Miracle-dz/UniFAR-FTUs huggingface dataset:
Managers: Their Effects on Accruals and Firm Policies

This paper investigates whether top executives have significant individual-specific effects on accruals that cannot be explained by firm characteristics. Exploiting 37 years of individual executive and firm data, we find that individual executives play a significant role in determining firms’ accruals. We examine whether executives’ effects on accruals are related to their personal styles on firm policies, investment, financing and operating decisions. Our results show that individual executives’ effects on accruals are more correlated with their operating decisions than investment and financing decisions. We next investigate whether managers also have a personal style for directly affecting accruals, themselves. We compare effects exerted by CEOs to CFOs. We find CEOs are more likely to affect accruals through firm policy decisions and CFOs are more likely to affect accruals through accounting decisions. CFOs tend to report more “solid” earnings than CEOs, i.e., CFOs are more likely to push accruals to zero.
SCADS: Scale-Independent Storage for Social Computing Applications

Collaborative web applications such as Facebook, Flickr and Yelp present new challenges for storing and querying large amounts of data. As users and developers are focused more on performance than single copy consistency or the ability to perform ad-hoc queries, there exists an opportunity for a highly-scalable system tailored specifically for relaxed consistency and pre-computed queries. The Web 2.0 development model demands the ability to both rapidly deploy new features and automatically scale with the number of users. There have been many successful distributed key-value stores, but so far none provide as rich a query language as SQL. We propose a new architecture, SCADS, that allows the developer to declaratively state application specific consistency requirements, takes advantage of utility computing to provide cost effective scale-up and scale-down, and will use machine learning models to introspectively anticipate performance problems and predict the resource requirements of new queries before execution.
Virtual-MIMO-Boosted Information Propagation on Highways

In vehicular communications, traffic-related information should be spread over the network as quickly as possible to maintain a safer transportation system. This motivates us to develop more efficient information propagation schemes. In this paper, we propose a novel virtual-MIMO-enabled information dissemination scheme in which the vehicles opportunistically form virtual antenna arrays to boost the transmission range, and therefore, accelerate information propagation along the highway. We model the information propagation process as a renewal reward process and investigate in detail the information propagation speed (IPS) of the proposed scheme. The corresponding closed-form IPS is derived, which shows that the IPS increases cubically with the vehicle density but will ultimately converge to a constant upper bound. Moreover, increased mobility also facilitates the information spreading by offering more communication opportunities. However, the limited network density essentially determines the bottleneck in information spreading. Extensive simulations are carried out to verify our analysis. We also show that the proposed scheme exhibits a significant IPS gain over its conventional counterpart.
Online Review Spam Detection using Language Model and Feature Selection

In today’s age of web 2.0, large numbers of product reviews posted on the Internet. Such reviews are important to customers or users and to companies. Customers use the reviews for deciding quality of product to buy. Companies or vendors use opinions to take a decision to improve their sales according to intelligent things done by other competitors. However, all reviews are given by customers or users are not true reviews. These reviews are given to promote or to demote the product. Some reviews are given on brand of product, and others are related to advertising of another product. There is need to find how many reviews are spam or non spam. In this paper, the system is proposed for detecting untruthful spam reviews using n-gram language model and reviews on brand spam detection using Feature Selection. Given system separately identifies spam and joined the result showing spam and non spam reviews.
Green Tea Extract Treatment Alleviates Ocular Inflammation in a Rat Model of Endotoxin-Induced Uveitis

Green tea extract (GTE) ingested by rats exerted anti-oxidative activities in various ocular tissues as shown in our previous studies. The present work investigated anti-inflammatory effects of GTE on endotoxin-induced uveitis (EIU). EIU was generated in adult rats by a footpad injection of 1 mg/kg lipopolysaccharide (LPS). Oral administration of GTE (550 mg/kg) was given one, two or four times after LPS injection. Twenty-four hours later, LPS produced severe hyperemia and edema in the iris. Immunocytochemical examinations showed an accumulation of infiltrating cells in the aqueous humor that were immunopositive for cluster of differentiation 43 (CD43) and CD68, markers for leucocytes and macrophages, respectively. Analyses of the aqueous humor showed an increase in pro-inflammatory mediators including tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and monocyte chemoattractant protein-1 (MCP-1). GTE treatments improved the clinical manifestations and reduced infiltrating cells and protein exudation in the aqueous humor, which were not observed under half dose of GTE (275 mg/kg). The number of CD68 positive macrophages residing in the iris and ciliary was also reduced. GTE suppressed production of TNF-α, IL-6 and MCP-1 in the aqueous humor, which was associated with a down-regulation of LPS receptor complex subunits, Toll-like receptor 4 (TLR-4) and CD14, and suppression of nuclear factor-kappa Bp65 (NF-κBp65) in the iris and ciliary body. Our findings show that GTE is a potent anti-inflammatory agent against the inflammation of EIU, and suggest a potential use in treatment of acute uveitis.
Resurrection of Anolis ustus Cope, 1864 from synonymy with Anolis sericeus Hallowell, 1856 (Squamata, Dactyloidae)

Abstract In this study, based on a morphological analysis, the resurrection of the name Anolis ustus Cope 1864, is proposed for populations from the Yucatán Peninsula (Campeche, Yucatán, and Quintana Roo, Mexico, and Belize), formerly referred as Anolis sericeus Hallowell, 1856. Anolis ustus differs from Anolis sericeus by its mean snout-vent length and number of gorgetal scales in males, in tibia length and head width in females, and dorsal and ventral scales for both sexes. In addition, Anolis ustus has a small dewlap of similar size between males and females, whereas in Anolis sericeus males have a dewlap much larger than that of the females. These characteristics allow Anolis ustus to be identified within the Anolis sericeus complex. In this study, a description of the characteristics of the hemipenis is also provided, and its importance in the taxonomy of Anolis is discussed.
The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms

Following the events of September 11, 2001, in the United States, world public awareness for possible terrorist attacks on water supply systems has increased dramatically. Among the different threats for a water distribution system, the most difficult to address is a deliberate chemical or biological contaminant injection, due to both the uncertainty of the type of injected contaminant and its consequences, and the uncertainty of the time and location of the injection. An online contaminant monitoring system is considered as a major opportunity to protect against the impacts of a deliberate contaminant intrusion. However, although optimization models and solution algorithms have been developed for locating sensors, little is known about how these design algorithms compare to the efforts of human designers, and thus, the advantages they propose for practical design of sensor networks. To explore these issues, the Battle of the Water Sensor Networks (BWSN) was undertaken as part of the 8th Annual Water Dist.
Eigenfrequencies of a Truncated Conical Resonator via the Classical and Wentzel–Kramers–Brillouin Methods

The eigenfrequencies within a truncated conical cavity resonator have similarities to the eigenfrequencies within both the cylindrical and spherical cavity resonators. This paper first find the family of eigenfrequencies of the truncated conical cavity resonator by solving the classical boundary value problem in the spherical coordinate system, similar to a spherical cavity resonator. Next, eigenfrequencies for the truncated conical resonator are found via the cylindrical coordinate system using the Wentzel-Kramers-Brillouin (WKB) method by making the approximation that the truncated conical cavity with a small half-cone angle is a cylindrical cavity with linearly sloping walls. While the WKB method is an approximation to the actual eigenfrequencies, the solution yielded by this method is far more simple than the solution yielded by the classical boundary value method. Resonant frequencies are derived via both methods and are compared to each other and to measurements made in an experimental truncated conical cavity platform, displaying a very good agreement.
Building Large-Scale Twitter-Specific Sentiment Lexicon : A Representation Learning Approach

In this paper, we propose to build large-scale sentiment lexicon from Twitter with a representation learning approach. We cast sentiment lexicon learning as a phrase-level sentiment classification task. The challenges are developing effective feature representation of phrases and obtaining training data with minor manual annotations for building the sentiment classifier. Specifically, we develop a dedicated neural architecture and integrate the sentiment information of text (e.g. sentences or tweets) into its hybrid loss function for learning sentiment-specific phrase embedding (SSPE). The neural network is trained from massive tweets collected with positive and negative emoticons, without any manual annotation. Furthermore, we introduce the Urban Dictionary to expand a small number of sentiment seeds to obtain more training data for building the phrase-level sentiment classifier. We evaluate our sentiment lexicon (TS-Lex) by applying it in a supervised learning framework for Twitter sentiment classification. Experiment results on the benchmark dataset of SemEval 2013 show that, TS-Lex yields better performance than previously introduced sentiment lexicons.
Duties in the wake of atrocity: a normative analysis of post-atrocity peacebuilding

Over the last two decades, the international community has taken on the task of rebuilding societies in the aftermath of mass-atrocities. Through a combination of trial and error and vigorous academic research, a relatively clear (and semi-malleable) blueprint of post-atrocity peacebuilding has developed. This includes setting up a temporary international transitional authority, establishing democracy, facilitating economic development, and holding war crime trials. Though there are volumes of studies which address the pragmatic strengths and weaknesses of these key elements of peacebuilding, to date political theorists have not critically analyzed the moral legitimacy of these policies. My thesis aims to fill this gap. The overarching question of this thesis is this: What moral duties does the international community have to post-atrocity societies? To answer this question, I critically examine the normative issues involved in the four key aspects of peacebuilding (identified above). Using the framework of just war theory and a cosmopolitan theory of fundamental human rights, I argue that, in most post-atrocity cases, the international community has duties to remove atrocity-committing regimes from power, occupy the target-state and act as a transitional authority, help facilitate the creation of democracy and economic development, and hold war crimes trials. These duties, of course, are extremely complicated and limited and these qualifications are examined and developed throughout. Running through the construction of my theory of post-atrocity duties is a clear message: we – the international community – have obligations to the victims and survivors of atrocities. In other words, providing assistance in the wake of mass-atrocities is not a supererogatory act of charity, rather, it is a duty which we owe to the victims of these horrible crimes.
Opciones para reformar el financiamiento de la enseñanza superior

The paper reviews the challenges higher education financing faces in Latin America and the Caribbean, namely the political challenge of democracy, technological challenges, and, the strong social challenge demanding higher education responsiveness. Globally, there has been a reduction in government higher education financing, consequently alternate financing mechanisms are being explored, to generate resources outside public financing, while increasing access, and quality to education as well. The paper questions reforms, and innovative efforts in reversing past experiences, and whether it is possible to overcome the current crisis in higher education. It argues on the dimensions of the financial crises, as political leaders in developing countries face higher education reforms, and the consequences it entails for the education sector, and, examines different options on the reform agenda, through the analysis of recent experiences, in countries which aimed at higher education financial sustainability. Recommendations suggest a strategic, institutional approach in the definition of excellence, compounded by specific financial measures to build higher education institutional capacity.
Regulation of Ly49D/DAP12 Signal Transduction by Src-Family Kinases and CD4512

Activating, DAP12-coupled members of the Ly-49 family of NK cell receptors help control viral infections in mice. However, the kinases and/or phosphatases mediating tyrosine phosphorylation of Ly-49D-associated DAP12 have not been elucidated. In this study, we show for the first time that Src family tyrosine kinases are physically and functionally associated with Ly-49D/DAP12 signaling in murine NK cells. Specifically, we demonstrate the following: 1) inhibition of Src family kinases suppresses DAP12 phosphorylation and downstream DAP12 signals; 2) both Fyn and Lck are capable of phosphorylating DAP12; and 3) both kinases coimmunoprecipitate with the Ly-49D/DAP12 complex in NK cells. Although we detect enhanced phosphorylation of Fyn upon Ly-49D cross-linking in NK cells, Ly-49D-mediated events in both Fyn−/− and Fyn/Lck−/− mice appear normal, reinforcing the theme of redundancy in the ability of Src family kinases to initiate activation events. In contrast to disruption of specific Src family enzymes, Ly-49D/DAP12-mediated calcium mobilization and cytokine production by CD45 null NK cells are defective. Although others have ascribed the effects of CD45 mutation solely on the suppression of Src family activity, we demonstrate in this study that DAP12 is hyperphosphorylated in CD45 null NK cells, resulting in uncoordinated tyrosine-mediated signaling upon Ly-49D ligation. Therefore, although our data are consistent with a Src kinase activity proximally within DAP12 signaling, DAP12 also appears to be a substrate of CD45, suggesting a more complex role for this phosphatase than has been reported previously.
Automatic Caption Generation for News Images

AbtractThis thesis is concerned with the task of automatically generating captions for images, which is important for many image related applications. Our model learns to create captions from publicly available dataset that has not been explicitly labelled for our task. A dataset consists of news articles, the pictures embedded in them, and their captions, and consists of two stages. First stage consists of content selection which identifies what the image and accompanying article are about, whereas second stage surface realization determines how to put the chosen content in a proper grammatical caption. For content selection, we are using probabilistic image annotation model that suggests keywords for an image. This model postulates that images and their textual descriptions are generated by a shared set of latent variables (topics) and is trained on a weakly labeled dataset (which treats the captions and associated news articles as image labels). The abstractive surface realization model generates captions that are favorable to human generated captions.
Large-scale Ordinal Collaborative Filtering

This paper proposes a hierarchical probabilistic model for ordinal matrix factorization by actively modelling the ordinal nature of ranking data, which is typical of large-scale collaborative filtering tasks. Two algorithms are presented for inference, one based on Gibbs sampling and one based on variational Bayes. The model is evaluated on a collaborative filtering task, where users have rated a collection of movies and the system is asked to predict their ratings for other movies. The Netflix data set is used for evaluation, which consists of around 100 million ratings. Using root mean-squared error (RMSE) as an evaluation metric, results show that the suggested model improves similar factorization techniques. Results also show how Gibbs sampling outperforms variational Bayes on this task, despite the large number of ratings and model parameters.
DEMO: Panoptiphone: How Unique is Your Wi-Fi Device?

MAC address randomization in Wi-Fi-enabled devices has recently been adopted to prevent passive tracking of mobile devices. However, Wi-Fi frames still contain fields that can be used to fingerprint devices and potentially allow tracking. Panoptiphone is a tool inspired by the web browser fingerprinting tool Panopticlick [2], which aims to show the identifying information that can be found in the frames broadcast by a Wi-Fi-enabled device. Information is passively collected from devices that have their Wi-Fi interface enabled, even if they are not connected to an access point. Panoptiphone uses this information to create a fingerprint of the device and empirically evaluate its uniqueness among a database of fingerprints. The user is then shown how much identifying information its device is leaking through Wi-Fi and how unique it is.
The contribution of anthropogenic bromine emissions to past stratospheric ozone trends: a modelling study

Bromine compounds play an important role in the depletion of stratospheric ozone. We have calculated the changes in stratospheric ozone in response to changes in the halogen loading over the past decades, using a two- dimensional (latitude/height) model constrained by source gas mixing ratios at the surface. Model calculations of the decrease of total column ozone since 1980 agree reason- ably well with observed ozone trends, in particular when the contribution from very short-lived bromine compounds is included. Model calculations with bromine source gas mixing ratios fixed at 1959 levels, corresponding approxi- mately to a situation with no anthropogenic bromine emis- sions, show an ozone column reduction between 1980 and 2005 at Northern Hemisphere mid-latitudes of only 55% compared to a model run including all halogen source gases. In this sense anthropogenic bromine emissions are responsi- ble for 45% of the model estimated column ozone loss at Northern Hemisphere mid-latitudes. However, since a large fraction of the bromine induced ozone loss is due to the com- bined BrO/ClO catalytic cycle, the effect of bromine would have been smaller in the absence of anthropogenic chlorine emissions. The chemical efficiency of bromine relative to chlorine for global total ozone depletion from our model cal- culations, expressed by the so called -factor, is 64 on an an- nual average. This value is much higher than previously pub- lished results. Updates in reaction rate constants can explain only part of the differences in . The inclusion of bromine from very short-lived source gases has only a minor effect on the global mean -factor.
Agglomeration economies and growth-The case of Italian local labour systems, 1991-2001

The main objective of this paper is to assess the role of a large set of factors which potentially relate agglomeration economies to local growth. Such a relationship is analysed thanks to an ample database on the case of Italy which refers to 784 Local Labour Systems and 34 sectors (21 manufacturing and 13 services) over the period 1991-2001. Econometric results show that local growth in Italy is characterized by significant differences across sectors. It is worth mentioning the positive influence of diversity externalities, human and social capital and the negative influence of specialisation externalities and competition. Spatial association is also detected.
Inequality and Trust

This paper reviews the literature on economic inequality and trust. Cross-country studies, within-country studies, and experiments all suggest that economic inequality exerts a negative influence on trust. Four mechanisms are proposed to explain the negative relationship: social ties (or networks), inference on social relationships (to see inequality as a signal of untrustworthy behavior), conflicts over resources, and opportunity cost of time. Social ties receive the strongest empirical support, but there is also some evidence in favor of inference on social relationships. Conflicts over resources and opportunity cost of time are contradicted by important pieces of evidence.
Impact of Low Birth Weight and Cardiovascular Risk Factors on Endothelial Function in Early Adult Life

Background — Low birth weight is related to increased risk of coronary heart disease in adults and recently has been associated with vascular endothelial dysfunction in children. We investigated whether the relation between birth weight and endothelial function was still present in early adult life and whether there was an interaction with emerging risk factors. Methods and Results — In 315 adults (165 women, 150 men, aged 20 to 28 years), high-resolution ultrasound was used to determine endothelium-dependent and -independent vascular responses of the brachial artery. Vascular measures were related to classic risk factors (smoking history, lipid profile, blood pressure, fasting insulin, exercise capacity, body mass index, and combined risk score) and birth weight. Low birth weight was associated with reduced flow-mediated dilation (coefficient=0.18 kg−1, 95% CI 0.004 to 0.35, P =0.04) but not with endothelium-independent dilation. The difference in flow-mediated dilation between the top and bottom fifths of birth weight was the same as between smokers and nonsmokers. Increasing levels of acquired risk factors overwhelmed the association, and there was a significant interaction of risk score with the birth weight–endothelial function relation (coefficient of interaction term [birth weight×risk score] = −0.12, 95% CI −0.22 to −0.03, P =0.01). Conclusions — Low birth weight is associated with endothelial dysfunction in young adults. This is most marked in individuals with lower risk factor profiles and may be relevant to the pathogenesis of atherosclerosis in later life.