a free-space or grounded conductor as long as the reflected surge from the ground has not arrived. Unlike a TEM transmission line, this conductor is characterized with time/position-variant surge impedance as surge current attenuates during its propagation. In this paper, a simplified formula was derived. Using the unique parameter-attenuation coefficient of current-an iterative method was developed to evaluate actual propagation characteristics. This method was verified numerically, and is much more efficient in calculation and easier in implementation. It is found that the surge impedance is affected by the waveform of an impulse current source, but is independent of the slope of a ramp current source. It increases quickly if the source current has a short rising time or failing time. The simplified formula generates overestimated results, but the difference decreases with increasing distance to the source. The proposed method can be used to address surge voltage on the tower upon the arrival of a reflected surge from the ground.
Multi-layered gesture recognition with Kinect

This paper proposes a novel multi-layered gesture recognition method with Kinect. We explore the essential linguistic characters of gestures: the components concurrent character and the sequential organization character, in a multi-layered framework, which extracts features from both the segmented semantic units and the whole gesture sequence and then sequentially classifies the motion, location and shape components. In the first layer, an improved principle motion is applied to model the motion component. In the second layer, a particle-based descriptor and a weighted dynamic time warping are proposed for the location component classification. In the last layer, the spatial path warping is further proposed to classify the shape component represented by unclosed shape context. The proposed method can obtain relatively high performance for one-shot learning gesture recognition on the ChaLearn Gesture Dataset comprising more than 50, 000 gesture sequences recorded with Kinect.
Bidding By Empirical Bayesians In Sealed Bid First Price Auctions

first price auctions, bidding strategies, independent private values, econometrics of auctions In Bayesian-Nash equilibrium formulations of auctions the bidders are assumed to know all the relevant structural elements of the game they are in. We investigate the empirical implications for bidding behavior of weakening this assumption in the context of sealed bid first price auctions. We study a model in which the bidders are assumed to estimate the unknown distributions that affect their payoff function by processing bids on same or similar items in previous auctions. We present Monte Carlo experimental results on the distribution of bidding strategies when a bidder substitutes the empirical analog of the unknown distribution of bids by the rivals. We also explore the performance of Bayesian-Nash equilibrium based empir ical approach to estimate the unknown distribution of bidder valuations when the proposed behavioral model rather than a Bayesian-Nash equilibrium process generates the observed bid data.
Securing the World and Challenging Civil Society: Before and After the ‘War on Terror’

Following President Bush's declaration of a ‘War on Terror’ in 2001, governments around the world introduced a range of counter-terrorist legislation, policies and practices. These measures have affected not only human rights and civil liberties but also civil society and aid frameworks. Although the Obama administration has renounced the language of the ‘War on Terror’ and taken steps to revoke aspects such as water-boarding and the detention facility at Guantanamo Bay, the bulk of the legislation and practices associated with the post-9/11 global security framework remain. The cluster of papers which follow provide detailed studies of the effects of the War on Terror regime on civil society in four contexts: the USA, Spain, Kenya and Uzbekistan. In this way it lays a basis for civil society actors and aid agencies to reflect more strategically on how they should engage with security debates and initiatives in a way that best protects the spaces of civil society and the interests of minority and vulnerable groups. This introduction sets out the three key themes pursued throughout the cluster articles, namely, the selective impact of counter-terrorist measures on civil society; the particularity of civil society responsiveness to these measures; and the role of aid and diplomacy in pursuing security objectives and its consequences for civil society.
High energy electron fluxes in dc-augmented capacitively coupled plasmas I. Fundamental characteristics

Power deposition from electrons in capacitively coupled plasmas (CCPs) has components from stochastic heating, Joule heating, and from the acceleration of secondary electrons through sheaths produced by ion, electron, or photon bombardment of electrodes. The sheath accelerated electrons can produce high energy beams which, in addition to producing excitation and ionization in the gas can penetrate through the plasma and be incident on the opposite electrode. In the use of CCPs for microelectronics fabrication, there may be an advantage to having these high energy electrons interact with the wafer. To control the energy and increase the flux of the high energy electrons, a dc bias can be externally imposed on the electrode opposite the wafer, thereby producing a dc-augmented CCP (dc-CCP). In this paper, the characteristics of dc-CCPs will be discussed using results from a computational study. We found that for a given rf bias power, beams of high energy electrons having a narrow angular spread (<1°) can be.
Challenging Islamophobia Through Visual Media Studies: Inquiring Into a Photograph of Muslim Women on the Cover of Canada's National News Magazine

Diane Watt is a PhD candidate in the Faculty of Education at the University of Ottawa. She spent much of the decade of the 1990's living with her husband and children in Pakistan, Syria, and Iran. Her research interests include intercultural education, curriculum studies, and media education. Funding for her research has been provided by the Social Sciences and Humanities Research Council of Canada.
Interspecific synchrony of seabird population growth rate and breeding success

Environmental variability can destabilize communities by causing correlated interspecific fluctuations that weaken the portfolio effect, yet evidence of such a mechanism is rare in natural systems. Here, we ask whether the population dynamics of similar sympatric species of a seabird breeding community are synchronized, and if these species have similar exceptional responses to environmental variation. We used a 24-year time series of the breeding success and population growth rate of a marine top predator species group to assess the degree of synchrony between species demography. We then developed a novel method to examine the species group – all species combined – response to environmental variability, in particular, whether multiple species experience similar, pronounced fluctuations in their demography. Multiple species were positively correlated in breeding success and growth rate. Evidence of “exceptional” years was found, where the species group experienced pronounced fluctuations in their demography. The synchronous response of the species group was negatively correlated with winter sea surface temperature of the preceding year for both growth rate and breeding success. We present evidence for synchronous, exceptional responses of a species group that are driven by environmental variation. Such species covariation destabilizes communities by reducing the portfolio effect, and such exceptional responses may increase the risk of a state change in this community. Our understanding of the future responses to environmental change requires an increased focus on the short-term fluctuations in demography that are driven by extreme environmental variability.
A Frame Rate Optimization Framework for Improving Continuity in Video Streaming

This paper aims to reduce the prebuffering requirements, while maintaining continuity, for video streaming. Current approaches do this by making use of adaptive media playout (AMP) to reduce the playout rate. However, this introduces playout distortion to the viewers and increases the viewing latency. We approach this by proposing a frame rate optimization framework that adjusts both the encoder frame generation rate and the decoder playout frame rate. Firstly, we model this problem as the joint adjustment of the encoder frame generation interval and the decoder playout frame interval. This model is used with a discontinuity penalty virtual buffer to track the accumulated difference between the receiving frame interval and the playout frame interval. We then apply Lyapunov optimization to the model to systematically derive a pair of decoupled optimization policies. We show that the occupancy of the discontinuity penalty virtual buffer is correlated to the video discontinuity and that this framework produces a very low playout distortion in addition to a significant reduction in the prebuffering requirements compared to existing approaches. Secondly, we introduced a delay constraint into the framework by using a delay accumulator virtual buffer. Simulation results show that the delay constrained framework provides a superior tradeoff between the video quality and the delay introduced compared to the existing approach. Finally, we analyzed the impact of delayed feedback between the receiver and the sender on the optimization policies. We show that the delayed feedbacks have a minimal impact on the optimization policies.
Blind Pilot Decontamination

A subspace projection to improve channel estimation in massive multi-antenna systems is proposed and analyzed. Together with power-controlled hand-off, it can mitigate the pilot contamination problem without the need for coordination among cells. The proposed method is blind in the sense that it does not require pilot data to find the appropriate subspace. It is based on the theory of large random matrices that predicts that the eigenvalue spectra of large sample covariance matrices can asymptotically decompose into disjoint bulks as the matrix size grows large. Random matrix and free probability theory are utilized to predict under which system parameters such a bulk decomposition takes place. Simulation results are provided to confirm that the proposed method outperforms conventional linear channel estimation if bulk separation occurs.
Peroxidases identified in a subtractive cDNA library approach show tissue-specific transcript abundance and enzyme activity during seed germination of Lepidium sativum

The micropylar endosperm is a major regulator of seed germination in endospermic species, to which the close Brassicaceae relatives Arabidopsis thaliana and Lepidium sativum (cress) belong. Cress seeds are about 20 times larger than the seeds of Arabidopsis. This advantage was used to construct a tissue-specific subtractive cDNA library of transcripts that are up-regulated late in the germination process specifically in the micropylar endosperm of cress seeds. The library showed that a number of transcripts known to be up-regulated late during germination are up-regulated in the micropylar endosperm cap. Detailed germination kinetics of SALK lines carrying insertions in genes present in our library showed that the identified transcripts do indeed play roles during germination. Three peroxidases were present in the library. These peroxidases were identified as orthologues of Arabidopsis AtAPX01, AtPrx16, and AtPrxIIE. The corresponding SALK lines displayed significant germination phenotypes. Their transcripts were quantified in specific cress seed tissues during germination in the presence and absence of ABA and they were found to be regulated in a tissue-specific manner. Peroxidase activity, and particularly its regulation by ABA, also differed between radicles and micropylar endosperm caps. Possible implications of this tissue-specificity are discussed.
Optimising Drug Solubilisation in Amorphous Polymer Dispersions: Rational Selection of Hot-melt Extrusion Processing Parameters

The aim of this article was to construct a T–ϕ phase diagram for a model drug (FD) and amorphous polymer (Eudragit® EPO) and to use this information to understand the impact of how temperature–composition coordinates influenced the final properties of the extrudate. Defining process boundaries and understanding drug solubility in polymeric carriers is of utmost importance and will help in the successful manufacture of new delivery platforms for BCS class II drugs. Physically mixed felodipine (FD)–Eudragit® EPO (EPO) binary mixtures with pre-determined weight fractions were analysed using DSC to measure the endset of melting and glass transition temperature. Extrudates of 10 wt% FD–EPO were processed using temperatures (110°C, 126°C, 140°C and 150°C) selected from the temperature–composition (T–ϕ) phase diagrams and processing screw speed of 20, 100 and 200rpm. Extrudates were characterised using powder X-ray diffraction (PXRD), optical, polarised light and Raman microscopy. To ensure formation of a binary amorphous drug dispersion (ADD) at a specific composition, HME processing temperatures should at least be equal to, or exceed, the corresponding temperature value on the liquid–solid curve in a F–H T–ϕ phase diagram. If extruded between the spinodal and liquid–solid curve, the lack of thermodynamic forces to attain complete drug amorphisation may be compensated for through the use of an increased screw speed. Constructing F–H T–ϕ phase diagrams are valuable not only in the understanding drug–polymer miscibility behaviour but also in rationalising the selection of important processing parameters for HME to ensure miscibility of drug and polymer.
Four-stranded DNA structure stabilized by a novel G:C:A:T tetrad.

The solution structure of a cyclic oligonucleotide d has been determined by two-dimensional NMR spectroscopy and restrained molecular dynamics. Under the appropriate experimental conditions, this molecule self-associates, forming a symmetric dimer stabilized by four intermolecular Watson-Crick base pairs. The resulting four-stranded structure consists of two G:C:A:T tetrads, formed by facing the minor groove side of the Watson-Crick base-pairs. Most probably, the association of the base-pairs is stabilized by coordinating a Na(+) cation. This is the first time that this novel G:C:A:T tetrad has been found in an oligonucleotide structure. This observation increases considerably the number of sequences that may adopt a four-stranded architecture. Overall, the three-dimensional structure is similar to those observed previously in other quadruplexes formed by minor groove alignment of Watson-Crick base pairs. This resemblance strongly suggests that we may be observing a general motif for DNA-DNA recognition.