Miracle-dz/UniFAR-FTUs huggingface dataset:
Paper Profits From Value, Size and Momentum: Evidence from the Polish Market

Abstract In this paper we investigate sources and characteristics of value, size and momentum profits on the Polish stock market. The research aims to broaden the academic knowledge in a few ways. First, we deliver fresh out-of-sample evidence on value, momentum, and size premiums. Second, we analyze the interdependences among the factors. Third, we investigate whether the factor premiums are present after accounting for liquidity constraints. Fourth, we check whether the factor premiums are robust to transaction costs. Our research is based on all the stocks listed on the WSE in years 2001-2013. We find, that the value, momentum, and size premiums are to some extent present on the Polish market. Furthermore, they strengthen each other, but they disappear after accounting for transaction costs and liquidity.
Debye–Waller coefficient of heavily deformed nanocrystalline iron1

Extensive deformation of an iron alloy powder increases the static disorder contribution to the thermal factor, with an increase of ∼20% in the Debye–Waller coefficient observed by both X-ray diffraction and extended X-ray absorption fine structure. Molecular dynamics simulations shed light on the underlying mechanisms, confirming the major role played by the grain boundary.
Technologies for trapped-ion quantum information systems Progress toward scalability with hybrid systems

Scaling up from prototype systems to dense arrays of ions on chip, or vast networks of ions connected by photonic channels, will require developing entirely new technologies that combine miniaturized ion trapping systems with devices to capture, transmit, and detect light,while refining how ions are confined and controlled.Building a cohesive ion system fromsuch diverse parts involvesmany challenges, including navigating materials incompatibilities and undesired coupling between elements. Here, we review our recent efforts to create scalable ion systems incorporating unconventional materials such as graphene and indium tin oxide, integrating devices like optical fibers and mirrors, and exploring alternative ion loading and trapping techniques.
Electroencephalographic Abnormalities in Patients with Idiopathic Insomnia

Objective: The main goal of the present research is to describe the electroencephalographic activity during sleep and the cyclic alternating pattern (CAP) on idiopathic insomniac patients. Methods: 22 idiopathic insomnia patients were included. Sleep recording included: fully conventional EEG recording (32 electrodes, with 16 channels getting ipsilateral bipolar recordings), EOG, EMG, EKG, thoracic and abdominal respiratory movements, nasal flow and oximetry. Results: Out of the 22 registered patients, 10 (45%) showed no electroencephalographic alteration, while 12 (55%) exhibited an electroencephalographic alteration (irritative activity). Concerning PSG variables, significant differences between groups (no EEG alteration and EEG alterations) were detected in: sleep latency, total sleep time, total wake time, sleep efficiency, light sleep percentage, slow waves sleep percentage and on the sub type A1 index of the cyclic alternant pattern CAP. Conclusions: The present data strongly suggest that within the population diagnosed with idiopathic insomnia, there is a subgroup in which the electroencephalographic alterations may play a critical role as the source of the sleep abnormality.
Dose-response: an International Journal Hormesis for Fine Particulate Matter (pm 2.5) Hormesis for Fine Particulate Matter (pm 2.5)

ᮀ The hypothesis of hormesis – that substances that harm health at high exposures can reduce risks below background at low exposures, e.g., if they activate defenses without overwhelming them – becomes important for practical policy making if it holds for regulated substances. Recently, the U.S. EPA concluded that reductions in ambient concentrations of fine particulate matter (PM2.5) in air caused trillions of dollars worth of human health benefits for a compliance cost of only about $65 billion per year. This conclusion depends on an unverified assumption of a positive, causal, straight-line relation between PM2.5 concentrations and mortality risks. We review empirical data on PM2.5 and mortality risks (and their precursors, inflammatory responses) and conclude that the PM2.5 concentration-response relation may be J-shaped, rather than linear. This possibility implies that the 1990 Clean Air Act Amendment may well have produced no (or negative) human health benefits, rather than the trillions of dollars worth of reduced mortalities ascribed to it by EPA; and that attempts to achieve further risk-reduction benefits by further reducing PM2.5 concentrations may be counterproductive. This creates a very high value for scientific information that better reveals the true shape of the PM2.5 concentration response function at and below current ambient levels.
Local decay of waves on asymptotically flat stationary space-times

Author(s): Tataru, Daniel | Abstract: In this article we study the pointwise decay properties of solutions to the wave equation on a class of stationary asymptotically flat backgrounds in three space dimensions. Under the assumption that uniform energy bounds and a weak form of local energy decay hold forward in time we establish a $t^{-3}$ local uniform decay rate for linear waves. This work was motivated by open problems concerning decay rates for linear waves on Schwarzschild and Kerr backgrounds, where such a decay rate has been conjectured by R. Price. Our results apply to both of these cases.
A Cognitive Model of Drivers Attention

Cognitive architectures can account for highly complex tasks. One of the greatest challenges is understanding and modeling human driving behavior. This paper describes an integrated cognitive model of human attention during the performance of car driving. In this task, the attention process can be divided into at least three basic components: the control process, the monitoring process, and finally, the decision making process. Of these basic tasks, the first has the highest priority. All three phases are implemented in a cognitive model in the cognitive Architecture ACT-R 6.0. The model is able to keep a traffic lane, overtake another vehicle by lane change, identifies traffic signs and different situations emerging at crossroads.
The area perspective transform: A homogeneous transform for efficient in-volume queries

A key problem in applications such as soft shadows and defocus blur is to identify points or primitives which are inside a volume of space. For example, the soft shadow computation involves finding surfaces which pass in front of an area light as viewed from a point p in the scene. The desired surfaces are those which are inside a frustum defined by the light and p, and can be found by intersecting the frustum with an acceleration structure over geometry. However, accurately computing this intersection is computationally intensive. In this article, we introduce a homogeneous transform which reduces the computation required to determine the set of points or primitives which are inside a tetrahedral volume. The transform converts tetrahedra into axis-aligned boxes, substantially reducing the cost of intersection with an axis-aligned acceleration structure over points or primitives. We describe the application of this transform to soft shadows and defocus blur, and briefly consider potential uses of the underlying mathematical approach in higher-dimensional problems.
An Analytical Model of Microcellular Propagation in Urban Canyons

The fast growth of cellular coverage demand for multimedia services based on wireless communication requires an increasing use of microcells to guarantee the satisfactory connectivity. In urban environments, especially in old town centres, the application of this solution is heavily limited by difficulties concerning coverage prediction and planning. The purpose of this paper is the investigation, development and testing of an analytical propagation model based on 2D ray-tracing approach for path loss prediction. Formulas are derived taking into account multiple reflections along street walls as well as diffractions at street corners, while ground reflections are neglected. Validation of the model has been carried out by using a data set collected during a measurement campaign in Genoa's old town centre.
An integrated framework of business intelligence and analytic with performance management system: A conceptual framework

The power of data had induced the implementation of Business Intelligence and Analytic (BIA) in most organizations. They need to uncover hidden information to accelerate organizational performance. However, the gap between IT and management had arisen in its implementation. Therefore, this study reviews broad perspective of BIA and Performance Management System (PMS) that seeks to build an integrated framework for the implementation. The proposed framework has distinguished four main layers which contribute to the key elements of the implementation.
Do Human Rights Treaties Make a Difference

Do countries comply with the requirements of human rights treaties that they join? Are these treaties effective in changing states' behavior for the better? This Article addresses these questions through a large-scale quantitative analysis of the relationship between human rights treaties and countries' human rights practices. The analysis relies on a database encompassing 166 nations over a nearly forty-year period in five areas of human rights law. The analysis finds that although the practices of countries that have ratified human rights treaties are generally better than those of countries that have not, noncompliance with treaty obligations appears common. More paradoxically, controlling for other factors that affect practices, it appears that treaty ratification is not infrequently associated with worse practices than otherwise expected. These findings can be explained in part, the Article contends, by the dual nature of treaties as both instrumental and expressive instruments. Treaties not only create binding law, but also declare or express the position of countries that ratify them. Because human rights treaties tend to be weakly monitored and enforced, countries that ratify may enjoy the benefits of this expression-including, perhaps, reduced pressure for improvements in practices-without bearing significant costs. This does not mean that human rights treaties do not have any positive influence, but simply that these positive effects may sometimes be offset or even outweighed by treaties' less beneficial effects. The Article concludes by considering better ways to help ensure that human rights treaties improve the lives of those they are meant to help.
Research on Glowworm Swarm Optimization with Ethnic Division

Glowworm swarm optimization (GSO) algorithm is a new intelligent optimization algorithm. Based on the problems of GSO, such as easy to fall into local optimum, slow convergence speed and low optimization precision, an improved GSO with group division is presented. Using shuffled frog leaping algorithm (SFLA), glowworms are divide into different ethnic groups, and local search and global information exchange method improves the GSO performance. The mechanism based on particle position update mechanism in PSO is proposed in order to improve glowworm diversity. By using chaos optimization technique, glowworm groups are initialized, and the algorithm can obtain high quality initial solutions group. Finally, with the classical test functions, the simulation results show that, the GSO with hybrid behavior has better convergence speed and precision. According to the different types of firefly and cold light color is not the same, the glowworm swarm is divided into two sub group, to complete the aspects of paired glowworm swarm population quantity change. Then the cloth Valley bird search algorithm, cloth Valley bird by Levi to fly to the best way to choose size, this kind of flying mode with the machine more strong, will this flight mode into two populations of fireflies swarm evolutionary algorithm. Finish the fireflies optimization path of improvement.
Leading Public Sector Innovation

In a time of unprecedented turbulence, how can public sector organisations increase their ability to find innovative solutions to society's problems? "Leading public sector innovation" shows how government agencies can use co-creation to overcome barriers and deliver more value, at lower cost, to citizens and business. Through inspiring global case studies and practical examples, the book addresses the key triggers of public sector innovation. It shares new tools for citizen involvement through design thinking and ethnographic research, and pinpoints the leadership roles needed to drive innovation at all levels of government. "Leading public sector innovation" is essential reading for public managers and staff, social innovators, business partners, researchers, consultants and others with a stake in the public sector of tomorrow. "This is an excellent book, setting out a clear framework within which the practical issues involved in public sector innovation are explored, using insights drawn from extensive practical experience of implementing and supporting it. It draws on an impressive range of research and relevant wider experience in both public and private sectors and is written in a clear and persuasive style. The book offers an excellent synthesis of principles, practices and tools to enable real traction on the innovation management problem and it ought to find a place on any manager's bookshelf. " John Bessant, Director of Research and Knowledge Transfer and Professor of Innovation and Entrepreneurship, University of Exeter Business School
There's always hope: Enhancing agent believability through expectation-based emotions

To endow virtual agents with more realistic affective behavior, the notion of expectation-based emotions plays an important role: emotional states of agents should not only be triggered by present stimuli, but also by anticipation on future stimuli, and evaluation of past stimuli in the context of these anticipations. Within this study, an extension of the belief-desire-intention (BDI) model with expectation-based emotions is proposed. The model has been implemented in the modeling language LEADSTO. In addition, a game application has been developed, in which a user can play a dice game against an agent that is equipped with the emotion-based model. An empirical evaluation indicates that the model significantly enhances the agent's believability, in particular concerning its involvement in the situation.
Knowledge Discovery using Text Mining: A Programmable Implementation on Information Extraction and Categorization

Textual data in electronic documents today around the world have no doubt brought forward all the information one could need and as data banks build up worldwide, and access gets easier through technology, it has become easier to overlook vital facts and figures that could bring about groundbreaking discoveries. This research paper discusses in detail an implementation of Information Extraction and Categorization in the text mining application that we have implemented. To extract terms from the document we have used modified version of Porter’s Algorithm for inflectional stemming. For calculating term frequencies for categorization, we have used a domain dictionary for ‘Computer Science’ domain.
A Model-Based Background Adjustment for Oligonucleotide Expression Arrays

High-density oligonucleotide expression arrays are widely used in many areas of biomedical research. Affymetrix GeneChip arrays are the most popular. In the Affymetrix system, a fair amount of further preprocessing and data reduction occurs after the image-processing step. Statistical procedures developed by academic groups have been successful in improving the default algorithms provided by the Affymetrix system. In this article we present a solution to one of the preprocessing steps—background adjustment—based on a formal statistical framework. Our solution greatly improves the performance of the technology in various practical applications. These arrays use short oligonucleotides to probe for genes in an RNA sample. Typically, each gene is represented by 11–20 pairs of oligonucleotide probes. The first component of these pairs is referred to as a perfect match probe and is designed to hybridize only with transcripts from the intended gene (i. e., specific hybridization). However, hybridization by other sequences (i. e., nonspecific hybridization) is unavoidable. Furthermore, hybridization strengths are measured by a scanner that introduces optical noise. Therefore, the observed intensities need to be adjusted to give accurate measurements of specific hybridization. We have found that the default ad hoc adjustment, provided as part of the Affymetrix system, can be improved through the use of estimators derived from a statistical model that uses probe sequence information. A final step in preprocessing is to summarize the probe-level data for each gene to define a measure of expression that represents the amount of the corresponding mRNA species. In this article we illustrate the practical consequences of not adjusting appropriately for the presence of nonspecific hybridization and provide a solution based on our background adjustment procedure. Software that computes our adjustment is available as part of the Bioconductor Project (http://www.bioconductor.org).
Implementing dynamic implied addressing mode for multi-output instructions

The ever-increasing demand for faster execution time, smaller resource usage and lower energy consumption has compelled architects of embedded processors to adopt more specialized hardware features with irregular data paths and heterogeneous registers that are customized to the needs of their target applications. These processors consequently provide a rich set of specialized instructions in order to enable programmers to access these features. Such an instruction is typically a multi-output instruction (MOI), which outputs multiple results parallely in order to exploit inherent underlying hardware parallelism. Earlier study has exhibited that MOIs help to enhance performance in aspect of instruction counts and code size. However, as MOIs require more operands, they tend to increase not only the size of the instruction set but also the size of individual instructions. This can be a serious setback for embedded processors, which are mostly subject to strong resource limitations (particularly in this case, limited instruction encoding space). For this reason, these processors are often allowed to include only a very small subset of the total desired MOIs in their instruction sets, despite there can be sufficient silicon real estate to accommodate these specialized MOIs. To attack this problem, we introduce a novel instruction encoding scheme based on the dynamic implied addressing mode (DIAM). In this paper, we will discuss how we have overcome the encoding space problem for our target embedded processor whose instruction set has been augmented with a variety of MOIs. Our DIAM-based encoding scheme employs a small on-chip buffer to supplement extra encoding information for MOIs at run time. The empirical results are promising: the scheme allows us to encode many more MOIs for our processor; thereby helping us to achieve considerable reduction of code size as well as running time after the DIAM is additively implemented in the original architecture.
Delay Modelling for Buffered RLC / RLY Trees

For deep-submicron, high-performance circuits, the inductive effect plays a very important role in determining the circuit delay. In this paper, we derive accurate formulae for modeling the delays of buffered RLY/RLC wires and trees. Our formulae can handle balanced and un-balanced trees and consider buffer insertion. Extensive simulations with HSPICE show that the formulae have high fidelity, with an average error of within 5.51% based on the 180 nm technology. The simulations show that our formulae are more accurate than previous works.
Environmental Digital Library Systems

The characteristics of environmental data present a challenge to the providers of this type of information. Both the wide variety of data types and the large size that typify environmental data objects combine to make it especially difficult to manage. Digital library technology shows promise for the management of environmental data. This paper surveys numerous environmental digital library and related systems that have been designed and implemented for this task.
Robust Beamforming Against Direction-of-Arrival Mismatch Using Subspace-Constrained Diagonal Loading

In this study, a new subspace-constrained diagonal loading (SSC-DL) method is presented for robust beamforming against the issue of a mismatched direction of arrival (DoA), based on an extension to the well known diagonal loading (DL) technique. One important difference of the proposed SSC-DL from conventional DL is that it imposes an additional constraint to restrict the optimal weight vector within a subspace whose basis vectors are determined by a number of angles neighboring to the estimated DoA. Unlike many existing methods which resort to a beamwidth expansion, the weight vector produced by SSC-DL has a relatively small beamwidth around the DoA of the target signal. Yet, the SSC-DL beamformer has a great interference suppression level, thereby achieving an improved overall SINR performance. Simulation results suggest the proposed method has a near-to-optimal SINR performance.
A Bayesian Approach to Efficient Diagnosis of Incipient Faults

Safe, reliable, and efficient operation of complex dynamical systems requires the ability to detect, isolate, and identify degradation in system components. Degradations are typically modeled as incipient faults, which are slow drifts in system parameters over time. This paper presents an efficient approach for the detection, isolation, and identification of incipient faults under uncertainty using a Dynamic Bayesian Network (DBN) approach. Initially a DBN is used as an observer to track nominal system behavior. Once a fault is detected, incipient fault hypotheses are generated using a variation of our qualitative TRANSCENDapproach for abrupt fault isolation. A modified DBN that includes the active fault hypotheses is then used to isolate the true fault and estimate the rate of change in its parameter value.
Analytical models for an Ethernet-like local area network link

Ethernet -like local area network links have been studied by a number of researchers. Most of these studies have involved extensive simulation models operating at the level of individual packets. However, as we begin building models of systems built around such links, detailed simulation models are neither necessary, nor cost-effective. Instead, a simple analytical model of the medium should be adequate as a component of the higher level system models. This paper discusses a number of analytical models and identifies a last-in-first-out M/G/1 model with slightly increased service time as one which adequately captures both the mean and the coefficient of variation of the response time. Given any offered load, this model can be used to predict the mean waiting time and its coefficient of variation. These two can be used to construct a suitable 2 stage hyperexponential distribution. Random numbers can then be drawn from this distribution for use as waiting times of individual packets.