Miracle-dz/UniFAR-FTUs huggingface dataset:
Corporate Governance and Takeover Outcomes

Manuscript type Review Research Question/Issue This article reviews how and through which channels corporate governance shapes takeover outcomes. Research Findings We summarize the main findings of the empirical literature that investigates the effect of corporate governance mechanisms on takeover outcomes. The internal and external governance mechanisms that we consider are: the board of directors, the takeover market, blockholders, financial markets in general, product market competition, and the labor market. Theoretical/Academic Implications This article adopts an agency perspective of the firm and reviews the mergers and acquisitions (M&A) literature through the lens of corporate governance. We highlight how the different corporate governance mechanisms affect the takeover process and outcomes. Practitioner/Policy Implications The article systematizes the current state of the research linking corporate governance and takeovers. In doing so, we emphasize which mechanisms policymakers can use to improve the efficiency of the takeover market. Alternatively, the review also offers indications concerning mechanisms that could be used to mitigate agency conflicts and, as such, increase firm value.
Electrolocation From Scholarpedia 2 ( 1 ) : 1411

Figure 1: Passive vs. Active electroreception. A: Paddlefish sense electric fields emitted by zooplankton (Daphnia) B: The gymnotiform wave-type weakly electric fish Apteronotus Leptorhynchus emits an electric field, the electric organ discharge (EOD), through an electric organ located in its tail. Objects with a conductivity different than that of the surrounding water will cause distorsions of this self-generated electric field. Zooplankton has a conductivity greater than that of the surrounding water and will strengthen the electric field locally. C: For active electrolocation, distorsions caused by a metal sphere lateral to tha animal form an electric image on the skin surface. In this case, the metal sphere increases the local amplitude of the EOD. This amplitude modulation is sensed by amplitude coding tuberous electroreceptors on the skin surface.
Modeling anisotropy and plate‐driven flow in the Tonga subduction zone back arc

The goal of this study is to determine whether shear wave splitting observed in subduction zone back arc regions, the Tonga subduction zone in particular, can be quantitatively modeled with flow in the back arc mantle driven by the motions of the subducting slab and the upper back arc plate. We calculated two-dimensional mantle flow models using known Tonga plate motions as boundary conditions and assuming a range of uniform and variable viscosity structures. Shear wave splitting was predicted for the anisotropy due to lattice preferred orientation (LPO) of olivine and orthopyroxene in the flow model finite strain fields. The predicted shear wave splitting provides a good match to the fast directions (parallel to the azimuth of subducting plate motion) and splitting times (0.5–1.5 s) observed in Tonga, both for models where LPO anisotropy develops everywhere above 410 km and for models where LPO anisotropy is confined to regions of relatively high stress. If LPO anisotropy does develop over the entire upper 410 km of the mantle, the strength of anistropy induced by a given amount of shear strain must be relatively weak (∼4% for shear strains of 1.5, with a maximum value of ∼6% for very large strains). The splitting observations are comparably fit by a wide range of different viscosity models. Anisotropy due to melt-filled cracks aligned by stresses in the back arc flow models predicts fast directions roughly normal to observed values and thus cannot alone explain the observed splitting.
Staying Afloat in the Tropics

SUMMARY This study examines the extent to which the top ten Caribbean destinations market their tourism product using their national tourism organization Websites. A comparison of the national tourism organization Websites of the Caribbean Tourism Organization member countries will be conducted to determine the differences in technical aspects, user friendliness, site attractiveness, and marketing effectiveness using the modified Balanced Scorecard (BSC) for Website evaluation. The modified BSC results were next used to develop and test a model of Caribbean NTO Website visitor retention. Third-order confirmatory factor analysis (CFA) was used to test the model. The model showed that the four aspects which comprise the modified BSC are important in the development of Caribbean NTO Websites.
ENVIRONMENTS OF QSOs AT REDSHIFT 0.9–1.3

We analyze new deep g- and i-band imaging of 16 QSOs in the redshift range 0.9–1.3 with the Canada–France–Hawaii Telescope. The principal points of interest are the symmetry and signs of tidal effects in the QSO hosts and nearby (companion) galaxies. The sample measures are compared with similar measures on randomly selected field galaxy samples. Asymmetry measures are made for all objects to g ∼ 22, and magnitudes of all galaxies 2 mag fainter. The QSOs are found in denser environments than the field, and are somewhat offset from the centroid of their surrounding galaxies. The QSO hosts appear more disturbed than other galaxies. While the QSO companions and field galaxies have the same average asymmetry, the distribution of asymmetry values is different. QSO companions within 15″ are fainter than average field galaxies. We discuss scenarios that are consistent with these and other measured quantities.
Robust Statistics for Describing Causality in Multivariate Time Series

A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the history of one time series to predict the current state of another, conditional on all other past information. While the Granger Causality (GC) principle remains uncontested, its literal application is challenged by practical and physical limitations of the process of discretely sampling continuous dynamic systems. Advances in methodology for time-series causality subsequently evolved mainly in econometrics and brain imaging: while each domain has specific data and noise characteristics the basic aims and challenges are similar. Dynamic interactions may occur at higher temporal or spatial resolution than our ability to measure them, which leads to the potentially false inference of causation where only correlation is present. Causality assignment can be seen as the principled partition of spectral coherence among interacting signals using both auto-regressive (AR) modeling and spectral decomposition. While both approaches are theoretically equivalent, interchangeably describing linear dynamic processes, the purely spectral approach currently differs in its somewhat higher ability to accurately deal with mixed additive noise. Two new methods are introduced 1) a purely auto-regressive method named Causal Structural Information is introduced which unlike current AR-based methods is robust to mixed additive noise and 2) a novel means of calculating multivariate spectra for unevenly sampled data based on cardinal trigonometric functions is incorporated into the recently introduced phase slope index (PSI) spectral causal inference method (Nolte et al., 2008). In addition to these, PSI, partial coherence-based PSI and existing AR-based causality measures were tested on a specially constructed data-set simulating possible confounding effects of mixed noise and another additionally testing the influence of common, background driving signals. Tabulated statistics are provided in which true causality influence is subjected to an acceptable level of false inference probability.
Hybrid-Parallel Sparse Matrix-Vector Multiplication with Explicit Communication Overlap on Current Multicore-Based Systems

We evaluate optimized parallel sparse matrix-vector operations for several representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Beyond the single node, the performance of parallel sparse matrix-vector operations is often limited by communication overhead. Starting from the observation that nonblocking MPI is not able to hide communication cost using standard MPI implementations, we demonstrate that explicit overlap of communication and computation can be achieved by using a dedicated communication thread, which may run on a virtual core. Moreover we identify performance benefits of hybrid MPI/OpenMP programming due to improved load balancing even without explicit communication overlap. We compare performance results for pure MPI, the widely used "vector-like" hybrid programming strategies, and explicit overlap on a modern multicore-based cluster and a Cray XE6 system.
DISTRIBUTED VIRTUAL ENVIRONMENTS FOR VISUALIZATION AND VISUAL DATA MINING

This paper presents a mobile virtual environment designed for the visualization of high-resolution virtualised scenes and for visual data mining. The architecture and the implementation of the mobile virtual environment are described. This environment is characterized by its distributed asynchronous architecture that optimises the rendering performances by distributing the graphical load over various computers. A client-server architecture insures the robustness of the connections and the scalability of the system. The various components of the virtual environment can be configured with an XML file. In stereo mode, two computers render the scene. The passive stereo projection system is composed of two circularly polarized DLP video projectors and the scene is rendered with two laptops (up to 400.000 polygons in real-time in this specific case). Both rear and front projection are supported. In tiled wall display mode, the number of computers is equal to the number of flat screens required for the visual display. Various applications of this virtual environment to visual data mining are considered. Finally, the system is utilized to visualize the crypt of Santa Cristina, a Byzantine crypt of the medieval period near Lecce (Italy) that has been scanned at high resolution with a MENSI range scanner and texture mapped with photogrammetric techniques.
Human capital, quality and trade

This paper develops a simple general equilibrium model of international trade based on vertical product differentiation and sector semi-specific human capital. The consequences on production and factor markets of a terms of trade shock are analyzed. The framework incorporates the hypotheses that higher quality products require a higher content of skill and that human capital is imperfectly mobile between sectors. The model is capable of explaining some stylized facts that cannot be captured by the conventional theory, in particular it explains the evolution of the international specialization observed for some countries in which unskilled intensive sectors have not been retrenched by the increased competition from developing countries.
Feedforward Inhibition Determines the Angular Tuning of Vibrissal Responses in the Principal Trigeminal Nucleus

Trigeminal neurons that relay vibrissal messages to the thalamus receive input from first-order afferents that are tuned to different directions of whisker motion. This raises the question of how directional tuning is maintained in central relay stations of the whisker system. In the present study we performed a detailed analysis of the angular tuning properties of cells in the principal trigeminal nucleus of the rat. We found that stimulus direction systematically influences response latency, so that the degree of directional tuning and the preferred deflection angle computed with first-spike latency yielded results nearly similar to those obtained with spike counts. Furthermore, we found that inhibition sharpens directional selectivity, and that pharmacological blockade of inhibition markedly decreases the angular tuning of cellular responses. These results indicate that the angular tuning of cells in the first relay station of the vibrissal system is determined by fast feedforward inhibition, which shapes excitatory inputs at the very beginning of synaptic integration.
Clustering medical data to predict the likelihood of diseases

Several studies show that background knowledge of a domain can improve the results of clustering algorithms. In this paper, we illustrate how to use the background knowledge of medical domain in clustering process to predict the likelihood of diseases. To find the likelihood of diseases, clustering has to be done based on anticipated likelihood attributes with core attributes of disease in data point. To find the likelihood of diseases, we have proposed constraint k-Means-Mode clustering algorithm. Attributes of Medical data are both continuous and categorical. The developed algorithm can handle both continuous and discrete data and perform clustering based on anticipated likelihood attributes with core attributes of disease in data point. We have demonstrated its effectiveness by testing it for a real world patient data set.
Modeling Coordination Costs Due to Time Separation in Global Software Teams

Research to date has not attempted to model coordination in global software teams. We formulate a preliminary collaboration model for a dyad to help us understand the consequences of time separation. We first describe the model and its theoretical foundations and we then evaluate the model by simulating several thousand observations and running regression models to inspect the effect of different variables on coordination costs. We then make suggestions for further extension of the model to include more complex scenarios with multiple collaborators and fewer assumptions. Our evaluation shows that the consequences of time separation are complex and that we need to understand them well before we can make claims about coordination outcomes in larger software teams that are separated by time zones.
Toward a Complexity Context for Social Entrepreneurship : A Complex Systems Leadership Perspective on Social Enterprise

The growing field of complexity leadership argues that leadership emerges from within interactions. The specific nature of the interaction dynamics that enable organizing to emerge in social entrepreneurial enterprises provides a context for leadership in these projects. Three dimensions of this complexity context are identified and described. A gene rative context for leadership is present when new knowledge or other resources in the environment are plentiful; in this case, encouraging new ideas and innovations becomes a focus of leadership attention. A unifying context exists when organizational decomposition, time, space and bureaucracy complicate organizing efforts as they scale up; information, knowledge and other resource flows become a focus of leadership in this context. Finally, a convergent context exists as solutions to pressing problems are sought; choosing direction and promoting efficiency become important when resources are constrained. Propositions are developed about the nature and implications of these dimensions at three levels of analysis.
Andrew Sentance: UK monetary policy - how long should "The song remain the same"?

It is a great pleasure to be speaking to a business audience here in Reading, in the heart of the Thames Valley. This is an extremely successful economic region – with the highest GDP per head in the United Kingdom outside central London and the 14th most prosperous region in the whole of the European Union. This track record of economic success reflects a concentration of high-tech and knowledge-based industries, particularly in the information and communications technologies sector. The Thames Valley economy also benefits from good transport links to London, other parts of the UK and international connections via Heathrow Airport, which is still Europe’s biggest aviation hub in terms of passenger numbers. It is not surprising, therefore, that a number of recent reports have highlighted the growth potential of this region in the current recovery. According to the Work Foundation, the Reading and Bracknell area is assessed to have the best job growth potential of any UK urban conurbation and Swindon and Oxford also make the top 10 in their league table.
Buyer-focused operations as a supply chain strategy: Identifying the influence of business characteristics

Purpose – Buyer‐focused operations aim at a high level of supply chain alignment by singling out resources for one buyer in order to serve this buyer optimally. The purpose of this paper is to identify what business characteristics make suppliers choose buyer‐focused operations as a supply chain strategy in their relationships with key buyers.Design/methodology/approach – A broad range of qualitative and quantitative data was collected during interviews and plant visits in a multi‐case study research design. Nine units and 42 supply links with key buyers were investigated and analysed.Findings – The suppliers choose buyer‐focused operations for different reasons. As expected, some of them choose buyer‐focused operations to fulfil the buyer's requirements in terms of flexibility (mix, volume, specification and timing). However, in other situations, buyer‐focus is used for other reasons: mostly to perform additional assembly operations. Suppliers rarely consider buyer‐focus of core production technology in .
Highly Eecient Codec Based on Signiicance-linked Connected Component a N a L Y S I S O F W Avelet Coeecients

Recent success in wavelet coding (or interchangeable, linear subband coding) is mainly attributed to the recognition of importance of data organization. There have been several very competitive wavelet codecs developed, namely, Shapiro's Embedded Zerotree Wavelets (EZW), Servetto et al.'s Morphological Representation of Wavelet Data (MRWD), and Said and Pearlman's Set Partitioning in Hierarchical Trees (SPIHT). In this paper, we propose a new image compression algorithm called Signi cance-Linked Connected Component Analysis (SLCCA) of wavelet coe cients. SLCCA exploits both within-subband clustering of signi cant coe cients and cross-subband dependency in signi cant elds. A so-called signi cance link between connected components is designed to reduce the positional overhead of MRWD. In addition, the signi cant coe cients' magnitude are encoded in bit plane order to match the probability model of the adaptive arithmetic coder. Experiments show that SLCCA outperforms both EZW and MRWD, and is tied with SPIHT. Furthermore, it is observed that SLCCA generally has the best performance on images with large portion of texture. When applied to ngerprint image compression, it outperforms FBI's wavelet scalar quantization by about 1 dB.
Some Method Fragments for Agile Software Development

The use of a situational method engineering approach to create agile methodologies is demonstrated. Although existing method bases are shown to be deficient, we take one of these (that of the OPEN Process Framework) and propose additional method fragments specific to agile methodologies. These are derived from a study of several of the existing agile methods, each fragment being created from the relevant pow- ertype pattern as standardized in the Australian Standard methodology metamodel of AS 4651.
The Spectraplakin Short Stop Is an Actin–Microtubule Cross-Linker That Contributes to Organization of the Microtubule Network

The dynamics of actin and microtubules are coordinated in many cellular processes, but little is known about molecules mediating cross-talk. We describe intracellular dynamics of Shot in a structure-function analysis of its role as a cross-linker. Shot interacts with microtubules two ways through EB1 and along microtubule lattices by the GAS2 domain.
Impact Of Employee Participation On Job Satisfaction, Employee Commitment And Employee Productivity

It is widely believed that the employee participation may affect employee’s job satisfaction; employee productivity, employee commitment and they all can create comparative advantage for the organization. The main intention of this study was to find out relationship among employee participation, job satisfaction, employee productivity and employee commitment. For the matter 34 organizations from Oil & Gas, Banking and Telecommunication sectors were contacted, of which 15 responded back. The findings of this study are that employee participation not only an important determinant of job satisfaction components. Increasing employee participation will have a positive effect on employee’s job satisfaction, employee commitment and employee productivity. Naturally increasing employee participation is a long-term process, which demands both attention from management side and initiative from the employee side.
The application of matching pursuit to extract vibration signalfeature

It has become the main direction equipment fault diagnosis to extract the signal character from the fault vibration signals using signal processing methods in the field of mechanical. This paper compares and analyzes the matching pursuit methods based on the Impulse Time-frequency Dictionary for bearing faults, using the Impulse Time-frequency Single Dictionary (ITSD) and the Impulse Time-frequency Composite Dictionary (ITCD) for decomposition of vibration signal measured by acceleration sensors, respectively. Firstly, two kinds of dictionaries are constructed based on the generation mechanism and characteristics of fault vibration signals of bearing. Then, the analysis results of simulation signals indicated the effectiveness of ITCD, and the impulse or harmonic characteristic components could be separately extracted.
Objective functions for maximum likelihood classifier design

This paper reports research into maximum likelihood parameter estimation for classification of data modelled as mixtures of multivariate Gaussian distributions. Two likelihood metrics are compared: the log conditional probability of the feature data (the non-discriminative log likelihood, L/sub n/), and the log conditional probability of the class labels (the discriminative log likelihood, L/sub d/). Results on some simple data sets indicate that L/sub d/ yields poorer classification accuracy, as measured by the average log probability l~/sub c/ of obtaining the correct classification of a set of labelled test data. Analysis of the score equations and the information matrices derived from L/sub d/ and L/sub n/ reveals that L/sub d/ produces estimates of class means with larger bias and variance, and hence larger mean-square error (E~/sup 2/), than those from L/sub n/. Some experimental results on simple data sets are given as illustration.