Miracle-dz/UniFAR-FTUs huggingface dataset:
Implied Volatility Smiles: Empirical Tests

Implied volatility "smiles" have been documented in a number of option markets worldwide. The volatilities implied by the Black-Scholes (1973) model tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) offer an explanation for this behavior, that is, the volatility of the return of the underlying asset is a deterministic function of the asset price level and time. Their option valuation methodology, dubbed the "implied binomial tree" approach, describes (perfectly) the observed structure of options prices and purportedly provides more accurate hedge ratios. We systematically evaluate the empirical properties of the implied binomial tree approach to option valuation using S&P 500 index options during the period June 1988 and December 1993.
A comparison of Species Distribution Modeling approaches for an under-sampled parasite of public health importance, Echinococcus multilocularis

Background Species distribution models (SDMs) have an important role in predicting the range of emerging and understudied pathogens and parasites. Their use, however, is often limited by the lack of high-resolution unbiased occurrence records. Echinococcus multilocularis is a parasitic cestode of public health importance which is widely distributed throughout Eu rasia and is considered an emerging threat in North America. In common with many parasite species, available data for E. multilocularis occurrence are spatially biased and often poorly geo-referenced. Results Here we produce three separate SDMs using MaxEnt for E. multilocularis using varying complexities of sampling schemes and environmental predictors, designed to make the best possible use of non-ideal occurrence data. The most realistic model utilized both derived and basic climatic predictors; an occurrence sampling scheme which relied primarily on high resolution occurrences from the literature and a bias grid to compensate for an apparently uneven research effort. All models predicted extensive regions of high suitability for E. multilocularis in North America, where the parasite is poorly studied and not currently under coordinated surveillance. Conclusions Through a pragmatic approach to non-ideal occurrence data we were able to produce a statistically well supported SDM for an under-studied species of public health importance. Although the final model was only trained on data from Eurasia, the global model projection encompassed all known occurrences in the United States. The approach defined here may be applicable to many other such species and could provide useful information to direct resources for future field based surveillance programs for E. multilocularis in North America.
Using Granularity Concepts for Discovering Causal Relations

Historically, causal markers, syntactic structures and connectives have been the sole identifying features for automatically extracting causal relations in natural language discourse. However various connectives such as “and”, prepositions such as “as” and other syntactic structures are highly ambiguous in nature, and it is clear that one cannot solely rely on lexico-syntactic markers for detection of causal phenomenon in discourse. This paper introduces the theory of granularity and describes different approaches to identify granularity in natural language. As causality is often granular in nature (Mazlack 2004), we use granularity relations to discover and infer the presence of causal relations in text. We compare this with causal relations identified using just causal markers. We achieve a precision of 0.91 and a recall of 0.79 using granularity for causal relation detection, as compared to a precision of 0.79 and a recall of 0.44 using pure causal markers for causality detection.
Porphyromonas gingivalis Lipopolysaccharide Induced Proliferation and Activation of Natural Killer Cells in Vivo

Porphyromonas gingivalis (P. gingivalis) lipopolysaccharide (LPS) promoted different innate immune activation than that promoted by Escherichia coli (E. coli) LPS. In this study, we examined the effect of P. gingivalis LPS on the proliferation and activation of natural killer (NK) cells in vivo and compared that function with that of E. coli LPS. Administration of P. gingivalis LPS to C57BL/6 mice induced stronger proliferation of NK cells in the spleen and submandibular lymph nodes (sLNs) and increased the number of circulating NK cells in blood compared to those treated with E. coli LPS. However, P. gingivalis LPS did not induce interferon-gamma (IFN-γ) production and CD69 expression in the spleen and sLN NK cells in vivo, and this was attributed to the minimal activation of the spleen and sLN dendritic cells (DCs), including low levels of co-stimulatory molecule expression and pro-inflammatory cytokine production. Furthermore, P. gingivalis LPS-treated NK cells showed less cytotoxic activity against Yac-1 target cells than E. coli LPS-treated NK cells. Hence, these data demonstrated that P. gingivalis LPS promoted limited activation of spleen and sLN NK cells in vivo, and this may play a role in the chronic inflammatory state observed in periodontal disease.
Does Heterogeneity Hinder Democracy

Research linking heterogeneity and democracy usually focuses on one single dimension of heterogeneity, such as the distribution of power resources, income inequality, gender inequality, or ethnic fractionalization. Empirical results have so far been inconsistent. This article attempts a sound conceptualization of the phenomenon of heterogeneity. In order to assess whether and how heterogeneity hampers democracy, we will first define what “heterogeneity” means and examine its various dimensions. Then we will discuss why and in which respect heterogeneity constitutes a challenge to democratic transition and consolidation and will review previous research. Our empirical analysis gauges the effect of various dimensions of heterogeneity on the political trajectory of states since the beginning of the third wave of democratization. We find that, while most facets of heterogeneity do not hinder democratic transition, most of them complicate democratic consolidation. Our final discussion offers some suggestions on how the obstacles that heterogeneity poses for democratic development could be overcome and which principles, procedures and institutions are most appropriate to deal with each of the different dimensions of heterogeneity.
Personalized Dynamic Pricing of Limited Inventories Goker Aydin *

Prior work has investigated time and inventory-level dependent pricing of limited inventories with finite selling horizons. We consider a third dimension in addition to time and inventory level that the firms can use in setting their prices: the information that the firm has at the individual customer level. An arriving customer provides a signal to the firm, which is an imperfect indicator of the customer’s willingness-to-pay, and the firm makes a personalized price offer depending on the signal, inventory level, and time. We consider two different models: full personalization and partial personalization. In full personalization model, the firm charges any price it wishes given the customer signal, while in the partial personalization model, the firm can charge one of two prices. We find that a mere correlation between the signals and customers’ willingness-to-pay is not sufficient to ensure intuitive relationships between the signal and the optimal prices. We determine a stronger condition, which leads to several structural properties including the monotonicity of the optimal price with respect to the signal in the full personalization model. For the partial personalization model, we show that the optimal pricing policy is of threshold-type and that the threshold is monotonic in the inventory level and time. Through a numerical study, we investigate the interactions between personalized pricing and dynamic pricing. In an extension model where signals from some of the customers are not available, we find that it might in fact be better for the firm if customers with high willingness-to-pay do not provide their signals, since it helps the firm better price-discriminate.
Extracting knowledge using probabilistic classifier for text mining

Text mining is a process of extracting knowledge from large text documents. A new probabilistic classifier for text mining is proposed in this paper. It uses ODP taxonomy and domain ontology and datasets to cluster and identify the category of the given text document. The proposed work has three steps, namely, preprocessing, rule generation and probability calculation. At the stage of preprocessing the input document is split into paragraphs and statements. In rule generation, the documents from the training set are read. In probability calculation, positive and negative weight factor is calculated. The proposed algorithm calculates the positive probability value and negative probability value for each term set or pattern identified from the document. Based on the calculated probability value the probabilistic classifier indexes the document to the concern group of the cluster.
On an irreducibility theorem of A. Schinzel associated with coverings of the integers

Let f(x) and g(x) be two relatively prime polynomials having integer coefficients with g(0) # 0. The authors show that there is an N N(f, g) such that if n > N, then the non-reciprocal part of the polynomial f(x)x + g(x) is either irreducible or identically or -1 with certain clear exceptions that arise from a theorem of Capelli. A version of this result is originally due to Andrzej Schinzel. The present paper gives a new approach that allows for an improved estimate on the value of N.
ESD induced latent defects in CMOS ICs and reliability impact

A dedicated test vehicle was designed to study the impact of ESD induced latent defects on digital and analog CMOS circuits. Both CDM and TLP stresses were applied to these circuits through a specific pad which allows stressing the circuit core. Both electrical characterization and non-destructive failure analysis were performed to locate the induced defect. For digital circuits, functionality is not affected although the IDDQ quiescent current increased. However, after burn-in and storage, it was observed that the IDDQ current significantly increased suggesting that the circuit lifetime is degraded. In contrast, even at very low stress level, the analog circuit exhibits a dramatic offset degradation and no recovery is observed after burn-in.
Object-Oriented Analysis and ~ e s i b in Software project Teams

Software development poses enormous cognitive, organizational, and managerial challenges. In this article, we focus on two of the most formidable of these challenges and on the promise of object-oriented (00) technology for addressing them. In particular, we analyze the claims made about 00 design (OOD) and (a) dissemination of domain knowledge and (b) communication and coordination. In order to address the validity of these claims, we conducted an in-depth observational study of OOD in an industrial setting as well as a series of interviews with experienced OOD practitioners. Compared to similar projects using traditional methods, our study found evidence in the OOD project for a reduced need for clarification in design discussions; differences in participation, in how meeting time is spent, and in the sequential order of design discussions; and a much greater OOD AND SOFTWARE . DESIGN TEAMS 251 tendency to ask why questions. We discuss the implications of these findings for tools, grain size of design units, interactions with clients, and organizing for OOD.
On the Automorphism Group of Integral Circulant Graphs

The integral circulant graph $X_n (D)$ has the vertex set $Z_n = \{0, 1,\ldots$, $n{-}1\}$ and vertices $a$ and $b$ are adjacent, if and only if $\gcd(a{-}b$, $n)\in D$, where $D = \{d_1,d_2, \ldots, d_k\}$ is a set of divisors of $n$. These graphs play an important role in modeling quantum spin networks supporting the perfect state transfer and also have applications in chemical graph theory. In this paper, we deal with the automorphism group of integral circulant graphs and investigate a problem proposed in [W. Klotz, T. Sander, Some properties of unitary Cayley graphs , Electr. J. Comb. 14 (2007), #R45]. We determine the size and the structure of the automorphism group of the unitary Cayley graph $X_n (1)$ and the disconnected graph $X_n (d)$. In addition, based on the generalized formula for the number of common neighbors and the wreath product, we completely characterize the automorphism groups $Aut (X_n (1, p))$ for $n$ being a square-free number and $p$ a prime dividing $n$, and $Aut (X_n (1, p^k))$ for $n$ being a prime power.
Valuation of Derivative on Asset with Network Price Externality Effects

The present paper focuses on pricing the plain vanila option when the price process of underlying asset is described by the stochastic Verhulst-Gompertz Equation with network external- ity effects in a complete market. The method is based on the change of measure, Girsanov theorem and martingale valuation techinique. The application to an exchange option is made attempt and the valuation formula for this option like the Black-Scholes one is derived. A simple relation similar to the put-call-parity between the exchange call option and the put option is provided. Our results will be useful to analyze the price evolution at a sudden rise or crash of the stock market.
Completely decoupled space-time block codes with low-rate feedback

In this paper, we propose a class of full diversity rate one space-time block codes (STBC) satisfying the generalized orthogonal constraint (GOC). First an explicit construction of completely decoupled STBC is proposed to obtain a rate one STBC with linear decoding complexity for any number of transmit antennas. Then we propose an adaptation strategy for the codes to achieve full diversity by utilizing partial phase information of the channel obtained via a feedback link. With a few feedback bits, the proposed rate one code has full diversity while reserving the same decoding complexity as Orthogonal STBCs. Moreover, the full diversity can be still achieved even if the simple zero-forced decoding is used at the receiver.
Deadlock and lock freedom in the linear π-calculus

We study two refinements of the linear π-calculus that ensure deadlock freedom (the absence of stable states with pending linear communications) and lock freedom (the eventual completion of pending linear communications). The main feature of both type systems is a new form of channel polymorphism that affects their accuracy in a significant way: they are the first of their kind that can deal with recursive processes connected by cyclic networks.
Beyond Hartree-Fock: MP2 and Coupled-Cluster Methods for Large Systems

This chapter reviews brieﬂy the theory of second order Møller-Plesset perturbation theory (MP2), the approximate coupled-cluster singles-and-doubles method CC2 and closely related ab initio methods for calculations on excited states which treat the electron-electron interaction correctly through second order. It is shown how the computational costs (CPU time and storage requirements) can be reduced for these methods by orders of magnitudes using the resolution- of-the-identity approximation for electron repulsion integrals. The demands for the auxiliary basis sets are discussed and it is shown how with optimized basis sets the errors due to this approximation become insigniﬁcant compared to the usual orbital basis set error. Furthermore, a parallel implementation of RI-MP2 and RI-CC2 in the TURBOMOLE program package for distributed memory architectures (as e.g. clusters of Linux boxes) is presented and some proto-typical applications are reviewed.
Towards a new framework for clustering in a mixed data space: Case of gasoline service stations segmentation in Morocco

Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datasets that contain either numeric or categorical attributes. However, data sets with mixed types of attributes are common in real life data mining applications. In this paper, we introduce a new framework for clustering mixed data which is based on Random Forest dissimilarity and PAM clustering. Then we apply this framework to segment market of services stations in Morocco to identify features that most influence on profit of each service station.
Periodic Optimal Search Control for a Target Appearing Randomly

This paper investigates an optimal search problem under the assumption that a target to be found appears randomly and stays for a fixed time interval. We first formulate the search problem as an optimization problem to maximize the probability of finding the target while reducing the control energy consumption, and provide a solution to this problem. In this paper, we moreover derive the expectation value of how many times the target appears without being found and a necessary and sufficient condition for the agent’s behavior to converge to a periodic trajectory. The effectiveness of the proposed method is demonstrated through a numerical simulation.
Health Information Exchange, System Size and Information Silos

There are many technology platforms that bring benefits only when users share data. In healthcare, this is a key policy issue, because of the potential cost savings and quality improvements from 'big data' in the form of sharing electronic patient data across medical providers. Indeed, one criterion used for federal subsidies for healthcare information technology is whether the software has the capability to share data. We find empirically that larger hospital systems are more likely to exchange electronic patient information internally, but are less likely to exchange patient information externally with other hospitals. This pattern is driven by instances where there may be a commercial cost to sharing data with other hospitals. Our results suggest that the common strategy of using 'marquee' large users to kick-start a platform technology has an important drawback of potentially creating information silos. This suggests that federal subsidies for health data technologies based on 'meaningful use' criteria, that are based simply on the capability to share data rather than actual sharing of data, may be misplaced.
Computer-Aided Engineering for Inference of Genetic Regulatory Networks Using Data from DNA Microarrays

Biological research topics gradually shift from structural genomics into functional genomics. DNA microarrays have been used to generate abundant data for exploring functions and interactions among genes. We propose a reverse-engineering strategy to predict the interactions between genes within a genetic network. Our inputs are perturbation matrices experimentally obtained from DNA microarrays. First, we make some assumptions for the interactions in the network. The proposed network is represented as a directed graph. After that, we enumerate all possible network models according to the assumptions. And then, some candidate models are obtained, resulted from calculated perturbation matrices out of computational simulation. The network involves in not only the transcription level but also the nucleotide/protein interactions in general. To justify this method, we take a well-known genetic regulatory network in yeast Saccharomyces cerevisia for a test. The result shows that one of the candidate models can generate an identical perturbation matrix as that from the yeast's DNA microarrays, experimentally determined by others. In conclusion, our method is useful and feasible for determining probable interactions within biological networks.
IMMUNE MECHANISMS IN PARABIOSIS INTOXICATION

When A strain mice are placed in parabiotic union with (A x C57Bl/1)F1 hybrid partners, the parental strain partners are polycythemic and the hybrids anemic from the 5th through the 16th parabiosis days. All hybrids develop clinical intoxication between the 7th and the 12th days, and no pairs survive to 1 month. Long-term survival of parabiotic pairs can be achieved if lethally irradiated or specifically tolerant parental strain mice are united to hybrid partners. Production of tolerance by either of these methods results in elimination of anemia-polycythemia by the 12th parabiosis day and prevents intoxication in the hybrid partners. Preimmunization of the parental strain partners against the C57Bl/1 component of the hybrid leads to a considerable intensification of day 5 anemia-polycythemia. Intoxication develops in the hybrid partners between the 4th and the 6th days after union. It is concluded that anemia is primarily responsible for the syndrome of clinical intoxication. Early anemia-polycythemia on day 5 does not depend upon an immunological mechanism, but the late anemia-polycythemia appearing between days 12 and 16 is a function of the ability of the parental strain mouse to react immunologically against its hybrid partner. When neonatally thymectomized A strain mice are joined to hybrid partners, anemia-polycythemia is sustained through the 16th day and the hybrid partners develop clinical intoxication. On the other hand, when both partners are neonatally thymectomized, late anemia-polycythemia is considerably reduced, and the hybrid partners apparently do not develop clinical intoxication. It is concluded that normal hybrid mice are capable of reconstituting the immunological capacity of their thymectomized partners, whereas thymectomized hybrid mice do not have this restorative capacity. These findings are discussed in terms of their possible application to the problem of the induction of immunological tolerance in adult mice by the parabiosis procedure.
Qualitative geocoding of persistent web pages

Information and specifically Web pages may be organized, indexed, searched, and navigated using various metadata aspects, such as keywords, categories (themes), and also space. While categories and keywords are up for interpretation, space represents an unambiguous aspect to structure information. The basic problem of providing spatial references to content is solved by geocoding; a task that relates identifiers in texts to geographic co-ordinates. This work presents a methodology for the semiautomatic geocoding of persistent Web pages in the form of collaborative human intervention to improve on automatic geocoding results. While focusing on the Greek language and related Web pages, the developed techniques are universally applicable. The specific contributions of this work are (i) automatic geocoding algorithms for phone numbers, addresses and place name identifiers and (ii) a Web browser extension providing a map-based interface for manual geocoding and updating the automatically generated results. With the geocoding of a Web page being stored as respective annotations in a central repository, this overall mechanism is especially suited for persistent Web pages such as Wikipedia. To illustrate the applicability and usefulness of the overall approach, specific geocoding examples of Greek Web pages are presented.