Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Personality Traits and Managers` Leadership Styles

Abstract This research study starts with the hypothesis that the personality traits of managers influence their leadership styles. Personality traits are taken from the model Big Five (McCrae and Costa) since it is one of the most dominant models of personality in modern psychology. Management styles (leadership) were investigated within the theories of transformational and transactional leadership, including laissez-faire style (Bruce Avolio & Bernard Bass). The research was conducted with 160 lower-level, middle-level and high-level managers in Serbia, employed in private and public sectors. From the questionnaire the NEO Personality Inventory (Serbian version, Kostić, P. 2002), and with the analysis of the main components, five dimensions of personality have been extracted: extraversion, neuroticism, conscientiousness, agreeableness and openness to experience. From the shorter version of Multifactor Leadership Questionnaire, three factors of leadership have been extracted: transformational, transactional and laissez-faire. The relationship between the received factors was checked by Pearson`s correlation coefficient and by multiple regression analysis. The received information showed that there is a statistically significant relationship between personality traits and leadership styles, and the most dominant relationship is between the transformational leadership style and extraversion (in a positive sense) and neuroticism (in a negative sense).
Importance of eyes and eyebrows for face recognition system

In this paper, we evaluate the effect of removing eyes or eyebrows from face image (no left eyebrow, no right eyebrow, no eyebrows, no left eye, no right eye, no eyes, no left eyebrow and no left eye, no right eyebrow and no right eye, no eyebrows and no eyes) on the performance of face recognition system based on Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Discrete Wavelet Decomposition (DWT), Discrete Cosine Transform (DCT) and application of DWT prior SVD (DWT-SVD). The evaluation is carried on the FEI database using the Recognition Rate (RR) and Equal Error Rate (EER) criteria.
ModNet: A Modular Approach to Network Stack Extension

The existing interfaces between the network stack and the operating system are less than ideal for certain important classes of network traffic, such as video and mobile communication. While TCP has become the de facto transport protocol for much of this traffic, the opacity of some of the current network abstractions prevents demanding applications from controlling TCP to the fullest extent possible. At the same time, non-TCP protocols face an uphill battle as the network management and control infrastructure around TCP grows and improves. In this paper, we introduce ModNet, a lightweight kernel mechanism that allows demanding applications better customization of the TCP stack, while preserving existing network interfaces for unmodified applications. We demonstrate ModNet's utility by implementing a range of network server enhancements for demanding environments, including adaptive bitrate video, mobile content adaptation, dynamic data and image compression, and flash crowd resource management. These enhancements operate as untrusted user-level modules, enabling easy deployment, but can still operate at scale, often providing gigabits per second of throughput with low performance overheads.
IMPACT OF GEOLOGICAL VARIABLES ON GYPSUM MINERALISATION: ASSESSMENT OF THE GUYUK GYPSUM OCCURRENCES,

Field observations are used to assess the impact of geomorphic, lithologic and physicochemical to ascertain their extent of control on gypsum formation and accumulation in Guyuk area. Varying quantities of gypsiferous beds are associated with mainly mudstone and highly fossiliferous – fissured limestone at depths between 0.02 to 9.12m and altitude 219.3 – 473.62m. Integration of the field evidences reveal that gypsum mineralisation is not restricted to a particular depth/altitude range rather its absence or copious occurrences depend on presence of limestone beds in the area. Inductively, dolomitization is given as the process of gypsum mineralisation in Guyuk area. The sparse mineralisation of the Jessu Formation is not unconnected with the low limestone content of the unit. The rock unit is limestone – rich toward the fringes bordering the overlying Sekule (in Lakoro area) and underlying Dukul Formations (in Gudenyi area). These characteristics depicts that gypsum mineralisation is related more to the chemistry of the associated/host rocks than to the altitude and/or depth of occurrence. This confirms Boyadiev’s (1974) opinion that precipitation of gypsum is a function of the nature and composition of the host rock and climate, even though geomorphology, the form of landscape, orientation of the rock structure and activity of cation exchange might influence the processes of its accumulation.
Do Actions Speak Louder Than Words? Optimistic Disclosure Tone, Insider Trading and Capital Structure

This paper examines the impact of managerial belief on capital structure. Computational tone analysis of Chairman’s Statement is used to gauge time-varying managerial overconfidence. We find that optimistic tone is negatively related to leverage. This finding provides initial empirical evidence consistent with Malmendier, Tate and Yan’s (2011) proposition that managerial overconfidence may lead to debt conservatism. The negative tone-leverage relationship is similar across firms with different degree of information asymmetry and information environment, ruling out two alternative explanations of tone (i.e. information asymmetry and impression management). We further investigate the joint effects of insider trading, as another window into managerial belief, and tone on leverage. As expected, high insider purchase (selling) confirms (contradicts) optimistic tone, which in turn enhances (weakens) the negative tone-leverage relationship. Overall, this study establishes a link between managerial optimistic words and conservative debt policy.
Cosmic evolution of metal densities: the enrichment of the intergalactic medium

By means of chemo-photometric models for galaxies of different morphological types, we have carried out a detailed study of the history of element production by spheroidal and dwarf irregular galaxies. Spheroidal galaxies suffer a strong and intense star formation episode at early times. In dwarf irregulars, the star formation rate (SFR) proceeds at a low regime but continuously. Both galactic types enrich the intergalactic medium (IGM) with metals by means of galactic winds. We have assumed that the galaxy number density is fixed and normalized to the value of the optical luminosity function observed in the local Universe. Our models allow us to investigate in detail how the metal fractions locked up in stars in spheroids and dwarf irregulars, those present in the interstellar medium (ISM) and those ejected into the IGM have changed with cosmic time. By relaxing the instantaneous recycling approximation and taking into account stellar lifetimes, for the first time we have studied the evolution of the chemical abundance ratios in the IGM and compared our predictions with a set of observations by various authors. Our results indicate that the bulk of the IGM enrichment is due to spheroids, with dwarf irregular galaxies playing a negligible role. Our predictions grossly account for the [O/H] observed in the IGM at high redshift, but overestimate the [C/H]. Furthermore, it appears hard to reproduce the abundance ratios observed in the high-redshift IGM. Some possible explanations are discussed in the text. This is the first attempt to study the abundance ratios in the IGM by means of detailed chemical evolution models which take into account the stellar lifetimes. Numerical simulations adopting our chemical evolution prescriptions could be useful to improve our understanding of the IGM chemical enrichment.
The Role of Whole Blood Impedance Aggregometry and Its Utilisation in the Diagnosis and Prognosis of Patients with Systemic Inflammatory Response Syndrome and Sepsis in Acute Critical Illness

Objective To assess the prognostic and diagnostic value of whole blood impedance aggregometry in patients with sepsis and SIRS and to compare with whole blood parameters (platelet count, haemoglobin, haematocrit and white cell count). Methods We performed an observational, prospective study in the acute setting. Platelet function was determined using whole blood impedance aggregometry (multiplate) on admission to the Emergency Department or Intensive Care Unit and at 6 and 24 hours post admission. Platelet count, haemoglobin, haematocrit and white cell count were also determined. Results 106 adult patients that met SIRS and sepsis criteria were included. Platelet aggregation was significantly reduced in patients with severe sepsis/septic shock when compared to SIRS/uncomplicated sepsis (ADP: 90.7±37.6 vs 61.4±40.6; p<0.001, Arachadonic Acid 99.9±48.3 vs 66.3±50.2; p = 0.001, Collagen 102.6±33.0 vs 79.1±38.8; p = 0.001; SD ± mean)). Furthermore platelet aggregation was significantly reduced in the 28 day mortality group when compared with the survival group (Arachadonic Acid 58.8±47.7 vs 91.1±50.9; p<0.05, Collagen 36.6±36.6 vs 98.0±35.1; p = 0.001; SD ± mean)). However haemoglobin, haematocrit and platelet count were more effective at distinguishing between subgroups and were equally effective indicators of prognosis. Significant positive correlations were observed between whole blood impedance aggregometry and platelet count (ADP 0.588 p<0.0001, Arachadonic Acid 0.611 p<0.0001, Collagen 0.599 p<0.0001 (Pearson correlation)). Conclusions Reduced platelet aggregometry responses were not only significantly associated with morbidity and mortality in sepsis and SIRS patients, but also correlated with the different pathological groups. Whole blood aggregometry significantly correlated with platelet count, however, when we adjust for the different groups we investigated, the effect of platelet count appears to be non-significant.
A Curvature-based Automatic Registration Algorithm for the Scattered Points

An automatic registration algorithm for the scattered point clouds is proposed in this paper. The curvature of each point is estimated by using the quadratic surface fitting method. And then, according to the change of curvature the feature points that have the maximum local changes are extracted. The initial match points are acquired by computing the Hausdorff distance of curvature, and the feature of the surface circumference shape is used on the initial match points to obtain the accurate match points. Finally, the rotation and translation matrix are estimated by the quaternion, and iterative solution is used to improve the registration accuracy. So, the automatic match of the scattered point cloud data is completed. Experimental results show that the algorithm is effective.
Colour Retinal Image Enhancement Based on Domain Knowledge

Retinal images are widely used to manually or automatically detect and diagnose many diseases. Due to the complex imaging setup, there is a large luminosity and contrast variability within and across images. Here, we use the knowledge of the imaging geometry and propose an enhancement method for colour retinal images, with a focus on contrast improvement with no introduction of artifacts. The method uses non-uniform sampling to estimate the degradation and derive a correction factor from a single plane. We also propose a scheme for applying the derived correction factor to enhance all the colour planes of a given image. The proposed enhancement method has been tested on a publicly available dataset. Results show marked improvement over existing methods.
Skippy: a new snapshot indexing method for time travel in the storage manager

The storage manager of a general-purpose database system can retain consistent disk page level snapshots and run application programs "back-in-time" against long-lived past states, virtualized to look like the current state. This opens the possibility that functions, such as on-line trend analysis and audit, formerly available in specialized temporal databases, can become available to general applications in general-purpose databases. Up to now, in-place updating database systems had no satisfactory way to run programs on-line over long-lived, disk page level, copy-on-write snapshots, because there was no efficient indexing method for such snapshots. We describe Skippy, a new indexing approach that solves this problem. Using Skippy, database application code can run against an arbitrarily old snapshot, and iterate over snapshot ranges, as efficiently it can access recent snapshots, for all update workloads. Performance evaluation of Skippy, based on theoretical analysis and experimental measurements, indicates that the new approach provides efficient access to snapshots at low cost.
Reduction of CuZn-Superoxide Dismutase Activity Exacerbates Neuronal Cell Injury and Edema Formation after Transient Focal Cerebral Ischemia

Apoptotic neuronal cell death has recently been associated with the development of infarction after cerebral ischemia. In a variety of studies, CuZn-superoxide dismutase (CuZn-SOD) has been shown to protect the brain from ischemic injury. A possible role for CuZn-SOD-related modulation of neuronal viability is suggested by the finding that CuZn-SOD inhibits apoptotic neuronal cell death in response to some forms of cellular damage. We evaluated this possibility in the model of transient focal cerebral ischemia in mice bearing a disruption of the CuZn-SOD gene (Sod1). Homozygous mutant (Sod1−/−) mice had no detectable CuZn-SOD activity, and heterozygous mutants (Sod1 +/−) showed a 50% decrease compared with wild-type mice. Sod1 −/− mice showed a high level of blood–brain barrier disruption soon after 1 hr of middle cerebral artery occlusion and 100% mortality at 24 hr after ischemia.Sod1 +/− mice showed 30% mortality at 24 hr after ischemia, and neurological deficits were exacerbated compared with wild-type controls. The Sod1 +/− animals also had increased infarct volume and brain swelling, accompanied by increased apoptotic neuronal cell death as indicated by the in situnick-end labeling technique to detect DNA fragmentation and morphological criteria. These results suggest that oxygen-free radicals, especially superoxide anions, are an important factor for the development of infarction by brain edema formation and apoptotic neuronal cell death after focal cerebral ischemia and reperfusion.
Hybrid quadruped bounding with a passive compliant spine and asymmetric segmented body

Most legged animals exploit flexible body and supporting muscles to produce power for dynamic behaviors which results in fast locomotion and additional mobility. Previous works have focused on the symmetric flexible body with massless legs associated to the body. However, body bending in animals during running happens prior to the rear side instead of the middle point of body. Therefore, a quadruped model with a passive spinal joint, asymmetric segmented body, actuated hip joints and legs is introduced. By using a numerical return map, a periodic bounding locomotion of the model is found with optimal sets of initial conditions and proper system parameters. Moreover, this paper investigates the effects of spine flexibility in segmented body on quadrupedal bounding gait. The results show that asymmetric segmented body has bigger spine oscillation, shorter stride period and smaller cost of transport, which helps the robot run more efficiently.
Improvement methods for stock market prediction using financial news articles

News articles serve the purpose of spreading company's information to the investors either consciously or unconsciously in their trading strategies on the stock market. Because of the immense growth of the internet in the last decade, the amount of financial articles have experienced a significant growth. It is important to analyze the information as fast as possible so they can support the investors in making the smart trading decisions before the market has had time to adjust itself to the effect of the information. This paper proposes an approach of using time series analysis and improved text mining techniques to predict daily stock market directions. Experiment results show that our system achieved high accuracy (up to 73%) in predicting the stock trends.
Language acquisition and conceptual development: Individuation, relativity, and early word learning

Which words do children learn earliest, and why? These questions bear on how humans organize the world into semantic concepts, and how children acquire this parsing . A useful perspective is to think of how bits of experience are conflated into the same concept . One possibility is that children are born with the set of conceptual conflations that figures in human language . But assuming (as we will) that most semantic concepts are learned, not innate, there remain two possibilities . First, aspects of perceptual experience could form inevitable conflations that are conceptualized and lexicalized as unified concepts. In this case, we would have cognitive dominance : concepts arise from the cognitive-perceptual sphere and are simply named by language. A second possibility is linguistic dominance : the world presents perceptual bits whose clumping is not pre-ordained, and language has a say in how the bits get conflated into concepts . We propose that both cognitive and linguistic dominance apply, but to different degrees for different kinds of words (Gentner 1981, 1982). Some bits of experience naturally form themselves into inevitable (preindividuated) concepts, while other bits are able to enter into several different possible combinations.
Introducing Multiresolution Representation in Deformable Object Modeling

The need to simulate the behaviour of biological tissues in virtual environments originated intense research to devise techniques for physically-based modeling of objects whose shape and topology can dynamically evolve. The relevant amount of computation required by the existing techniques and the growing complexity of the scenes to be simulated impose the study of more flexible methods that should be adaptable to both the accuracy required by the simulation and the complexity of the scene. We propose to enhance the flexibility of deformable object models by introducing a multiresolution approach. The reason for proposing the adoption of a multiresolution approach in deformable object modeling is to allow easy adaptation of the granularity of the representation of each object, depending from the forecasted simulation time complexity and the interactive frame rate required. Multiresolution can also be used to adjust data granularity, according to the accuracy needed to preserve the properties of the material and to obtain a sufficiently correct dynamic behaviour of the object. A first design of a multiresolution deformable model is presented in the paper, based on hexahedral cells and a hierarchical decomposition scheme.
A localized, distributed protocol for secure information exchange in sensor networks

We consider the problem of securing communication between sensor nodes in large-scale sensor networks. We propose a distributed, deterministic key management protocol designed to satisfy authentication and confidentiality, without the need of a key distribution center. Our scheme is scalable since every node only needs to hold a small number of keys independent of the network size, and it is resilient against node capture and replication due to the fact that keys are localized; keys that appear in some part of the network are not used again. Another important property of our protocol is that it is optimized for message broadcast; each node shares one pairwise key with all of its immediate neighbors, so only one transition is necessary to broadcast a message. Furthermore, our scheme is suited for data fusion and aggregation processing; if necessary, nodes can "peak" at encrypted data using their cluster key and decide upon forwarding or discarding redundant information. Finally, we describe a mechanism for evicting compromised nodes as well as adding new nodes. A security analysis is discussed and simulation experiments presented.
Inertial Navigation Algorithm Based on Modified Kalman Filter and Wavelet Technique for Intelligent Vehicle

Aimed at solving the problems of GPS outage or deterioration of accuracy, the strap-down inertial navigation system (SINS) is proposed to provide reliable positioning or attitude information for intelligent vehicle. A set of mathematical transformations and integrations with respect to time are applied to these measurements of SINS to calculate position, velocity and attitude information. More importantly, in allusion to the deterioration with time of SINS accuracy, caused by the possible noise, this paper analyzes the stochastic mathematical model of SINS, uses two de-noising methods to preprocess the raw experimental data of the intelligent vehicle for eliminating integrated error. By comparing the position errors calculated with three sets of data: the raw data, the wavelet de-noised data and the adaptive fading Kalman filtered data based on the current statistical model of acceleration in the experiment, we draw a conclusion that inertial navigation algorithm with data preprocessed by the two de-noising methods can improve the position accuracy considerably. And the proposed adaptive fading Kalman filter method based on the current statistical model of acceleration is better than the wavelet de-noising method.
Trust in criminal justice and compliance with the law in Czech society: Testing the normative hypothesis on 1999 and 2011 samples

Design/Methods/Approach: The study is rooted in normative theory of compliance and empirically verifies the model of compliance as suggested by Jackson et al. (2011b) within Czech context, assuming an important role of trust in procedural fairness of the police in shaping compliant behaviour. The analysis is based on structural equation modelling with use of two representative datasets (European Social Survey, 2010; Bezpecnostni rizika, 1999).
Video Fingerprinting Based on Centroids of Gradient Orientations

Fingerprints are feature vectors that can uniquely characterize the video signal. The goal of a video fingerprinting system is to judge whether two videos have the same contents by measuring distance between fingerprints extracted from the videos. In this paper, a novel video fingerprinting method based on the centroids of gradient orientations is proposed. The centroid of gradient orientations is chosen due to its reliability and robustness against common video processing steps. A threshold used to reliably determine a fingerprint match is theoretically derived, and its validity is experimentally verified. The experimental results show that the proposed fingerprint is not only pairwise independent but also robust against common video processing steps
Comonotonic Approximations for Optimal Portfolio Selection Problems

We investigate multiperiod portfolio selection problems in a Black & Scholes type market where a basket of 1 riskfree and m risky securities are traded continuously. We look for the optimal allocation of wealth within the class of ’constant mix’ portfolios. First, we consider the portfolio selection problem of a decision maker who invests money at predetermined points in time in order to obtain a target capital at the end of the time period under consideration. A second problem concerns a decision maker who invests some amount of money (the initial wealth or provision) in order to be able to fullfil a series of future consumptions or payment obligations. Several optimality criteria and their interpretation within Yaari’s dual theory of choice under risk are presented. For both selection problems, we propose accurate approximations based on the concept of comonotonicity, as studied in Dhaene, Denuit, Goovaerts, Kaas & Vyncke (2002 a,b). Our analytical approach avoids simulation, and hence reduces the computing effort drastically.