Miracle-dz/UniFAR-FTUs huggingface dataset:
Implied Volatilities as Forecasts of Future Volatility , the Market Risk Premia , and Returns Variability 1

The unbiasedness tests of implied volatility as a forecast of future realized volatility have found implied volatility to be a biased predictor. We explain this puzzle by recognizing that option prices contain a market risk premium not only on the asset itself, but also on its volatility. We show using a stochastic volatility model, that a call option price can be represented as an expected value of the Black-Scholes formula evaluated at the average integrated volatility. If we allow volatility risk to be priced, this expectation should be taken under the risk-neutral probability measure, and can be decomposed into the expectation with respect to the physical measure and the risk-premium term. This term is just a linear function of the unobservable spot volatility. The decomposition explains the bias documented in the empirical literature and shows that the realized and historical volatility, which are used in the tests, are in fact the estimates of the unobserved quadratic variation and spot volatility of the stock-return generating process. Therefore, the use of these estimates generates the error-in-the-variables problem. We provide an empirical example based on the S&P 100 returns and the VIX index. We find, that when we take into an account the risk-premium and use efficient methods to estimate volatility, the unbiasedness hypothesis can not be rejected, and the point estimate of the slope in the traditional regression is exactly equal to 1. JEL classification:
Trace anomaly and black holes evaporation

A model is proposed to describe a transition from a Schwarzschild black hole of mass $M_{0}$ to a Schwarzschild black hole of mass $M_{1}$ $\leq M_{0}$. The basic equations are derived from the non-vacuum Einstein field equations taking a source representing a null scalar field with a nonvanishing trace anomaly. It is shown that the nonvanishing trace anomaly of the scalar field prevents a complete evaporation.
Data Learning: Understanding Biological Data

The four most important data-related considerations for the bioinformatic analysis of biological systems are understanding of: the complexity and hierarchical nature of processes that generate biological data, fuzziness of biological data, biases and potential misconceptions in data, and the effects of noise and errors. We discuss these issues and summarize our findings by defining a Data Learning Process (DLP). DLP comprises a series of steps for comprehension of biological data within the bioinformatics framework. DLP is a formalization aimed at facilitating knowledge discovery in biological databases.
Collective behavior of minus-ended motors in mitotic microtubule asters gliding toward DNA

Microtubules (MTs) nucleated by centrosomes form star-shaped structures referred to as asters. Aster motility and dynamics is vital for genome stability, cell division, polarization and differentiation. Asters move either toward the cell center or away from it. Here, we focus on the centering mechanism in a membrane independent system of Xenopus cytoplasmic egg extracts. Using live microscopy and single particle tracking, we find that asters move toward chromatinized DNA structures. The velocity and directionality profiles suggest a random-walk with drift directed toward DNA. We have developed a theoretical model that can explain this movement as a result of a gradient of MT length dynamics and MT gliding on immobilized dynein motors. In simulations, the antagonistic action of the motor species on the radial array of MTs leads to a tug-of-war purely due to geometric considerations and aster motility resembles a directed random-walk. Additionally, our model predicts that aster velocities do not change greatly with varying initial distance from DNA. The movement of asymmetric asters becomes increasingly super-diffusive with increasing motor density, but for symmetric asters it becomes less super-diffusive. The transition of symmetric asters from superdiffusive to diffusive mobility is the result of number fluctuations in bound motors in the tug-of-war. Overall, our model is in good agreement with experimental data in Xenopus cytoplasmic extracts and predicts novel features of the collective effects of motor-MT interactions.
Extracting Features for Sentiment Classification: in the Perspective of Statistical Natural Language Processing

In order to improve the accuracy of sentiment classification especially for Chinese online reviews, this paper proposed an approach to extract features for sentiment classification effectively and efficiently. The proposed method is based on supervised machine learning and follows the basic procedure of statistical natural language processing (SNLP). Through feature selection, feature extraction and feature weighting, the significant features for sentiment classification are obtained while the insignificant ones are removed. Comparative experiments have been made on mobile phone online reviews in Chinese, and improvement of three extraction algorithms (DF, IG and CHI) have also been made to obtain more accurate result. This research enriches the studies on sentiment classification theoretically, and is helpful for future work.
Amplitude and latency of beta power during a discrete and continuous motor imageries

Motor imagery modifies the neural activity within the primary sensorimotor areas of the cortex in a similar way as a real movement. More precisely, beta oscillations (18-25 Hz), which are often considered as a sensorimotor rhythm, show that the amplitude of brain oscillations is modulated before, during, and after a motor imagery. A large number of Brain-Computer Interfaces (BCIs) are based on the detection of motor imagery related features in the electroencephalographic signal. In most BCI experimental paradigms, subjects realize continuous motor imagery, i.e. a prolonged intention of movement, during a time window of a few seconds. Then, the system detects the movement based on the event-related desynchronization (ERD) and the event-related synchronization (ERS) principles. This study shows that a discrete motor imagery, corresponding to a single short motor imagery, would allow a better detection of ERD and ERS patterns than a continuous motor imagery. Indeed, the results of experiments involving 11 healthy subjects suggest that a continuous motor imagery generates a later ERS as well as a more variable and less detectable ERD than discrete motor imagery. This finding suggests an improved experimental paradigm.
Designing Persuasive Technology to Manage Peak Electricity Demand in Ontario Homes

When it comes to environmental sustainability, the time that electricity is consumed matters. For example, using an air conditioner on a hot summer afternoon as the power grid is strained necessitates the use of more polluting sources to meet demand. In this paper, we analyze end-user response to two utility-driven conservation programs in Ontario, Canada: Time-of-Use pricing and the peaksaver program. We find that time-of-use pricing encourages shifting some electricity demand, but only when it is convenient. We also find that while potentially effective at a larger scale, the peaksaver program in its current form is unattractive to participants. These results are discussed in the context of Fogg's Behavior Model for Persuasive Design, which allows us to explore the design space for improvement to these programs and ground our design implications for the design of technologies to encourage reduction of peak electricity demand.
Kernel-Based Adaptive Online Reconstruction of Coverage Maps With Side Information

In this paper, we address the problem of reconstructing coverage maps from path-loss measurements in cellular networks. We propose and evaluate two kernel-based adaptive online algorithms as an alternative to typical offline methods. The proposed algorithms are application-tailored extensions of powerful iterative methods such as the adaptive projected subgradient method (APSM) and a state-of-the-art adaptive multikernel method. Assuming that the moving trajectories of users are available, it is shown how side information can be incorporated in the algorithms to improve their convergence performance and the quality of the estimation. The complexity is significantly reduced by imposing sparsity awareness in the sense that the algorithms exploit the compressibility of the measurement data to reduce the amount of data that is saved and processed. Finally, we present extensive simulations based on realistic data to show that our algorithms provide fast and robust estimates of coverage maps in real-world scenarios. Envisioned applications include path-loss prediction along trajectories of mobile users as a building block for anticipatory buffering or traffic offloading.
A Multi-purpose Architecture for Collaborative Web Labs

Laboratory classes are integral part of scientific education, but they are resource-intensive, imposing significant logistic constraints upon the curriculum. An option to reduce these burdens is to implement remote access laboratory classes, where students remotely interact with devices, instead of in traditional laboratory environment. This kind of remote labs are increasingly popular, but their development has been often focused on specific experiences, to address the needs of a particular lab. Moreover they are often designed for one user at a time, i.e. the user experience can not be shared with others. In the article we discuss a new Web Lab platform that can be easily adapted to a large number of different laboratory equipments and that is based on CSCL (computer-supported collaborative learning) techniques in order to share the lab experience within small groups of remote students.
Vertical Resolution Estimates in Version 5 of AIRS Operational Retrievals

In this paper, we present an overview of averaging-kernel computations from the Atmospheric Infrared Sounder (AIRS) Version 5 product retrieval software. Temperature and moisture retrievals form the focus of this paper; however, some results for all other retrieved gas amounts are presented. The theory and methodology required to utilize the averaging kernels for comparison of AIRS retrievals with correlative measurements are given. The averaging kernels are used to transform correlative measurements to AIRS effective resolution and are used to assess and derive the vertical resolution of Version 5 temperature and moisture retrievals in different atmospheric conditions. We find that depending on the scene, AIRS Version 5 tropospheric temperature (moisture) retrieval resolution, which is as determined by the full-width at half-maximum of the averaging kernels, ranges between 2.5 km (2.7 km) near the surface and 7.1 km (4.3 km) near the tropopause.
Real time power estimation and thread scheduling via performance counters

Estimating power consumption is critical for hardware and software developers, and of the latter, particularly for OS programmers writing process schedulers. However, obtaining processor and system power consumption information can be non-trivial. Simulators are time consuming and prone to error. Power meters report whole-system consumption, but cannot give per-processor or per-thread information. More intrusive hardware instrumentation is possible, but such solutions are usually employed while designing the system, and are not meant for customer use. Given these difficulties, plus the current availability of some form of performance counters on virtually all platforms (even though such counters were initially designed for system bring-up, and not intended for general programmer consumption), we analytically derive functions for real-time estimation of processor and system power consumption using performance counter data on real hardware. Our model uses data gathered from microbenchmarks that capture potential application behavior. The model is independent of our test benchmarks, and thus we expect it to be well suited for future applications. We target chip multiprocessors, analyzing effects of shared resources and temperature on power estimation, leveraging our model to implement a simple, power-aware thread scheduler. The NAS and SPEC-OMP benchmarks shows a median error of 5.8% and 3.9%, respectively. SPEC 2006 shows a marginally higher median error of 7.2%.
Efﬁcient Generation of Soft Shadow Textures

This paper extends work described in CMU-CS-97-104. Abstract Soft shadows give important cues of realism to 3D scenes. Existing meth-ods can produce hard shadows in real time and soft shadows in minutes to hours per frame. Here a technique for producing accurate soft shadows quickly in software is presented, allowing soft shadow texture maps to be computed for simple scenes on commodity hardware in real time.
Summarization Techniques of Cloud Computing

Text summarization is a process in which it abbreviating the source script into a short version maintaining its information content with its original meaning. It is an impossible or difficult task for human beings to summarize very large number of documents by hand. The word text summarization methods divided into two parts extractive or abstractive summarization. The extractive summarization technique extracts by selecting significant sentences, paragraphs etc from its original documents and connect them into a short form. The status of sentence is decided by sentences arithmetical and dialectal features. In other hands an abstractive method of summarization entails of understanding the unique text and re-telling it in a few words. It uses linguistic approaches to inspect and decipher the text and find the new observations and expressions to best define it by engendering a new shorter text that delivers the most meaningful facts from the original text document. A deep study of Text Summarization systems has been presented in this paper.
Implementation of method object in active object-based storage systems

The concept of active storage was investigated through adding computational capabilities to I/O contexts, in which increasing data-locality in parallel or placing post-/preprocessing functionality for storage self-maintainability. The advantages of this scheme are tow fold, because it is able to leverage the processing power of the storage nodes and considerably reduce the network traffic at the same time. The emergence of object interface provides a good opportunity for the development of active storage to fight back with highly expressive interface semantics, and the functionality and scalability of active storage in the object storage system, The active storage that we proposed is targeting object-based storage system upon the building block of extended international standard T10 OSD (Object-based Storage Device) command set. Different with the existing work, our work focuses on researching and developing two new kinds of method object to realize active storage, in which user method object is used to manipulate the common user data object, triggered to perform by the user's read and write requests, and the system method object is used in accordance with the policy object and status of the system to implement self-management of the system respectively. Then these active objects are put together to integrated into proposed active storage framework.
Acoustic-waveform Logging -advances Intheory And Application

Full-waveform acoustic logging has made significant advances in both theory and appli c cation in recent years, and these advances have greatly increased the capability of log analysts to measure the physical properties of formations. Advances in theory provide the analytical tools required to understand the properties of measured seismic waves, and to relate those properties to such quantities as shear and compressional velocity and attenuation, and primary and fracture porosity and permeability of potential reservoir rocks. The theory demonstrates that all parts of recorded waveforms are related to various modes of propagation, even in the case of dipole and quadrupole source logging. However, the theory also indicates that these mode properties can be used to design velocity and attenuation picking schemes, and shows how source frequency spectra can be selected to optimize results in specific applications. Synthetic microseismogram computations are an effective tool in waveform interpretation theory; they demonstrate how shear arrival picks and mode attenuation can be used to compute shear velocity and intrinsic attenuation, and formation permeability for monopole, dipole and quadrupole sources. Array processing of multi-receiver data offers the opportunity to apply even more sophisticated analysis techniques. Synthetic microseismogram data is used to illustrate the application of the maximum-likelihood method, semblance cross-correlation, and Prony's method analysis techniques to determine seismic velocities and attenua-8 Paillet et al. tions. The interpretation of acoustic waveform logs is illustrated by reviews of various practical applications, including synthetic seismogram generation, lithology determination , estimation of geomechanical properties in situ, permeability estimation, and design of hydraulic fracture operations.
Reducing Conflict Misses by Application-Specific Reconfigurable Indexing

The predictability of memory access patterns in embedded systems can be successfully exploited to devise effective application-specific cache optimizations. In this paper, an improved indexing scheme for direct-mapped caches, which drastically reduces the number of conflict misses by using application-specific information, is proposed. The indexing scheme is based on the selection of a subset of the address bits. With respect to similar approaches, the solution has two main strengths. First, owing to an analytical model for the conflict-miss conditions of a given trace, it provides a symbolic algorithm to compute the optimum solution (i.e., the subset of address bits to be used as cache index that minimize the number of conflict misses). Second, owing to a reconfigurable bit selector that can be programmed at run time, it allows the optimal cache indexing to fit to a given application. Results show an average reduction of conflict misses of 24%, measured over a set of standard benchmarks, and for different cache configurations
Facial emotion detection considering partial occlusion of face using Bayesian network

Recently, robots that communicate with human have attracted much attention in the research field of robotics. In communication between human, almost all human recognize the subtleties of emotion in each other's facial expressions, voices, and motions. Robots can communicate more smoothly with human as they detect human emotions and respond with appropriate behaviors. Usually, almost all human express their own emotions with their facial expressions. In this paper, we propose an emotion detection system with facial features using a Bayesian network. In actual communication, it is possible that some parts of the face will be occluded by adornments such as glasses or a hat. In previous studies on facial recognition, these studies have been had the process to fill in the gaps of occluded features after capturing facial features from each image. However, not all occluded features can always be filled in the gaps accurately. Therefore, it is difficult for robots to detect emotions accurately in real-time communication. For this reason, we propose an emotion detection system taking into consideration partial occlusion of the face using causal relations between facial features. Bayesian network classifiers infer from the dependencies among the target attribute and explanatory variables. This characteristic of Bayesian network makes our proposed system can detect emotions without filling in the gaps of occluded features. In the experiments, the proposed system succeeded in detecting emotions with high recognition rates even though some facial features were occluded.
Star clusters as building blocks for dSph galaxy formation

Abstract We study numerically the formation of dSph galaxies. Intense starbursts, e.g., in gas-rich environments, typically produce a few to a few hundred young star clusters within a region of just a few hundred pc. The dynamical evolution of these star clusters may explain the formation of the luminous component of dwarf spheroidal (dSph) galaxies. Here, we perform a numerical experiment to show that the evolution of star cluster complexes in dark-matter haloes can explain the formation of the luminous components of dSph galaxies.
Evolving definitions of authorship in Ebook design

The development of ebooks for tablet devices offers a rich space for collaboration between writers and designers. This paper examines how this emerging media affects ideas around collaboration and authorship. Specifically it considers the changing role of designers in shaping meaning and content and how this may affect existing paradigms of authorship. Using class-based projects as case studies, the paper presents and discusses examples of how designers have shifted their role from historic notions of “crystal goblet” design or expressive design to genuine collaborators and authors.
A collaborative simulation monitor system of ship based on patterns

Computer simulation has been widely used in scientific research. But the present simulation systems are mostly designed for a specific purpose, which can only be applied in specific research experiment, so the expansibility is not good. The main purpose of pattern technology is to extend the technologies of software reuse based on Object Oriented [1]. Pattern technology can reuse not only the codes of function modules, but also the structural design of system software. In the design and implementation of the collaborative ship simulation monitor system mentioned in this paper, kinds of pattern technologies have been used. The system has not just the characteristics of high efficiency, easy to extend and maintain, but also the characteristic of high reusability.
Visual Motion Analysis by a Neural Network

In the visual systems of mammals, visual scenes are analyzed in parallel by sepa- rate channels. Information concerning visual motion is mainly analyzed through the occipito- parietal pathway. In area MST of the pathway, there are cells that respond selectively to spe- cific motions of a large area of the visual field, such as rotation, expansion and contraction. Many of these cells are reported to respond steadily even when the location of the center of optic flow shifts on the retina. This paper proposes a neural network model that explains the position-invariant responses of the MST cells. The network has a hierarchical multilayered architecture and extracts optic flow based on vector field hypothesis.
Posterior expression of a homeobox gene in early Xenopus embryos.

The homeobox containing transcript Xhox-36 is expressed exclusively in the posterior mesoderm and ectoderm of early Xenopus embryos. Therefore, the transcript shows region-specific rather than tissue-specific expression in the gastrula and neurula, a time when cells are becoming committed to defined fates. Exposure of early embryos to LiCl, which shifts posterior cells to more anterior fates, reduces the abundance of this posterior-specific transcript. In contrast, embryos ventralized by u.v. treatment express normal levels of the transcript, implying that expression of the gene is not absolutely linked to dorsal cell identity. The sequence of a full-length cDNA corresponding to this transcript predicts a homeodomain-containing protein of 209 amino acids.