Miracle-dz/UniFAR-FTUs huggingface dataset:
Pricing and Hedging Spread Options

We survey theoretical and computational problems associated with the pricing and hedging of spread options. These options are ubiquitous in the financial markets, whether they be equity, fixed income, foreign exchange, commodities, or energy markets. As a matter of introduction, we present a general overview of the common features of all spread options by discussing in detail their roles as speculation devices and risk management tools. We describe the mathematical framework used to model them, and we review the numerical algorithms actually used to price and hedge them. There is already extensive literature on the pricing of spread options in the equity and fixed income markets, and our contribution is mostly to put together material scattered across a wide spectrum of recent textbooks and journal articles. On the other hand, information about the various numerical procedures that can be used to price and hedge spread options on physical commodities is more difficult to find. For this reason, we make a systematic effort to choose examples from the energy markets in order to illustrate the numerical challenges associated with these instruments. This gives us a chance to discuss an interesting application of spread options to an asset valuation problem after it is recast in the framework of real options. This approach is currently the object of intense mathematical research. In this spirit, we review the two major avenues to modeling energy price dynamics. We explain how the pricing and hedging algorithms can be implemented in the framework of models for both the spot price dynamics and the forward curve dynamics.
BlockyTalky: A Physical and Distributed Computer Music Toolkit for Kids

NIME research realizes a vision of performance by means of computational expression, linking body and space to sound and imagery through eclectic forms of sensing and interaction. This vision could dramatically impact computer science education, simultaneously modernizing the field and drawing in diverse new participants. We describe our work creating a NIME-inspired computer music toolkit for kids called BlockyTalky; the toolkit enables users to create networks of sensing devices and synthesizers. We offer findings from our research on student learning through programming and performance. We conclude by suggesting a number of future directions for NIME researchers interested in education.
Dyons Near the Planck Scale

In this paper we suggest a new model of preons–dyons making composite quark–leptons and bosons, described by the supersymmetric string-inspired flipped gauge group of symmetry. This approach predicts the possible extension of the Standard Model to the family replicated gauge group model of type GNfam, where Nfam is the number of families and G is the symmetry group: G = SMG, SU(5), SO(10), E6, etc. Here E6 and are nondual and dual sectors of theory with hyperelectric g and hypermagnetic charges, respectively. Starting with an idea that the most realistic model leading to the unification of all fundamental interactions (including gravity) is the "heterotic" string-derived flipped model, we have assumed that at high energies μ > 1016GeV there exists the following chain of the flipped models: ended by the flipped E6 gauge group of symmetry at the scale MSSG ~ 1018GeV. Suggesting N = 1 supersymmetric preonic model we have considered preons as dyons confined by hypermagnetic strings in the region of energies μ≲MPl. Our model is based on the recent theory of composite non-Abelian flux tubes in SQCD — analog ANO-strings. Considering the breakdown of E6 and at the Planck scale into the SU(6) × U(1) gauge group, we have shown that the six types of k-strings — composite N = 1 supersymmetric non-Abelian flux tubes — are created by the condensation of spreons–dyons near the Planck scale and have six fluxes quantized according to the Z6 center group of SU(6): Φn = nΦ0(n = ±1, ±2, ±3). These fluxes give three types of k-strings with tensions Tk = kT0, where k = 1, 2, 3, and produce three (and only three) generations of composite quark–leptons and bosons giving a very specific type of "horizontal symmetry. " Thus, the present model predicts Ngen = Nfam = 3. It was shown that our preonic strings are very thin, with radius Rstr ~ 10-18GeV-1, and their tension T0 is enormously large: T0 ~ 1038GeV2. It was shown that the condensation of spreons near the Planck scale gives the phase transition at some scales Mcrit and , which correspond to the following breakdowns of E6 (or ) for preons: E6 →SU(6)×U(1), or . We have calculated the critical values of gauge coupling constants: α-1(Mcrit) ≈4.23 and . It was investigated that in our world we have quark–leptons and gauge bosons Aμ in the region of energies μ≲MPl, but monopolic "quark–leptons" and dual gauge fields exist in the region μ≳MPl.
THE SMUT-SUGARCANE INTERACTION AS A MODEL SYSTEM FOR THE INTEGRATION OF MARKER DISCOVERY AND GENE ISOLATION

Genes that are differentially expressed by resistant sugarcane varieties in response to challenge by pathogens or pests have the potential to be useful in Marker Assisted Selection (MAS) once a link with resistance has been confirmed. Methodologies and resources designed to maximise the discovery of genetic markers and to facilitate the isolation of full-length coding sequences of resistance genes are described. To test the potential of the authors’ approach, the smut-sugarcane interaction was chosen for a preliminary study. Sequence analysis of genes differentially expressed in response to challenge by smut has identified putative receptors involved in the signalling of resistance mechanisms, transcription factors, and enzymes involved in phenylpropanoid-flavonoid metabolism. Fragments having homology with flavonoid pathway transcription factors X1 and P1 were utilised as RFLP probes in a marker discovery effort. A resultant multiple linear regression model included two polymorphisms and explained 26% of the variation in smut resistance ratings within a set of 78 phenotypically well-characterised sugarcane clones. The full-length coding sequence for transcription factor X1 is in the process of being isolated from a PCR amplified cDNA pool using a ‘capture-enrichment’ methodology. Two full-length thaumatin (PR5) antifungal proteincoding sequences have already been isolated and are available for use as transgenes.
Optimizing existential datalog queries

The problem of pushing projections in recursive rules has received little attention. The objective of this paper is to motivate this problem and present some (partial) solutions. We consider programs with function-free rules, also known as Datalog programs. After formally defining existential subqueries, we present a syntactic criterion for detecting them and then consider optimization in three areas 1) We identify the existential subqueries and make them explicit by rewriting the rules. This, in effect, automatically captures some aspects of Prolog's cut operator that are appropriate to the bottom-up model of computation 2) We eliminate argument positions in recursive rules by “pushing projections” 3) We observe that “pushing projections” in rules also has the effect of making some rules (even recursive rules) redundant and try to (identify and) discard them
Mechanics of Camera Work in Mobile Video Collaboration

Mobile video conferencing, where one or more participants are moving about in the real world, enables entirely new interaction scenarios (e.g., asking for help to construct or repair an object, or showing a physical location). While we have a good understanding of the challenges of video conferencing in office or home environments, we do not fully understand the mechanics of camera work-how people use mobile devices to communicate with one another-during mobile video calls. To provide an understanding of what people do in mobile video collaboration, we conducted an observational study where pairs of participants completed tasks using a mobile video conferencing system. Our analysis suggests that people use the camera view deliberately to support their interactions-for example, to convey a message or to ask questions-but the limited field of view, and the lack of camera control can make it a frustrating experience.
Numerical Semigroups on Compound Sequences

We generalize the geometric sequence {ap, ap−1b, ap−2b2,…, bp} to allow the p copies of a (resp. b) to all be different. We call the sequence {a1a2a3… ap, b1a2a3…ap, b1b2a3…ap,…, b1b2b3…bp} a compound sequence. We consider numerical semigroups whose minimal set of generators form a compound sequence, and compute various semigroup and arithmetical invariants, including the Frobenius number, Apéry sets, Betti elements, and catenary degree. We compute bounds on the delta set and the tame degree.
Glyphosate resistance: state of knowledge

Studies of mechanisms of resistance to glyphosate have increased current understanding of herbicide resistance mechanisms. Thus far, single-codon non-synonymous mutations of EPSPS (5-enolypyruvylshikimate-3-phosphate synthase) have been rare and, relative to other herbicide mode of action target-site mutations, unconventionally weak in magnitude for resistance to glyphosate. However, it is possible that weeds will emerge with non-synonymous mutations of two codons of EPSPS to produce an enzyme endowing greater resistance to glyphosate. Today, target-gene duplication is a common glyphosate resistance mechanism and could become a fundamental process for developing any resistance trait. Based on competition and substrate selectivity studies in several species, rapid vacuole sequestration of glyphosate occurs via a transporter mechanism. Conversely, as the chloroplast requires transporters for uptake of important metabolites, transporters associated with the two plastid membranes may separately, or together, successfully block glyphosate delivery. A model based on finite glyphosate dose and limiting time required for chloroplast loading sets the stage for understanding how uniquely different mechanisms can contribute to overall glyphosate resistance.
Clustered Matrix Approximation

In this paper we develop a novel clustered matrix approximation framework, first showing the motivation behind our research. The proposed methods are particularly well suited for problems with large scale sparse matrices that represent graphs and/or bipartite graphs from information science applications. Our framework and resulting approximations have a number of benefits: (1) the approximations preserve important structure that is present in the original matrix; (2) the approximations contain both global-scale and local-scale information; (3) the procedure is efficient both in computational speed and memory usage; and (4) the resulting approximations are considerably more accurate with less memory usage than truncated SVD approximations, which are optimal with respect to rank. The framework is also quite flexible as it may be modified in various ways to fit the needs of a particular application. In the paper we also derive a probabilistic approach that uses randomness to compute a clustered matrix approx.
Range extraction from underwater Imaging Sonar data

Nearly all advanced mobile robotic tasks require some knowledge of the robot location in the environment. Autonomous Underwater Vehicles are usually endowed with acoustic devices to perform localization, because underwater scenarios pose important limitations to light based sensors. One of these acoustic devices is the Mechanically Scanned Imaging Sonar (MSIS). This sensor scans the environment by emitting ultrasonic pulses and it provides echo intensity profiles (beams) of the scanned area.
Improved constraints on possible variation of physical constants from H i 21‐cm and molecular QSO absorption lines

Quasar (QSO) absorption spectra provide an extremely useful probe of possible cosmological variation in various physical constants. Comparison of H i 21-cm absorption with corresponding molecular (rotational) absorption spectra allows us to constrain variation in , where α is the fine-structure constant and gp is the proton g-factor. We analyse spectra of two QSOs, PKS 1413+135 and TXS 0218+357, and derive values of at absorption redshifts of and 0.6847 by simultaneous fitting of the H i 21-cm and molecular lines. We find and respectively, indicating an insignificantly smaller y in the past. We compare our results with other constraints from the same two QSOs given recently by Drinkwater et al. and Carilli et al., and with our recent optical constraints, which indicated a smaller α at higher redshifts.
Human identification using Linear Multiclass SVM and Eye Movement biometrics

The paper presents a system to accurately differentiate between unique individuals by utilizing the various eye-movement biometric features. Eye Movements are highly resistant to forgery as the generation of eye movements occur due to the involvement of complex neurological interactions and extra ocular muscle properties. We have employed Linear Multiclass SVM model to classify the numerous eye movement features. These features were obtained by making a person fixate on a visual stimuli. The testing was performed using this model and a classification accuracy up to 91% to 100% is obtained on the dataset used. The results are a clear indication that eye-based biometric identification has the potential to become a leading behavioral technique in the future. Moreover, its fusion with different biometric processes such as EEG, Face Recognition etc., can also increase its classification accuracy.
Multi-level image segmentation and object representation for content based image retrieval

Due to the increasing demand and offer of the technology, the next generation of the image file formats will be more likely to store and retrieve images based on their semantic content. Thus, an image should be segmented into "meaningful" regions, each of which corresponds to an object and/or background. In this study, we propose a scheme for multi-level image segmentation, based on a simple descriptor, called "the closest color in the same neighborhood". The proposed scheme generates a stack of images without using any segmentation threshold. The stack of images is hierarchically ordered in a uniformity tree. The uniformity tree is, then, associated with a semantic tree, which is built by the user for content based representation. The experiments indicate superior results for retrieving images, which consist of few objects and a background.
Post-fabrication reconfiguration for power-optimized tuning of optically connected multi-core systems

Integrating optical interconnects into the next-generation multi-/many-core architecture has been considered a viable solution to addressing the limitations in throughput, latency, and power efficiency of electrical interconnects. Optical interconnects also allow the performance growth of inter-core connectivity to keep pace with the growth of the cores' processing ability. However, variations in the fabrication process significantly impair an optical network's communication quality. Existing post-fabrication tuning methods, which are based on adjusting the voltages and temperatures, have very limited tunability and require excessive power to fully compensate for the variation. In this paper, we study the sources and severity of process variation, and propose two methods to enhance the robustness of an on-chip optical network: 1) adding spare modulators and detectors for post-fabrication reconfiguration and low-power tuning, and 2) introducing a combined detector/modulator structure for a more robust network topology. Simulation results show that employing both methods can reduce the tuning power from hundreds of watts to 6W while maintaining a throughput of 99.7%. To maintain a throughput of 50%, the tuning power can be further reduced to only 12mW.
Translating Neurobiological Findings Into Improved Combined Pharmacological and Psychotherapeutic Interventions for Posttraumatic Stress Disorder

Reaching as far back as the 17th century and Ren e Descartes’ philosophy of dualism, the mind and body have historically been viewed as distinct entities, and consistent with this view, biology and psychotherapy have often been approached separately in the empirical literature. We propose that the exciting neurobiological findings about posttraumatic stress disorder (PTSD) reviewed by Kelmendi, Adams, Southwick, Abdallah, and Krystal (2017) illustrate the complementary nature of these disciplines. Consistent with this review’s framework of using research on the neurobiology of PTSD as a foundation for hypotheses related to mechanisms of pharmacotherapy for this disorder, we would like to emphasize that this biological research can also be used as a foundation for hypotheses related to psychotherapy for PTSD, as well as combined psychotherapy and pharmacotherapy approaches. As noted recently (Arbuckle, Travis, & Ross, 2017), the distinctions between “biological” and “psychological” are diminishing, particularly given empirical findings that effective interventions, including psychotherapeutic or pharmacologic approaches, alter brain networks and thus can be conceptualized as biological in nature. As such, within our commentary we elaborate on translational fear conditioning models as an important framework for investigating and understanding specific biological and psychological mechanisms across pharmacological, psychotherapeutic, and combined PTSD treatment approaches. We also will review why we are in strong agreement with Kelmendi et al. (2017) that extinction-based and cognitive-behavioral therapy (CBT) combined with pharmacological agents should be given top priority in future research. In this discussion, we will highlight some specific issues in combined approaches that warrant attention given their relevance and ability to inform future research and clinical practice. Kelmendi et al. (2017) provide a thoughtful review of neurobiological findings with regard to PTSD, and how this literature informs our understanding of mechanisms underlying existing and novel pharmacological interventions for this disorder. Recent empirical literature has provided many notable findings regarding the pathophysiology of PTSD and has provided a richer illustration of the complexity surrounding this disorder. PTSD is a disorder that is heterogeneous, involves multiple neurobiological systems, and is frequently comorbid with other mental and physical illnesses. As noted in this review, there is a paucity of literature on combined pharmacological and psychotherapy approaches for PTSD. We believe that this is a crucial area to highlight, particularly as pharmacological interventions are frequently combined with psychotherapy in clinical practice. Thus, it is imperative that neurobiological findings are used to inform research investigating the effectiveness and optimal timing of combined approaches.
Evolution of Emergent Cooperative Behavior using Genetic Programming

The recently developed genetic programming paradigm provides a way to genetically breed a computer program to solve a wide variety of problems. Genetic programming employs Darwinian survival and reproduction of the fittest and the genetic crossover (sexual recominbation) operation to evolve progressively better solutions to problems. In this chapter, a computer program that governs the behavior of a group of independently acting agents is genetically evolved to solve the "painted desert" problem. The evolved program exhibits emergent and cooperative behavior.
Versal deformation of the Lie algebra $L_2$

We investigate deformations of the infinite dimensional vector field Lie algebra spanned by the fields $e_i = z^{i+1}d/dz$, where $i \ge 2 $. The goal is to describe the base of a ``versal'' deformation; such a versal deformation induces all the other nonequivalent deformations and solves the deformation problem completely.
The Secure Boot of Embedded System Based on Mobile Trusted Module

In this paper the transitive trust of TPM and the secure boot of MTM are analyzed. A scheme of secure boot for embedded system is proposed. Based on U-Boot and embedded Linux, the secure boot functions for embedded system are implemented by the integrity measurement, integrity storage and integrity reporting. This scheme can improve the security of embedded system by introducing MTM. Finally the implementation of secure boot is tested, which verify the effectiveness of the secure boot scheme.
Nongeometry, duality twists, and the worldsheet

In this paper, we use orbifold methods to construct nongeometric backgrounds, and argue that they correspond to the spacetimes discussed in [1], [2]. More precisely, we make explicit through several examples the connection between interpolating orbifolds and spacetime duality twists. We argue that generic nongeometric backgrounds arising from duality twists will not have simple orbifold constructions and then proceed to construct several examples which do have consistent worldsheet descriptions.
Mathematical Modeling of Signaling Pathways Leading to Type I IFN Gene Expression

Many viruses can escape cellular innate antiviral immune responses by encoding one or more proteins to inhibit the induction of type I interferons (IFN-α/β), which leads to the occurrence of major diseases. However, the mechanisms how some virus-encoded proteins inhibit IFN-α/β induction have not yet been fully understood. Based on available literature and experimental data of classical swine fever virus (CSFV), in this study, we develop a mathematical model of virus- and dsRNA-triggered type I IFN signaling pathways, and investigate the quantitative relationship between the dose of the transfected plasmid and the inhibitory effects of N pro or E rns . Our simulation results showed that CSFV N pro inhibited both dsRNA- and virus- induced IFN-β expression, and E rns only inhibited exogenous dsRNA- triggered IFN-β production, which are agreement with experimental data. The dose-dependent inhibition by N pro or E rns was observed when the transfected plasmid was less than 1.5 g. Furthermore, when the plasmid was more than 1.5 g, the inhibitory effects of both N pro and E rns can reach maximum. These results provide insight into systems properties and generation
Second Order Analysis for Optimal Control Problems: Improving Results Expected From Abstract Theory

An abstract optimization problem of minimizing a functional on a convex subset of a Banach space is considered. We discuss natural assumptions on the functional that permit establishing sufficient second-order optimality conditions with minimal gap with respect to the associated necessary ones. Though the two-norm discrepancy is taken into account, the obtained results exhibit the same formulation as the classical ones known from finite-dimensional optimization. We demonstrate that these assumptions are fulfilled, in particular, by important optimal control problems for partial differential equations. We prove that, in contrast to a widespread common belief, the standard second-order conditions formulated for these control problems imply strict local optimality of the controls not only in the sense of $L^\infty$, but also of $L^2$.