Miracle-dz/UniFAR-FTUs huggingface dataset:
A Closer Look at the “ Anomalous ” V-Shaped Earnings-Equity Value Relation in a Real Options Framework with Investor Learning

A Closer Look at the “Anomalous” V-Shaped Earnings-Equity Value Relation in a Real Options Framework with Investor Learning This study examines how earnings are related to equity value in a real options framework. Collins, Pincus, and Xie (1999) argue that the “anomalous” negative price-earnings relation for loss firms as described by Burgstahler (1998) is caused by a misspecified earnings capitalization model and the phenomenon disappears when book value of equity is included in the valuation model. We focus on R&D intensive firms and show that the earnings-equity value relation has a V-shaped pattern that does not disappear after controlling for book value of equity. We derive our predicted earnings-equity value relation from a real options valuation model in which a firm optimally waits to invest in or abandon R&D projects, and we allow for investor learning about the quality of a firm’s R&D. Based on simulations under different R&D success and firm age scenarios, we derive three predictions: (1) there is a V-shaped relation between earnings and equity value that (2) changes with firm age and (3) and with its R&D quality. That is, earnings are less associated with equity value for more mature firms and earnings of lower R&D quality firms are valued less than these of higher R&D quality firms. We empirically check our predictions in a sample of traditional pharmaceutical firms and another sample of biotechnology firms. Our three predictions are supported in the data. We conclude that the earnings number is picking up different aspects of the cash flows that are valued by investors across a firm’s life cycle and R&D success rate.
Image denoising using non-negative sparse coding shrinkage algorithm

This paper proposes a new method for denoising natural images using our extended non-negative sparse coding (NNSC) neural network shrinkage algorithm, which is self-adaptive to the statistic property of natural images. The basic principle of denoising using NNSC shrinkage is similar to that using standard sparse shrinkage and wavelet soft threshold. Using test images corrupted by additive Gaussian noise, we evaluated the method across a range of noise levels. We utilized the normalized mean squared error as a measure of the quality of denoising images and the signal to noise rate (SNR) value as an evaluative feature of different denoising approaches. The experimental results prove that the NNSC shrinkage certainly is effective in image denoising. Otherwise, we also compare the effectiveness of the NNSC shrinkage with sparse coding shrinkage and wavelet soft threshold method. The simulative tests show that our denoising method outperforms any other of the two kinds of denoising approaches.
Triad-NVM: Persistency for Integrity-Protected and Encrypted Non-Volatile Memories

Non-Volatile Memory is here and provides an attractive fabric for main memory. Unlike DRAM, non-volatile main memory (NVMM) retains data after power loss. This allows memory to host data persistently across crashes and reboots, but opens up opportunities for attackers to snoop and/or tamper with data between boot episodes. While memory encryption and integrity verification have been well studied for DRAM systems, new challenges surface for NVMM if we want to simultaneously preserve security guarantees, data recovery across crashes/reboots, good persistence performance, and fast recovery. In this paper, we explore persistency of data with all security metadata (counters, MACs, and Merkle Tree) to achieve secure persistency. We show that to ensure security guarantees, message authentication code (MAC) and Bonsai Merkle Tree (BMT) need to be maintained, in addition to counters, and they provide the majority of persistency overheads. We analyze the requirements for achieving secure persistency for both persistent and non-persistent memory regions. We found that the non-volatility nature of memory may trigger integrity verification failure at reboot, hence we propose a separate mechanism to support non-persistent memory region. Fourth, we propose designs to make recovery fast. Our evaluation shows that the proposed design, Triad-Nvm, can improve the throughput by an average of 2× relative to strict persistence. Moreover, Triad-NVM can achieve orders of magnitude faster recovery time compared to systems without security metadata persistence.
Research on file system and its self computing based on memristor

Magnetic change memory, resistive change memory, phase change memory are promising non-volatile memory whose file system is worthy of study. Because the memristor is not commercial yet, few works focus on the file system of memristor. This paper presents a scheme of file system as well as data management based on memristor. What's more, the data comparison in the file system oriented to memristor is designed based on its state logic function. It can reduce the number of reading and writing data in file system and the CPU computing time.
Ontology-based information retrieval and extraction

Using domain knowledge and semantics to conduct effective information retrieval (IR) is one of the major challenges in IR. In this paper we introduce a framework that can facilitate information retrieval based on a sharable domain ontology. Specifically we conduct semantic annotation on the descriptive metadata of images or articles and convert metadata automatically into machine readable format in terms of semantic Web representation. The retrieval of an image instance or information extraction of an historic question can then be conducted by matching the semantic and structural descriptions of the user query based on those of the annotated descriptive metadata. We show that with aid of domain ontology, an IR system can achieve a better performance than the keyword-based information retrieval systems.
Diagram Analysis using Context-Based Constraint Grammars 1

This report presents a constraint-based grammar formalism which can be used for the specification and efficient syntactic analysis of a variety of types of complex diagrams. The significant concepts developed for this work are: the use of constraints and inherited attributes to successively delimit the objects considered until the desired solution sets are obtained, the performance of top-down analysis to effectively direct the parsing process, and the fact that objects are allowed to participate in more than one structure. The above ideas, along with the addition of set types to the grammar and spatial indexing of the data, make it possible to efficiently parse real diagrams of substantial complexity. The current work demonstrates efficient diagram parsing coupled to simple domain retargeting by writing alternate grammars. The classes of diagrams that we have analyzed include x,y data graphs and genetic diagrams drawn from the biological literature, as well as finite state automata diagrams (states and arcs).
Flavopiridol Protects Against Inflammation by Attenuating Leukocyte-Endothelial Interaction via Inhibition of Cyclin-Dependent Kinase 9

Objective—The cyclin-dependent kinase (CDK) inhibitor flavopiridol is currently being tested in clinical trials as anticancer drug. Beyond its cell death–inducing action, we hypothesized that flavopiridol affects inflammatory processes. Therefore, we elucidated the action of flavopiridol on leukocyte–endothelial cell interaction and endothelial activation in vivo and in vitro and studied the underlying molecular mechanisms. Methods and Results—Flavopiridol suppressed concanavalin A–induced hepatitis and neutrophil infiltration into liver tissue. Flavopiridol also inhibited tumor necrosis factor-&agr;–induced leukocyte–endothelial cell interaction in the mouse cremaster muscle. Endothelial cells were found to be the major target of flavopiridol, which blocked the expression of endothelial cell adhesion molecules (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, and E-selectin), as well as NF-&kgr;B-dependent transcription. Flavopiridol did not affect inhibitor of &kgr;B (I&kgr;B) kinase, the degradation and phosphorylation of I&kgr;B&agr;, nuclear translocation of p65, or nuclear factor-&kgr;B (NF-&kgr;B) DNA-binding activity. By performing a cellular kinome array and a kinase activity panel, we found LIM domain kinase-1 (LIMK1), casein kinase 2, c-Jun N-terminal kinase (JNK), protein kinase C&thgr; (PKC&thgr;), CDK4, CDK6, CDK8, and CDK9 to be influenced by flavopiridol. Using specific inhibitors, as well as RNA interference (RNAi), we revealed that only CDK9 is responsible for the action of flavopiridol. Conclusion—Our study highlights flavopiridol as a promising antiinflammatory compound and inhibition of CDK9 as a novel approach for the treatment of inflammation-associated diseases.
Environmental Tobacco Smoke in the Workplace Induces Oxidative Stress in Employees, Including Increased Production of

Environmental tobacco smoke (ETS) is a pervasive contaminant in the workplace. Our objective was to determine the oxidative stress effects of ETS on employees who are exposed. The results provide information that is useful to the resolution of risk assessment questions associated with ETS. We analyzed two blood draws from volunteers in our control and exposed groups. The level of exposure to ETS was determined through plasma cotinine measurements, which showed a 65% increase from the control group to the exposed group. Exposure to ETS resulted in a statistically significant increase of 63% of the oxidative DNA mutagen 8-hydroxy-2’-deoxyguanosine in the blood of exposed subjects. This oxidative DNA damage has been linked to an increased risk of developing several degenerative chronic diseases, including coronary heart disease and cancer. The exposed subjects also had increased levels of superoxide dismutase, catalase, glutathione peroxidase (GPOX), and glutathione reductase. However, these increases were only statistically significant in catalase and GPOX. Catalase levels were 13% higher in the exposed group, and GPOX levels were 37% higher in exposed volunteers. The biochemical evidence suggests that exposure to ETS causes oxidative stress, resulting in DNA damage that may increase the risk of certain diseases.
Facilitation of serotonin-induced contraction of rat mesenteric artery by ketamine

Ketamine is an anesthetic with hypertensive effects, which make it useful for patients at risk of shock. However, previous ex vivo studies reported vasodilatory actions of ketamine in isolated arteries. In this study, we reexamined the effects of ketamine on arterial tones in the presence and absence of physiological concentrations of 5-hydroxytryptamine (5-HT) and norepinephrine (NE) by measuring the isometric tension of endothelium-denuded rat mesenteric arterial rings. Ketamine little affected the resting tone of control mesenteric arterial rings, but, in the presence of 5-HT (100~200 nM), ketamine (10~100 µM) markedly contracted the arterial rings. Ketamine did not contract arterial rings in the presence of NE (10 nM), indicating that the vasoconstrictive action of ketamine is 5-HT-dependent. The concentration-response curves (CRCs) of 5-HT were clearly shifted to the left in the presence of ketamine (30 µM), whereas the CRCs of NE were little affected by ketamine. The left shift of the 5-HT CRCs caused by ketamine was reversed with ketanserin, a competitive 5-HT2A receptor inhibitor, indicating that ketamine facilitated the activation of 5-HT2A receptors. Anpirtoline and BW723C86, selective agonists of 5-HT1B and 5-HT2B receptors, respectively, did not contract arterial rings in the absence or presence of ketamine. These results indicate that ketamine specifically enhances 5-HT2A receptor-mediated vasoconstriction and that it is vasoconstrictive in a clinical setting. The facilitative action of ketamine on 5-HT2A receptors should be considered in ketamine-induced hypertension as well as in the pathogenesis of diseases such as schizophrenia, wherein experimental animal models are frequently generated using ketamine.
An Ontology for Managing a Virtual Environment for Risk Prevention

In this paper we present how we combine artificial intelligence and knowledge engineering to provide an ontology inspired approach in order to manage a virtual environment for risk prevention. In the virtual environment, different entities cohabit: virtual operators represented by cognitive agents and the learner’s avatar that represents a real operator. They can interact with the objects through actions and modify their state. It is therefore useful to have on one hand a system that specifically defines the framework in which the interactions or actions are allowed and on the other hand a representation of the knowledge involved in such interactions. The ontology models the objects of the environment, the agents operating in the environment, the events that can happen, the actions and the relations between all such concepts. We proposed an agent, COLOMBO, containing the developed ontology and a set of reasoning rules.
Multiview Image Compression : Future Challenges and Today ’ s Solutions

Large data volumes that are produced during multiview image generation have to be efficiently compressed in order to be stored or transmitted. Two main classes of encoders use transform coding techniques either by utilizing spatial prediction methods or by using higher degree transforms. Our work summarizes the various types of multiview image sets and the corresponding coding techniques and, provides a useful comparison of the compression efficiency of these two classes of multiview image encoders over a variety of test images. Representation quality and application specific requirements are taken into account in order to decide in favour of the encoder to be used.
Environmental Noise Variability in Population Dynamics Matrix Models

The impact of environmental variability on population size growth rate in dynamic models is a recurrent issue in the theoretical ecology literature. In the scalar case, R. Lande pointed out that results are ambiguous depending on whether the noise is added at arithmetic or logarithmic scale, while the matrix case has been investigated by S. Tuljapurkar. Our contribution consists first in introducing another notion of variability than the widely used variance or coefficient of variation, namely the so-called convex orders. Second, in population dynamics matrix models, we focus on how matrix components depend functionaly on uncertain environmental factors. In the log-convex case, we show that, in a sense, environmental variability increases both mean population size and mean log-population size and makes them more variable. Our main result is that specific analytical dependence coupled with appropriate notion of variability lead to wide generic results, valid for all times and not only asymptotically, and requiring no assumptions of stationarity, of normality, of independency, etc. Though the approach is different, our conclusions are consistent with previous results in the literature. However, they make it clear that the analytical dependence on environmental factors cannot be overlooked when trying to tackle the influence of variability.
Transfer Learning For Message Passing Algorithm

— A new learning scenario, Transfer Learning (TL) has improves learning performance when the data can be in different feature spaces and where no correspondence between data instances in these spaces is provided. Transfer learning has been used to present image clustering as an example to illustrate how unsupervised learning can be improved by transferring knowledge from auxiliary data. This paper proposes a new and far more efficient method of Transfer Learning for Message Passing Algorithm. Based on this they cluster a small collection of images using readily available annotated image data so as to improve the speed and performance of clustering and also to measure the quality of our clustering results. Message Passing was recently introduced as an unsupervised learning algorithm for exemplar based clustering. It operates by simultaneously considering all data point as potential exemplars and exchanging messages between data points until a good set of exemplars and clusters emerges. This Algorithm improves the speed and performance of our clustering. Speed and Performance is measured in terms of Entropy and F-measure.
An enhanced cooperative transmit diversity in integrated MSS systems

In this paper, we propose an enhanced cooperative transmit diversity scheme in integrated mobile satellite service (MSS) systems. The proposed scheme is an efficient technique to adapt various power differences between a satellite signal and CGC signals, depending on the position of user equipments in integrated MSS systems. In the proposed scheme, we utilize modified space-time block coding (STBC) in order to realize the transmit diversity for the mobile satellite system with several complementary ground components (CGCs). The satellite and two groups of CGCs operate in unison the send the encoded signals, so that the receiver may realize diversity gain. The simulation results show that the proposed method can provide stable improved performance.
Suicide risk in the detachment from reality: failures in the quest for love that saves

Suicide is among the leading causes of death worldwide, accounting for almost one million annual deaths globally. The author presents an exploration into the suicidal mind using Freud's cathexis and decathexis theory. This model describes the patient’s withdrawal from reality and the need to gratify libidinal and aggressive drives in the internal world. Theories and beliefs of other authors are used to introduce the importance of early disturbed relationships with parental figures. Working with the particular subtype of suicidal patient described in this essay may be a challenge for clinicians. A psychodynamic approach may help in the understanding of the patient’s complex and private world of psychological pain. If unresolved, the patient’s conflicts may precipitate suicide.
Multilingual Food and Health Ontology Learning Using Semi-Structured and Structured Web Data Sources

The availability of open Web-based information sources such as Wikipedia in semi-structured format made it possible to build or extend multilingual domain ontologies. This work is a part of a project where we are developing a framework for semantic manipulation of health and nutrition information. In this paper, we present ongoing work aiming to build such ontology utilizing Wikipedia and other multilingual online resources automatically. The constructed ontology consists of monolingual ontologies and language-agnostic ontology connecting them. The constructed ontology is built to capture the culture-relevant aspects for each language based on the available concepts for each language. The ontology then could be used in many applications such as cross-lingual information access and multilingual information extraction for the domains of Food and Health. An initial evaluation shows the effectiveness and correctness of the constructed ontology.
Envelope tomography of long-period variable stars ?;?? III. Line-doubling frequency among Mira stars

This paper presents statistics of the line-doubling phenomenon in a sample of 81 long-period variable (LPV) stars of various periods, spectral types and brightness ranges. The set of observations consists of 315 high- resolution optical spectra collected with the spectrograph ELODIE at the Haute-Provence Observatory, during 27 observing nights at one-month intervals and spanning two years. When correlated with a mask mimicking a K0III spectrum, 54% of the sample stars clearly showed a double-peaked cross-correlation prole around maximum light, reflecting double absorption lines. Several pieces of evidence are presented that point towards the double absorption lines as being caused by the propagation of a shock wave through the photosphere. The observation of the Balmer lines appearing in emission around maximum light in these stars corroborates the presence of a shock wave. The observed velocity discontinuities, ranging between 10 and 25 km s 1 , are not correlated with the brightness ranges. A comparison with the center-of-mass (COM) velocity obtained from submm CO lines originating in the circumstellar envelope reveals that the median velocity between the red and blue peaks is blueshifted with respect to the COM velocity, as expected if the shock moves upwards. The LPVs clearly exhibiting line-doubling around maximum light with the K0III mask appear to be the most compact ones, the stellar radius being estimated from their eective temperatures (via the spectral type) and luminosities (via the period-luminosity relationship). It is not entirely clear whether or not this segregation between compact and extended LPVs is an artefact of the use of the K0III mask. Warmer masks (F0V and G2V) applied to the most extended and coolest LPVs yield asymmetric cross-correlation functions which suggest that line doubling is occurring in those stars as well. Although a rm conclusion on this point is hampered by the large correlation noise present in the CCFs of cool LPVs obtained with warm masks, the occurrence of line doubling in those stars is conrmed by the double CO v = 3 lines observed around 1.6 m by Hinkle et al. (1984, ApJS, 56, 1). Moreover, the H line in emission, which is another signature of the presence of shocks, is observed as well in the most extended stars, although with a somewhat narrower prole. This is an indication that the shock is weaker in extended than in compact LPVs, which may also contribute to the diculty of detecting line doubling in cool, extended LPVs.
MiBoard: iSTART Metacognitive Training through Gaming

MiBoard (Multiplayer Interactive Board Game) is an online, turn-based board game, which is a supplement of the iSTART (Interactive Strategy Training for Active Reading and Thinking) application. MiBoard is developed to test the hypothesis that integrating game characteristics (point rewards, game-like interaction, and peer feedback) into the iSTART trainer will significantly improve its effectiveness on students' learning. It was shown by M. Rowe that a physical board game did in fact enhance students' performance. MiBoard is a computer-based version of Rowe's board game that eliminates constraints on locality while retaining the crucial practice components that were the game's objective. MiBoard gives incentives for participation and provides a more enjoyable and social practice environment compared to the online individual practice component of the original trainer