Miracle-dz/UniFAR-FTUs huggingface dataset:
Financial Performance and Corporate Governance in the European Football Industry

The aim of this paper is to analyze the impact of corporate governance quality (namely board size, board independence, managerial ownership, institutional ownership, and CEO duality) on the profitability and viability of European Union’s football clubs over the period 2005-2009. Empirical results documented that corporate governance quality (higher managerial and institutional ownership, increased board size and independence, and the separation of the CEO and chairman roles) leads to greater levels of profitability and viability. Further analysis based on clubs’ profitability and viability indicates that sound governance mechanisms are also important for those clubs with intense problems of insolvency and low financial performance. The results of this study dictate the necessity of corporate governance principles for protecting the interests of shareholders and various stakeholders and for maximizing the clubs’ economic results and social return. The empirical findings are robust to several sensitivity tests concerning the specification of the models and the measures of financial performance.
Analysis and modeling of a piezoelectric transformer in high output voltage applications

Piezoelectric transformers (PZT) can be used advantageously in high output voltage DC-DC converters. In such applications, the output section includes a voltage doubling rectification scheme to help increase the output voltage. This topology was modeled and analyzed by considering the expected voltage and current waveforms under first harmonics approximation. The results were then used to build a linear AC equivalent circuit that emulates the AC-DC stage. The proposed model was verified against experimental results.
Evidence that Price Leads of Earnings Increase with Analyst Following and Institutional Ownership

This paper presents evidence that prices of firms followed by sell-side analysts and favored by institutional investors incorporate future earnings earlier than prices of other firms. Our tests are based on regressions of year t abnormal returns on earnings changes from years t-1, t, and t+1. We find that lead coefficients for firms most heavily followed by analysts or favored by institutions are greater than lead coefficients for firms with little analyst following or institutional holdings. In contrast, contemporaneous coefficients for analyst and institutional favorites are less than contemporaneous coefficients for other firms. Furthermore, the results for analysts and institutions are incremental to each other. In addition, neither effect is due to the fact that price leads are an increasing function of firm size. One possible explanation for our results is that market professionals are more skilled than other investors in analyzing publicly available information. Alternatively, the positive association between price leads and professional interest may exist only because management provides more detailed information to sell-side and buy-side analysts than to individual investors. This possibility prompted the SEC to issue Regulation FD, which creates a more level playing field for all investors by eliminating selective disclosures. Our results, which are based on data prior to the passage of Regulation FD, suggest that the "distribution gain" sought by the SEC may come with an "allocation cost. " That is, if Regulation FD causes management to reduce the flow of information to market professionals, the length of price leads could be shortened.
Unifying Representations and Large-Scale Whole-Body Motion Databases for Studying Human Motion

Large-scale human motion databases are key for research questions ranging from human motion analysis and synthesis, biomechanics of human motion, data-driven learning of motion primitives, and rehabilitation robotics to the design of humanoid robots and wearable robots such as exoskeletons. In this paper we present a large-scale database of whole-body human motion with methods and tools, which allows a unifying representation of captured human motion, and efficient search in the database, as well as the transfer of subject-specific motions to robots with different embodiments. To this end, captured subject-specific motion is normalized regarding the subject's height and weight by using a reference kinematics and dynamics model of the human body, the master motor map (MMM). In contrast with previous approaches and human motion databases, the motion data in our database consider not only the motions of the human subject but the position and motion of objects with which the subject is interacting as well. In addition to the description of the MMM reference model, we present procedures and techniques for the systematic recording, labeling, and organization of human motion capture data, object motions as well as the subject-object relations. To allow efficient search for certain motion types in the database, motion recordings are manually annotated with motion description tags organized in a tree structure. We demonstrate the transfer of human motion to humanoid robots and provide several examples of motion analysis using the database.
Neuroprotective Effects of Inhibiting Fyn S-Nitrosylation on Cerebral Ischemia/Reperfusion-Induced Damage to CA1 Hippocampal Neurons

Nitric oxide (NO) can regulate signaling pathways via S-nitrosylation. Fyn can be post-translationally modified in many biological processes. In the present study, using a rat four-vessel-occlusion ischemic model, we aimed to assess whether Fyn could be S-nitrosylated and to evaluate the effects of Fyn S-nitrosylation on brain damage. In vitro, Fyn could be S-nitrosylated by S-nitrosoglutathione (GSNO, an exogenous NO donor), and in vivo, endogenous NO synthesized by NO synthases (NOS) could enhance Fyn S-nitrosylation. Application of GSNO, 7-nitroindazole (7-NI, an inhibitor of neuronal NOS) and hydrogen maleate (MK-801, the N-methyl-d-aspartate receptor (NMDAR) antagonist) could decrease the S-nitrosylation and phosphorylation of Fyn induced by cerebral ischemia/reperfusion (I/R). Cresyl violet staining validated that these compounds exerted neuroprotective effects against the cerebral I/R-induced damage to hippocampal CA1 neurons. Taken together, in this study, we demonstrated that Fyn can be S-nitrosylated both in vitro and in vivo and that inhibiting S-nitrosylation can exert neuroprotective effects against cerebral I/R injury, potentially via NMDAR-mediated mechanisms. These findings may lead to a new field of inquiry to investigate the underlying pathogenesis of stroke and the development of novel treatment strategies.
An iterative approach for amplitude amplification with nonorthogonal measurements

Using three coupled harmonic oscillators, we present an amplitude-amplification method for factorization of an integer. We generalize the method in [arXiv:1007.4338] by employing non-orthogonal measurements on the harmonic oscillator. This method can increase the probability of obtaining the factors by repeatedly using the nonlinear interactions between the oscillators and non-orthogonal measurements. However, this approach requires an exponential amount of resources for implementation. Thus, this method cannot provide a speed-up over classical algorithms unless its limitations are resolved.
Marginal cost rate design and wholesale water markets

Part 1 Changing institutions and increasing scarcity: changing institutions to mitigate water scarcity, Darwin C. Hall environmental values in water benefits and costs, Thomas C. Wegge and W. Michael Hanemann. Part 2 Integrated resource planning: long term forecasting of urban water demands, Benedyct A. Dziegielewski impact of xeriscaping on residential demand, Michael Nieswiadomy and Kariann Sokulsky integrated resource and reliability planning, Dan Rodrigo and Timothy A. Blair. Part 3 Urban water rate design: implementating marginal cost pricing for water, Darwin C. Hall marginal cost pricing and the new LADWP water rates, W. Michael Hanemann. Part 4 Wholesale water markets: modeling reduced agricultural water supplies with endogenous irrigation technology, David Sunding and David Zilberman empirical measures of water market supply, Richard E. Howitt water banking to manage supply variability, Kathleen A. Miller water marketing in California, Richard W. Wahl what price water marketing, Mason Gaffney.
Question classification in Persian language based on conditional random fields

The question classification system is one of the important subsystems in the Question Answering Systems (QAS). In such systems through retrieval methods and information extraction the texts are retrieved in order to get to a correct answer. The current study is designed to present the architecture of question classification (QC) in Persian based on the Conditional Random Fields (CRF) machine learning model and evaluate effects of various features on its accuracy. In this study, sentences were classified into two levels of coarse and fine classes based on the type of the answer to each question. After extracting features and setting sliding window on the CRF model, CRF question classifier (QC) is train. Then, the QC predicts labels for every token in question. Next, a majority voting on the question classification output, is used to extract a unique label for each question. Further, the effects of different features on the ultimate accuracy of the system were evaluated. Finally results of this question classifier, illustrate a satisfactory accuracy.
THE EFFECT OF HEDONIC SHOPPING MOTIVATION ON CONSUMER SATISFACTION AND CONSUMER LOYALTY

The study investigates the relationships among shopping motivation, customer satisfaction and customer loyalty. Measures based on the literature on the subject were used in this study. Surveys were constructed to 372 students in classroom settings at Aksaray University in the Turkey. Firstly, the Exploratory Factor Analysis (EFA) was carried out and thus, a five-factor solution was obtained. Then, the result model was tested by the Structural Equation Model (SEM). Results show that experimentation motivation has positive impact on both customer satisfaction and customer loyalty. However, value shopping motivation does not have any impact on them. In addition, gratification motivation does not influence customer loyalty, and idea and role shopping motivations do not have any impact on customer satisfaction. Findings of this study will help both researchers and practitioners in the field understand the roles of shopping motivations in customer satisfaction and customer loyalty. Finally, limitations, suggestions for further research and practical implications of this study are provided.
Effect of chemical structure on secondary organic aerosol formation from C 12 alkanes

The secondary organic aerosol (SOA) formation from four C_(12) alkanes (n-dodecane, 2-methylundecane, hexylcyclohexane, and cyclododecane) is studied in the Caltech Environmental Chamber under low-NO_x conditions, in which the principal fate of the peroxy radical formed in the initial OH reaction is reaction with HO_2. Simultaneous gas- and particle-phase measurements elucidate the effect of alkane structure on the chemical mechanisms underlying SOA growth. Reaction of branched structures leads to fragmentation and more volatile products, while cyclic structures are subject to faster oxidation and lead to less volatile products. Product identifications reveal that particle-phase reactions involving peroxyhemiacetal formation from several multifunctional hydroperoxide species are key components of initial SOA growth in all four systems. The continued chemical evolution of the particle-phase is structure-dependent, with 2-methylundecane SOA formation exhibiting the least extent of chemical processing and cyclododecane SOA achieving sustained growth with the greatest variety of chemical pathways. The extent of chemical development is not necessarily reflected in the oxygen to carbon (O : C) ratio of the aerosol as cyclododecane achieves the lowest O : C, just above 0.2, by the end of the experiment and hexylcyclohexane the highest, approaching 0.35.
An approach to adaptive map building of mobile robots in unknown environment

Map building in unknown environment is the prerequisite to perform other tasks for the mobile robots. An effective approach based on the frontier points is proposed in this paper. Firstly, an adaptive clustering algorithm which integrates subtractive clustering and k-means clustering is introduced to partition the frontier points into different groups. Secondly, the centers of the groups serve as candidate destination points and they are evaluated using multi-step-ahead prediction. The optimal one will be selected to guide the robot to explore the environment with high accuracy. Finally, simulation results are provided for validation which show that the proposed strategy can generate accurate and complete (or nearly complete) maps of the unknown environments.
The Impact of ICT on Manufacturing Industry: An Empirical Analysis

This research aims to explore and validate the relationship between the uses of information and communication technology, operational leadership and marketing efficiency in the Indian manufacturing industry in an empirical manner. Extensive literature survey and several rounds of interviews were performed with practitioners and academicians for developing the items of constructs and research model. After this factor analysis and Cronbach's alpha test was conducted to validate the items into the constructs of the measuring instrument. Finally, structured equation modeling analysis with the help of AMOS tools was performed to empirically validate the proposed model. This research finds the strong relationship between ICT usage, operational leadership and marketing efficiency. This research provides an insight into measuring the efficiency of ICT usage in the manufacturing organizations and the strength of relationship between the constructs. This research can be further extended beyond the manufacturing industry in the Indian scenario.
Modelling and Forecasting the Metical-Rand Exchange Rate

This paper investigates the ability of the Dornbusch (1976) sticky-price model for the nominal metical-rand exchange rate, over the period 1994:1-2005:4 in explaining the exchange rate movements of Mozambique. Based on the model, the authors find that there is a stable relationship between the exchange rate and the fundamentals. Gross domestic product and inflation differentials between Mozambique and South Africa play the major role in explaining the metical-rand exchange rate. However, when the Dornbusch (1976) model is re-estimated over the period of 1994:1-2003:4, and the out-of-sample forecast errors are compared with the atheoretical, Classical and Bayesian variants of the Vector Autoregressive (VAR) and Vector Error Correction (VEC) models, and models capturing alternative forms of the Efficient Market Hypothesis (EMH) of exchange rates, the sticky-price model performs poorer. Overall, the Bayesian VEC models (BVECMs) with relatively tight priors, are best suited for forecasting the metical-rand exchange rate, both in terms of out-of-sample forecasting and predicting turning points.
A sketch-based query interface for 3D CAD model retrieval

A sketch-based query interface is proposed for retrieving 3D CAD models. The maximum distribution of normal vectors of a 3D model is computed to assist the PCA algorithm to normalize the pose of the 3D model, and then the outline views of the 3D model can be coordinated with the freehand sketches submitted by users. To retrieve the 3D models similar with the user sketches, an image similarity assessment algorithm is employed to compare the shape similarity between user sketches and the outline views of 3D models. Experiments demonstrate that users can express the query shape through the proposed query interface rapidly and the retrieval performance is satisfactory.
A Novel Photosynthesis of Carboxymethyl Starch-Stabilized Silver Nanoparticles

The water soluble photoinitiator (PI) 4-(trimethyl ammonium methyl) benzophenone chloride is used for the first time in the synthesis of silver nanoparticles (AgNPs). A new green synthesis method involves using PI/UV system, carboxymethyl starch (CMS), silver nitrate, and water. A mechanism of the reduction of silver ions to AgNPs by PI/UV system as well as by the newly born aldehydic groups was proposed. The synthesis process was assessed by UV-vis spectra and TEM of AgNPs colloidal solution. The highest absorbance was obtained using CMS, PI and AgNO3 concentrations of 10 g/L, 1 g/L, and 1 g/L, respectively; 40°C; 60 min; pH 7; and a material : liquor ratio 1 : 20. AgNPs so-obtained were stable in aqueous solution over a period of three weeks at room temperature (~25°C) and have round shape morphology. The sizes of synthesized AgNPs were in the range of 1–21 nm and the highest counts % of these particles were for particles of 6–10 and 1–3 nm, respectively.
Polar Optical Phonons in AlN / GaN superlattice structures

Infrared reflection spectra of bulk semiconductors and superlattices can be predicted mathematically with optical phonon frequencies as some of the input variables. This method will be used to determine the polar longitudinal and transverse optical phonons modes and their corresponding energies that are present in AlN/GaN superlattices. Theoretical results will be compared to reflection experiments taken at a 75 incidence angle. Different AlN/GaN superlattice combinations will be studied to see if any pattern of phonon energies may arise. This outcome may prove useful in engineering phonons at specific frequencies. Furthermore, new phonons exist that are not at the energy levels present in bulk AlN and GaN. Phonon dispersion curve “folding” might prove useful to predict these new phonons. It will be determined whether this “folding” is a useful explanation for these new phonons, and if not, a new hypothesis will be made.
Towards Intelligent Visual Understanding under Minimal Supervision Dingwen

Because of playing one of the most important roles in the artificial intelligent systems like robots, visual understanding has gained vast interests in the past few decades. Most of the existing approaches need human labelled training data to train the learning models for visual understanding and in the most recent years, significant performance gain was obtained relying on unparalleled tremendous amount of human labelled training data. Under this circumstance, people are endowed with great burden to cost energy and time on the tedious data annotation for the traditional visual understanding approaches. To alleviate this problem, we propose to develop novel visual understanding algorithms which can learn informative visual patterns under minimal (none or very weak) supervision and thus facilitate higher-level intelligence of the visual understanding systems. Specifically, we focus on three subtopics, i.e., saliency detection, co-saliency detection, and weakly supervised learning based object detection, which can be used in both the image and video understanding systems. The experimental results have demonstrated the effectiveness of the proposed algorithms.
The New Rough Neuron

This paper proposes a novel method of combining rough concepts with neural computation. The proposed rough neuron consists of, one lower bound neuron and another boundary neuron. The combination is designed in such a way that the boundary neuron deals only with the random and unpredictable part of the applied signal. Such architecture effectively prunes the search space for the respective constituent neurons based on the certain and uncertain behaviors. This division results in an improved rate of error convergence in the back propagation of the neural network along with an improved parameter approximation during the network learning process. Preliminary structures of the rough neural network along with some testing results have been presented. Further, the performance of the rough neural network has been compared with some of the prevalent designs
Centroid dynamic sink location for clustered wireless mobile sensor networks

The wireless sensor network consists of three main components: a large number of small-sized sensors, a remote sink connected to the internet, and a cluster head whose existence depends on the overall network structure. The sensor in the wireless sensor network can be deployed through many ways, such as a simple model, a random walk model, and a random direction model. There were studies that examined networks and their various installation methods to save energy consumption and increase the network lifetime. These were usually achieved by formatting the network structure with one or multi-sinks, with or without clusters, or using static or mobile components such as sink, cluster heads, and sensors. In addition, using a homogeneous or heterogeneous environment implies using special devices as cluster heads or electing them from sensors periodically at specified times depending on different protocols. Previous studies did not focus on saving energy when all network's components were mobile. Our scheme, Centroid Dynamic Sink Location (CDSL), focuses on this case and aims to reduce the energy consumption through moving the sink to the optimal location with respect to the cluster heads. The simulation results indicated that the CDSL scheme increases the network lifetime by saving the cluster heads energy. When the sink is mobile, the network lifetime increased in all cases from 14.21% to 53.09% compared to that which use a fixed sink.
Near-infrared laser delivery of nanoparticles to developing embryos: A study of efficacy and viability

Targeted delivery of materials to individual cells remains a challenge in nanoscience and nanomedicine. Near infrared (NIR) laser injection may be a promising alternative to manual injection (where the micropipet diameter limits targeting to small cells) or other laser techniques (such as picosecond green and UV lasers, which can be damaging to cells). However, the efficiency with which NIR pulses can deliver nanoparticles and any adverse effects on living cells needs thorough testing. Toward this end, we have determined the efficacy and toxicity of delivering quantum dots (QDs) into cells of Xenopus laevis embryos by NIR laser injection. Because this model system provides not only living cells but also a developing organism, we were able to assess relatively long‐term effects of NIR pulses on embryonic development (through the tadpole stage). We developed parameters for NIR pulses that did not affect embryonic viability or morphology and delivered QDs as effectively as manual injection. Higher intensities of NIR pulses caused permanent damage to the targeted cells, and thus NIR pulses may also prove useful for ablation of specific cells within tissues.
Verifying physical presence of neighbors against replay-based attacks in wireless ad hoc networks

Verifying physical presence of a neighbor in wireless ad hoc networks is one of the key components in developing protocols resilient to replay-based attacks. For this, we first consider RTT-based and power-based approaches. We then couple them to design an effective neighbor verification protocol (NVP). In theory, we always see some room for replay-based attacks. However, our proposed protocol significantly limits the effectiveness of replay-based attacks by restricting the range where they might be launched and thus makes them practically impossible.
Compressed membership problems revisited

Membership problems for compressed strings in regular languages are investigated. Strings are represented by straight-line programs, i.e . cont xtfree grammars that generate exactly one string. For the representation of regular languages, various formalisms with different degrees of succinctnes s (e.g. suitably extended regular expressions, hierarchical automata) are cons idered. Precise complexity bounds are derived. Among other results, it is shown tha t the compressed membership problem for regular expressions with interse ction is PSPACE-complete. This solves an open problem of Plandowski and Rytte r.