Miracle-dz/UniFAR-FTUs huggingface dataset:
The Information Content of Negative Earnings and its Relation with Initial-Loss Persistence

This study examines the information content of negative earnings and the relation between that information content and the persistence of negative earnings. Recent studies have found evidence that negative earnings convey significantly less information than positive earnings. One reason for this result may be the difference between the expected persistence of gains and losses. This study extends prior literature by studying the relation between negative earnings and persistence. I first provide evidence of the information content of initial-loss-year earnings. I then develop evidence that the information content of losses is related to the persistence of the loss. Specifically, I find that initial losses from single-year loss periods have less information content than initial losses from multi-year loss periods. Second, I find evidence that initial losses have significantly more information content than subsequent losses. Third, I find a significant difference in the information content of losses across groups of firms with different levels of initial-loss persistence. The study concludes with an examination of the potential usefulness of financial statement information for predicting initial-loss persistence.
Try again. Fail again. Fail better. Analysis of the contribution of 65 evaluations to the modernisation of public action in France

« Modernisation of Public Action » (MAP) was an initiative to make evaluation the main instrument of reform for public policies at State level in France: 80 evaluations were launched between 2012 and 2017. MAP is the late child of both « evaluation à la française » (a 1990s attempt to make evaluation a way to reinvent democracy) and RGPP (a policy review aimed at cost-cutting under President Sarkozy). We explain how this strange combination set the expectations for the MAP. We undertook a metaevaluation to assess the quality of the evaluations, which put a very high emphasis on use, but were initially lacking some basic features such as evaluation questions or an intervention logic. However they improved over time. Finally, using contribution analysis and Process Tracing, we subject 8 evaluation processes to 10 empirical tests to assess their use. We show the diversity of impact pathways leading to reform (or lack thereof), some of which are unexpected, stressing the importance of context and attitude of stakeholders in the impacts that can be expected.
A simple hybrid movie recommender system

A simple hybrid movie recommender system is described that combines content based and collaborative modelling and provides an explanation for increased user acceptance. The system uses rating data from the Netflix database which is linked to content information from the Internet Movie Database. In order to provide the user with insight into the reasoning behind a recommendation, the system creates an HTML page with a detailed explanation. Performance results are presented as well as a discussion on future improvements.
A Highly Robust Method for Face Authentication

This paper proposes a highly robust method for face authentication. Techniques introduced in this work are composed of two stages. Firstly, the feature of face is to be detected by the principle of Trace Transform. Then, in the second stage, the Hausdorff-Shape Context is employed to measure and determine of similarity between models and test images. From the experimental result of 2,520 images form ORL and Yale database, the accuracy rate is very high.
Optical antennas and plasmonics

Optical antenna is a nanoscale miniaturisation of radio or microwave antennas that is also governed by the rule of plasmonics. We introduce various types of optical antenna and make an overview of recent developments in optical antenna research. The role of local and surface plasmons in optical antenna is explained through antenna resonance and resonance conditions for specific metal structures are explicitly obtained. A strong electric field is shown to exist within a highly localised region of optical antennas such as antenna feed gap or apertures. We describe physical properties of field enhancement in apertures (circular and rectangular holes) and gaps (infinite slit and feed gap), as well as experimental techniques measuring enhanced electric vector field. We discuss the analogies and differences between conventional and optical antennas with a projection for future developments.
Reduction in Left Ventricular Wall Stress and Improvement in Function in Failing Hearts using Algisyl-LVR

Injection of Algisyl-LVR, a treatment under clinical development, is intended to treat patients with dilated cardiomyopathy. This treatment was recently used for the first time in patients who had symptomatic heart failure. In all patients, cardiac function of the left ventricle (LV) improved significantly, as manifested by consistent reduction of the LV volume and wall stress. Here we describe this novel treatment procedure and the methods used to quantify its effects on LV wall stress and function. Algisyl-LVR is a biopolymer gel consisting of Na+-Alginate and Ca2+-Alginate. The treatment procedure was carried out by mixing these two components and then combining them into one syringe for intramyocardial injections. This mixture was injected at 10 to 19 locations mid-way between the base and apex of the LV free wall in patients. Magnetic resonance imaging (MRI), together with mathematical modeling, was used to quantify the effects of this treatment in patients before treatment and at various time points during recovery. The epicardial and endocardial surfaces were first digitized from the MR images to reconstruct the LV geometry at end-systole and at end-diastole. Left ventricular cavity volumes were then measured from these reconstructed surfaces. Mathematical models of the LV were created from these MRI-reconstructed surfaces to calculate regional myofiber stress. Each LV model was constructed so that 1) it deforms according to a previously validated stress-strain relationship of the myocardium, and 2) the predicted LV cavity volume from these models matches the corresponding MRI-measured volume at end-diastole and end-systole. Diastolic filling was simulated by loading the LV endocardial surface with a prescribed end-diastolic pressure. Systolic contraction was simulated by concurrently loading the endocardial surface with a prescribed end-systolic pressure and adding active contraction in the myofiber direction. Regional myofiber stress at end-diastole and end-systole was computed from the deformed LV based on the stress-strain relationship.
On the modeling of dielectric charging in RF-MEMS capacitive switches

The dielectric charging in RF MEMS capacitive switches is modeled. The modeling focus on charge injections processes and the calculations start from first principles. The calculations were performed on materials with uniform and exponential distribution of defects. The time and bias dependence of distribution of injected charges are derived. The dielectric charging/polarization build-up is derived and found to obey the stretched exponential law, a result being supported by experimental data in various dielectrics.
Ga ing Technique : An Ass SSlllent and Training Tool for In ividuals with Learning Deficits ( menta retardation , developmental delay , hoard games )

In this article the literature on gaming techmque is reviewed as applied to life simulation experiences. The gaming technique is the use or the adaptation of existing games or the development of training games. Training games aTe useful educational tools to teach daily living skills to the mild to moderate mentally retarded population and other individuals with learning deficits. The author discusses the application of games to a variety of traming situations in the occupational therapy clime and summarizes techniques for making an adaptation of or for constructmg games. Four games are included: a pegboard game, a friendship or socialization game, a money-calculator game, and a disaster game.
Adaptive Bug Classification for CVE List using Bayesian Probabilistic Approach

Software bug classification is a precondition for bug fixation and it plays a vital role in software maintenance. It is found that bug fixation often takes long due to the distribution of misclassified or non-classified bugs by the triager among the developers. In this paper, we propose an adaptive bug classification approach on CVE dataset that involves two Bayesian classifiers such as Naive Bayes and Bayes net, and takes adaptive decision for classification. Naive Bayes is a classification algorithm which adopts a naive approach regarding class conditional distribution during classification and assumes that all the features of a sample are conditionally independent given the class label. Bayes net is a graphical representation of a set of random variables and their conditional dependencies via a directed acyclic graph. It can be used for knowledge representation as well as classification. Exploiting the domain knowledge about the bug class, we conduct the experiments from two different view points group-based approach and general approach. In case of groupbased approach, both classifiers are learned using the bug groupspecific samples and selected features from five groups. In case of general approach, 28,266 bug samples and 64 bug features are considered. Experiments show that Bayes net classifier has more potential than Naive Bayes for classification with CVE dataset and therefore it is preferable. However, it is also found that Naive Bayes classifier performs fairly well in CVE bug classification due to its simplistic concept and less number of parameters.
Situational Data-Analytics for the Web-of-Things

The proliferation of web-accessible sensors and actuators provided by smart things and mobile devices has led to a distinct class of WoT-applications. These are data-driven and situational as they build on the analytical processing of data streams from specific devices in the user context. Promising approaches for supporting such applications have emerged that enable a) the compositional specification of device stream processing and b) the distributed execution of processing pipelines on edge devices. In this paper we report on experiences of applying one such approach in order to realize our vision for scenarios of situational WoT-applications. We discuss the requirements of these advanced scenarios and propose possible future directions for features and architectural approaches of a WoT-platform.
Differences in public acceptance between generic and premium branded GM food products: an analytical model.

Biotechnology is an enormously expanding discipline with various applications in the medical, agricultural and food sector. The use of genetic modification technology in food production is only one example, nevertheless a very important one. It offers new perspectives for product development, cost reduction and environmental protection. According to the White Paper, modern biotechnology includes an impulse for competitiveness and economic growth (European Commission, 1994). However, biotechnology in general and genetically modified (GM) food in particular came recently to the forefront of public attention. Abundant questions are being asked about safety for human health and for the environment, ethics, free consumer choice, socio-economic and legal issues. Public support is especially low for biotechnology applications in the food sector. Europeans show more concern and resistance towards GM food compared with other parts of the world (Table 3.1). These consumer concerns seriously jeopardize the future market success of modern biotechnology products, including GM food products (EFB Task Group on Public Perceptions of Biotechnology, 1998, 1999). Consequently, gaining insight into consumer beliefs, attitudes and behavioural intentions concerning GM food is essential.1 Against this background, the objective of this chapter is twofold:
Under-Updated Particle Swarm Optimization for Small Feature Selection Subsets from Large-Scale Datasets

Feature selection is the process of choosing a subset of features from the original larger set that are related to a certain outcome, such as disease type, dose, income, and time to event. The use of feature selection procedures is almost compulsory and complex in biology and medicine because the generation of massive datasets is nowadays common for many stateof-the-art technologies such as transcriptomics, proteomics, metabolomics, and genomics where a single, conventional, and relatively cheap experiment may yield the measurement of several thousands of features per sample (Hieter and Boguski, 1997; Sauer et al., 2005). In such cases, feature selection is used to reduce complexity and large computational costs, as well as to improve pattern recognition accuracy, data interpretability and hypothesis generation (Shen et al., 2008; Vapnik, 1998; Guyon et al., 2002).
I am a sensor, and I approve this message

Despite the popularity of adding sensors to mobile devices, the readings provided by these sensors cannot be trusted. Users can fabricate sensor readings with relatively little effort. This lack of trust discourages the emergence of applications where users have an incentive to lie about their sensor readings, such as falsifying a location or altering a photo taken by the camera. This paper presents a broad range of applications that would benefit from the deployment of trusted sensors, from participatory sensing to monitoring energy consumption. We present two design alternatives for making sensor readings trustworthy. Although both designs rely on the presence of a trusted platform module (TPM), they trade-off security guarantees for hardware requirements. While our first design is less secure, it requires no additional hardware beyond a TPM, unlike our second design. Finally, we present the privacy issues arising from the deployment of trusted sensors and we discuss protocols that can overcome them.
Option pricing in the multidimensional Black-Scholes market with Vasicek interest rates

An explicit state-price deflator for the multidimensional Black-Scholes market with Vasicek stochastic interest rates is constructed. It is applied to obtain extensions of the Margrabe and Black-Scholes option pricing formulas. These formulas, which are validated in a multiple risk economy with stochastic interest rates, remain invariant under changing market prices of risk. Some comments including related research round up the expose.
Adaptive Network Precoding Based on SJNR to Mitigate Inter-Cell Interference

Focusing on the problem that the co-frequency interference of the downlink channels in multi-cell of multi-out multi-input (MIMO) systems, this paper used the adaptive network precoding based on the SJNR to reduce the inter-cell interference. First of all, the adaptive precoding design based on the SJNR criteria is given. In this design, each base station use independent precoding approach to suppress adjacent inter-cell interference. And then in order to decrease the handing complex by the active way, the adaptive network precoding is attained respectively in the urban and suburb area environments, two adaptive network precoding based on SJNR are obtained respectively. Simulation results show that the inter-cell interference was obviously restrained and the system performance was improved after using the active network precoding basing on the SJNR, but also reduced processing algorithms of system.
Combine use of Steganography and Visual Cryptography for Secured Data hiding in Computer Forensics

The proposed system highlights a novel approach for creating a secure steganographic method and visual cryptography for data hiding in computer forensics. Although there has been an extensive research work in the past, but majority of the research work has no much optimal consideration for robust security towards the encrypted image. The proposed method encodes the secret message in least significant bits of the original image, where the pixels values of the encrypted image are modified by the genetic algorithm to retain their statistic characters, thereby making the detection of secret of message difficult. Use of Genetic algorithm has compelled the system for enhancing the security. The proposed system hides data in a real image and achieve its detection after under went to visual cryptography. The main aim of the proposed model is to design a feasible RSresistance secure algorithm which combines the use of both steganography and visual cryptography for improving security, reliability and efficiency for secret message. The implementation is done in java platform which shows that the proposed system has better resilienc by considering the steganalysis. Keywords-Steganography, Visual Cryptograhy, Genetic Algorithm, RS Analysis
The Global Optimization Geometry of Nonsymmetric Matrix Factorization and Sensing

In this paper we characterize the optimization geometry of a matrix factorization problem where we aim to find $n\times r$ and $m\times r$ matrices $U$ and $V$ such that $UV^T$ approximates a given matrix $X^\star$. We show that the objective function of the matrix factorization problem has no spurious local minima and obeys the strict saddle property not only for the exact-parameterization case where $rank(X^\star) = r$, but also for the over-parameterization case where $rank(X^\star) r$. These geometric properties imply that a number of iterative optimization algorithms (such as gradient descent) converge to a global solution with random initialization. For the exact-parameterization case, we further show that the objective function satisfies the robust strict saddle property, ensuring global convergence of many local search algorithms in polynomial time. We extend the geometric analysis to the matrix sensing problem with the factorization approach and prove that this global optimization geometry is preserved as long as the measurement operator satisfies the standard restricted isometry property.
Quantification of Hydroxylated Polybrominated Diphenyl Ethers (OH-BDEs), Triclosan, and Related Compounds in Freshwater and Coastal Systems

Hydroxylated polybrominated diphenyl ethers (OH-BDEs) are a new class of contaminants of emerging concern, but the relative roles of natural and anthropogenic sources remain uncertain. Polybrominated diphenyl ethers (PBDEs) are used as brominated flame retardants, and they are a potential source of OH-BDEs via oxidative transformations. OH-BDEs are also natural products in marine systems. In this study, OH-BDEs were measured in water and sediment of freshwater and coastal systems along with the anthropogenic wastewater-marker compound triclosan and its photoproduct dioxin, 2,8-dichlorodibenzo-p-dioxin. The 6-OH-BDE 47 congener and its brominated dioxin (1,3,7-tribromodibenzo-p-dioxin) photoproduct were the only OH-BDE and brominated dioxin detected in surface sediments from San Francisco Bay, the anthropogenically impacted coastal site, where levels increased along a north-south gradient. Triclosan, 6-OH-BDE 47, 6-OH-BDE 90, 6-OH-BDE 99, and (only once) 6’-OH-BDE 100 were detected in two sediment cores from San Francisco Bay. The occurrence of 6-OH-BDE 47 and 1,3,7-tribromodibenzo-p-dioxin sediments in Point Reyes National Seashore, a marine system with limited anthropogenic impact, was generally lower than in San Francisco Bay surface sediments. OH-BDEs were not detected in freshwater lakes. The spatial and temporal trends of triclosan, 2,8-dichlorodibenzo-p-dioxin, OH-BDEs, and brominated dioxins observed in this study suggest that the dominant source of OH-BDEs in these systems is likely natural production, but their occurrence may be enhanced in San Francisco Bay by anthropogenic activities.
Improving bit error rate of STBC-OFDM using convolutional and turbo codes over Nakagami-m fading channel for BPSK modulation

In this paper, a new trend of Space Time Block codes-Orthogonal Frequency Division Multiplexing (STBC-OFDM) with Convolutional and Turbo codes. The applied method is based on Alamouti's scheme[1]. We examine the performance of two, three and four transmitters with one receiver over Nakagami-m fading channel using convolutional and turbo codes using BPSK. Also we examine their performance using turbo code with different rates (1/2, 1/3) at BPSK. The performance of two transmitters with two receivers is also shown using convolutional and turbo codes over Nakagami-m fading channel at BPSK.
Patients with Rheumatoid Arthritis and Chronic Pain Display Enhanced Alpha Power Density at Rest

Patients with chronic pain due to neuropathy or musculoskeletal injury frequently exhibit reduced alpha and increased theta power densities. However, little is known about electrical brain activity and chronic pain in patients with rheumatoid arthritis (RA). For this purpose, we evaluated power densities of spontaneous electroencephalogram (EEG) band frequencies (delta, theta, alpha, and beta) in females with persistent pain due to RA. This was a cross-sectional study of 21 participants with RA and 21 healthy controls (mean age = 47.20; SD = 10.40). EEG was recorded at rest over 5 min with participant's eyes closed. Twenty electrodes were placed over five brain regions (frontal, central, parietal, temporal, and occipital). Significant differences were observed in depression and anxiety with higher scores in RA participants than healthy controls (p = 0.002). Participants with RA exhibited increased average absolute alpha power density in all brain regions when compared to controls [F(1.39) = 6.39, p = 0.016], as well as increased average relative alpha power density [F(1.39) = 5.82, p = 0.021] in all regions, except the frontal region, controlling for depression/anxiety. Absolute theta power density also increased in the frontal, central, and parietal regions for participants with RA when compared to controls [F(1, 39) = 4.51, p = 0.040], controlling for depression/anxiety. Differences were not exhibited on beta and delta absolute and relative power densities. The diffuse increased alpha may suggest a possible neurogenic mechanism for chronic pain in individuals with RA.
Variations in Functional and Anatomical Outcomes and in Proliferative Vitreoretinopathy Rate along a Prospective Collaborative Study on Primary Rhegmatogenous Retinal Detachments: The Retina 1 Project—Report 4

Purpose. To analyse variations in the anatomical and functional outcomes and in proliferative vitreoretinopathy (PVR) rate of a prospective multicentric study that was primarily designed for identification of clinical risk factors for PVR. Methods. 1,046 retinal detachment (RD) cases were analysed. Cases were divided into two series based upon variation in PVR rate determined by logistic regression analysis. Series 1 (S1) included RD treated during 2004-2005 (n = 481) and Series 2 (S2) during 2006–2008 (n = 565). Pre-, intra-, and postoperative characteristics were recorded. Results. There were few differences in the preoperative characteristics. S2 had more vitrectomies and scleral bands and fewer explants and associated cataract extractions than S1. Anatomic reattachment improved from 87.9% to 92.9% in S1 and S2, respectively, (P = 0.006). Visual acuity at 3 months ≥20/40 increased from 36.5% of S1 to 44.2% in S2 (P = 0.049). PVR rate diminished from 14.1% in S1 to 8.1% in S2 (P = 0.002). Centres with higher rates of PVR in S1 showed the greatest reductions in S2. Conclusion. An improvement in anatomical and functional outcome and PVR rate occurred in participating centres cannot be attributed to the learning curve of surgeons. We speculated that it could be an effect of their participation in the study.