Miracle-dz/UniFAR-FTUs huggingface dataset:
Parity and Exotic Combinatorial Formulae for Finite-Type Invariants of Virtual Knots

The present paper produces examples of Gauss diagram formulae for virtual knot invariants which have no analogue in the classical knot case. These combinatorial formulae contain additional information about how a subdiagram is embedded in a virtual knot diagram. The additional information comes from the second author's recently discovered notion of parity. For a parity of flat virtual knots, the new combinatorial formulae are Kauffman finite-type invariants. However, many of the combinatorial formulae possess exotic properties. It is shown that there exists an integer valued virtualization invariant combinatorial formula of order n for every n (i.e. it is stable under the map which changes the direction of one arrow but preserves the sign). Hence, it is not of Goussarov-Polyak-Viro finite-type. Moreover, every homogeneous Polyak-Viro combinatorial formula admits a decomposition into an "even" part and an "odd" part. For the Gaussian parity, neither part of the formula is of GPV finite-type when it is nonconstant on the set of classical knots. In addition, eleven new non-trivial combinatorial formulae of order 2 are presented which are not of GPV finite-type.
Closely spaced object detection utilizing spatial information in spectroastrometric observations

The detection of closely spaced artificial satellites informs tactical decision making in a high risk scenario in the space domain. In regimes where spatial information is lost (ground observations of small or distant satellites), spectroastrometry simulations have demonstrated the potential to detect the presence of multiple objects down to 0′′. 05–ten meters at geostationary orbit–using a medium resolution optical spectrograph on a large aperture telescope.1 This technique falls into the growing field of learned space domain awareness: leveraging convolutional neural networks to rapidly infer tactical information from complex, non-intuitive data. In this work we present a field rotation nodding technique that removes the need for a priori knowledge of the closely spaced object on sky orientation. We discuss modifications to an optical spectrograph necessary to perform this technique. We present simulated bounds on the effectiveness of spectroastrometry for the detection of closely spaced objects.
Homotopy theory of C*-algebras

In this work we construct from ground up a homotopy theory of C-algebras. This is achieved in parallel with the development of classical homotopy theory by first introducing an unstable model structure and second a stable model structure. The theory makes use of a full fledged import of homotopy theoretic techniques into the subject of C-algebras. The spaces in C-homotopy theory are certain hybrids of functors represented by C-algebras and spaces studied in classical homotopy theory. In particular, we employ both the topological circle and the C-algebra circle of complex-valued continuous functions on the real numbers which vanish at infinity. By using the inner workings of the theory, we may stabilize the spaces by forming spectra and bispectra with respect to either one of these circles or their tensor product. These stabilized spaces or spectra are the objects of study in stable C-homotopy theory. The stable homotopy category of C-algebras gives rise to invariants such as stable homotopy groups and bigraded cohomology and homology theories. We work out examples related to the emerging subject of noncommutative motives and zeta functions of C-algebras. In addition, we employ homotopy theory to define a new type of K-theory of C-algebras. Department of Mathematics, University of Oslo, Norway. MSC Primary: 46L99, 55P99
Simulation and experimental study on the elbow pressure loss of large air duct with different internal guide vanes

Air duct pressure loss, especially the duct elbow, is a significant component of building air-conditioning energy consumption. Improving the airflow uniformity in the duct elbow for large prefabricated air ducts can help reduce the local resistance loss. In this paper, the influence of guide vanes on the pressure loss of elbows in the duct was investigated through experimentally validated simulation results. According to similarity theory, the computational fluid dynamics (CFD) simulation results were employed to perform a parametric study to optimize the duct elbow guide vane. Different numbers, positions, and shapes of air guide vanes in the elbow were used to reduce the pressure loss and also played a crucial role in improving the uniformity of airflow in the elbow. Through CFD simulation, the optimized specifications of guide vanes in the elbow on the airflow and local pressure loss coefficients were explored. This study will provide a reference for numerical prediction and engineering application of using guide vane to minimize the local pressure loss of large prefabricated air ducts.
POINTED HOPF ALGEBRAS WITH STANDARD BRAIDING ARE GENERATED IN DEGREE ONE

We show that any finite-dimensional pointed Hopf algebra over an abelian group such that its infinitesimal braiding i s of stan- dard type is generated by group-like and skew-primitive elements. This fact agrees with the long-standing conjecture by Andruskiewitsch and Schneider. We also show that the quantum Serre relations hold in any coradically graded pointed Hopf algebra over of finite dime nsion and determine how these relations are lifted in the standard case.
Asymptotics of Selberg-like integrals: The unitary case and Newton's interpolation formula

We investigate the asymptotic behavior of the Selberg-like integral 1N! ∫[0,1]Nx1p∏i<j(xi−xj)2∏ixia−1(1−xi)b−1dxi, as N → ∞ for different scalings of the parameters a and b with N. Integrals of this type arise in the random matrix theory of electronic scattering in chaotic cavities supporting N channels in the two attached leads. Making use of Newton's interpolation formula, we show that an asymptotic limit exists and we compute it explicitly.
A comparison between Kalman ensemble generator and geostatistical frequency-domain electromagnetic inversion: the impacts on near-surface characterization

The spatial distribution of the physical properties of the first meters beneath the Earths surface is often complex due to its highly dynamic nature and small-scale heterogeneities resulting from both natural and anthropogenic processes. Therefore, obtaining numerical three-dimensional models that accurately describe the spatial distribution of these properties is often challenging, yet essential for different fields such as environmental assessment and remediation, geoarchaeological conservation, and precision agriculture. Frequency-domain electromagnetic (FDEM) induction methods have proven their potential to image these properties in high (spatial) detail as FDEM measurements are sensitive to two key soil properties: electrical conductivity; and magnetic susceptibility. Predicting subsurface properties from FDEM data requires solving an ill-posed and nonlinear inverse problem with multiple solutions. Recently, there has been a rapid growth of FDEM inversion methods, which may be broadly divided into probabilistic and deterministic methods. We compare two stochastic FDEM inversion approaches: the Kalman ensemble generator (KEG); and another one formulated as an iterative geostatistical FDEM inversion. Both methods are applied to a synthetic data set with spatially heterogeneous physical properties of interest, mimicking a real landfill mining site. The predicted models are compared to the reference models in terms of histogram and variogram models reproduction and in their ability to quantify spatial uncertainty. The results show the ability of both methods to predict the reference values. While the KEG is computationally efficient, it struggles to reproduce the extreme values. On the contrary, the geostatistical inversion approach ensures the reproduction of the imposed histograms and variogram models in the predicted models. As the prior information is included in both inversion methods in different ways, the pointwise variance models computed from all the posterior models has different information. The synthetic data set is available to the community so it can be used as benchmark for other FDEM inversion methods.
Equivariant Gromov-Witten theory of one dimensional stacks

In math.AG/0207233, Okounkov and Pandharipande gave an operator formalism for computing the equivariant Gromov-Witten theory of the projective line. This thesis extends their result to orbifold lines. In the effective case the theory is again governed by the 2-Toda hierarchy. In the ineffective case the decomposition conjecture of hep-th/0606034 is verified.
Resonances for a diffusion with small noise

We study resonances for the generator of a diffusion with small noise in $R^d$ :$ L_\epsilon = -\epsilon\Delta + \nabla F \cdot \nabla$, when the potential F grows slowly at infinity (typically as a square root of the norm). The case when F grows fast is well known, and under suitable conditions one can show that there exists a family of exponentially small eigenvalues, related to the wells of F . We show that, for an F with a slow growth, the spectrum is R+, but we can find a family of resonances whose real parts behave as the eigenvalues of the "quick growth" case, and whose imaginary parts are small.
Snake Venom and 3D Microenvironment Cell Culture: From Production to Drug Development

Snake venoms are a natural biological source of bioactive compounds, mainly composed of proteins and peptides with specific pathophysiological functions. The diversity of protein families found in snake venoms is reflected by the range of targets and toxicological effects observed, and consequently, a wide variety of potential pharmacological activities. In this context, in vitro biomimetic models such as spheroid and organoid systems, which are three-dimensional (3D) cell culture models, enable extensive screening and identification of substances with pharmacological potential and the determination of the mechanisms underlying their activities. In this review we summarize the main findings of 3D microenvironment cell culture as a promising model for snake venom research, from producing snake toxins on venom gland organoids to screening pharmacological active compounds on spheroids for drug development.
Forest 1.0: A Language and Toolkit For Programming with Filestores

A ﬁlestore is a structured collection of data ﬁles housed in a conventional hierarchical ﬁle system. Many applications use ﬁlestores as a poor-man’s database, and the correct execution of these applications requires that the collection of ﬁles, directories, and symbolic links stored on disk satisfy a variety of precise invariants. More-over, all of these structures must have acceptable ownership, permission, and timestamp attributes. Unfortunately, current programming languages do not provide support for documenting assumptions about ﬁlestores, detecting errors, or safely loading from and storing to them. This paper describes the design, implementation, and semantics of Forest, a novel domain-speciﬁc language for describing ﬁle-stores. The language uses a type-based metaphor to specify the expected structure, attributes, and invariants of ﬁlestores. Forest generates loading and storing functions that make it easy to connect data on disk to an isomorphic representation in memory that can be manipulated as if it were any other data structure. Forest also generates metadata that describes the degree to which the structures on the disk conform to the speciﬁcation, making error detection easy. Hence, in a nutshell, Forest extends the rigorous discipline of typed programming languages and many of their beneﬁts to the untyped world of ﬁle systems. We have implemented Forest as an embedded domain-speciﬁc language in Haskell. In addition to generating infrastructure for reading, writing and checking ﬁle systems, our implementation generates a type class instances that make it easy to build generic tools that operate over arbitrary ﬁlestores. We illustrate the utility of this infrastructure by building a ﬁle system visualizer, a ﬁle access checker, a generic query interface, description-directed variants of several standard UNIX shell tools and (circularly) a simple Forest description inference engine. Finally, we formalize a core fragment of Forest in a semantics inspired by classical tree logics and prove round-tripping laws showing that the loading and storing functions behave sensibly
Software-Defined Network Virtualization with FlowN

Network virtualization enables multiple control planes to run concurrently and each aﬀect only its portion of the data plane state and conﬁguration. With the standardization of the interface between the control plane and data plane, software deﬁned networking is a natural ﬁt with network virtualization as any software can run to interact with the data plane. A virtualization layer can then be created which modiﬁes the view of the physical network and enables multiple control planes to run concurrently – each targeting a diﬀerent view of the dataplane. In contrast to previous virtualization solutions, which also attempt to abstract the network design, we propose that for shared infrastructures, such as cloud computing, the abstraction should be decoupled from the virtualization support, to support diﬀerent abstractions for diﬀerent tenants. With this, we present the FlowN system, which implements full network virtualization, with which each virtual network: (i) is independent and can control the entire ﬂow address space, (ii) can control the entire path within the network, (iii) can be an arbitrary topology. The FlowN architecture is designed to be scalable through two novel approaches in software deﬁned networking (SDN): the use of existing database technology for mapping virtual to physical topologies, and a shared controller platform analogous to container-based virtualization. Our prototype extends the OpenFlow NOX controller and uses a MySQL database. We demonstrate the latency eﬃciency of our container based approach by comparing it to FlowVisor and unvirtualized NOX.
Generalized Heine’s identity for complex Fourier series of binomials

In his treatise, Heine (Heine 1881 In Theorie und Anwendungen) gave an identity for the Fourier series of the function , with , and z>1, in terms of associated Legendre functions of the second kind . In this paper, we generalize Heine’s identity for the function , with , and , in terms of . We also compute closed-form expressions for some .
Exploiting Neur al Networ k for Tempor al Multi-var iate Air Quality and Pollutant Pr ediction

In recent years, the air pollution and Air Quality Index (AQI) has been a pivotal point for researchers due to its effect on human health. Various research has been done in predicting the AQI but most of these studies, either lack dense temporal data or cover one or two air pollutant elements. In this paper, a hybrid Convolutional Neural approach integrated with recurrent neural network architecture (CNN-LSTM), is presented to find air pollution inference using a multivariate air pollutant elements dataset. The aim of this research is to design a robust and real-time air pollutant forecasting system by exploiting a neural network. The proposed approach is implemented on a 24-month dataset from Seoul, Republic of Korea. The predicted results are cross-validated with the real dataset and compared with the state-of-the-art techniques to evaluate its robustness and performance. The proposed model outperforms SVM, SVM-Polynomial, ANN, and RF models with 60.17%, 68.99%, 14.6%, and 6.29%, respectively. The model performs SVM and SVM-Polynomial in predicting O3 by 78.04% and 83.79%, respectively. Overall performance of the model is measured in terms of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and the Root Mean Square Error (RMSE).
ON ASSESSMENT IN TEACHING POLITICAL PHILOSOPHY: DESIRABILITY

The article offers a tool that can be used for assessment of ideas in political philosophy with students in education processes. The proposed method of assessment is based on the criteria of desirability and feasibility. Employing this method can help the students focus more carefully and point their thinking to two important aspects of normative theories in political philosophy. The article provides an analysis of the two criteria and shows how desirability-feasibility assessment should proceed. By doing that, it proposes a system of combining desirability and feasibility in critical assessment of ideas in political philosophy.
Performance comparison between optimization algorithms for asymmetrical cascaded multilevel inverter

This paper discusses the hardware and control system design of the asymmetric cascade multilevel inverter. The asymmetric cascaded multilevel inverter structure is adopted to minimize bridges, gate drive circuits and DC power source number. Therefore, the proposed structure is able to generate higher voltage at higher speed with low switching losses and high efficiency. SelectiveHarmonic Elimination (SHE) based onNewton-Raphson (N-R) algorithm is developed to calculate a switching angle for a range of modulation index to control asymmetric cascade multilevel inverter. Simulation results prove that Newton-Raphson technique is more effective than genetic algorithm (G-A) and equal calculated switching angles method (ECSA). A comparison between the algorithm performance for 9-level asymmetric cascade H-bridge inverter control was evaluated and experimentally tested on FPGA-based prototypes ARTICLE HISTORY Received 18 September 2019 Accepted 10 August 2020
Harveri : A Small (Semi-)Autonomous Precision Tree Harvester

This article presents the development of a small harvester (Harveri) targeted for thinning operations and energy tree harvesting. We are interested in two possible use cases: teleoperation by a human and fully autonomous operation. We introduce Harveri itself, together with the hardware modifications made to facilitate the automation of the machine. Furthermore, we describe the sensors used and the rationale behind each sensor choice and physical placement on the machine. The article also discusses computation units used to achieve the teleoperation and autonomy task and connectivity to the machine. Most of the autonomy features are ported from our previous work on HEAP, and in this article, we describe the modifications necessary for Harveri. We present the current automation progress and give directions for future work.
On Rho invariants of fiber bundles

Using adiabatic limits of Eta invariants, Rho invariants of the total space of a fiber bundle are investigated. One concern is to formulate the aspects of local index theory for families of Dirac operator in terms of the odd signature operator, and place known results in a context which permits the treatment of Rho invariants. The main focus is, however, to use this to compute Rho invariants for explicit classes of fibered 3-manifolds. More precisely, we consider $\U(1)$-Rho invariants of principal $S^1$-bundles over closed, oriented surfaces as well as mapping tori with torus fiber. Hyperbolic monodromy maps deserve particular attention. When discussing them, the logarithm of a generalized Dedekind Eta function naturally appears. An explicit formula for $\U(1)$-Rho invariants is then deduced from a transformation formula for these Dedekind Eta functions.
General Theory for Integer-Type Algorithm for Higher Order Differential Equations

Based on functional analysis, we propose an algorithm for finite-norm solutions of higher-order linear Fuchsian-type ordinary differential equations (ODEs) with by using only the four arithmetical operations on integers. This algorithm is based on a band-diagonal matrix representation of the differential operator , though it is quite different from the usual Galerkin methods. This representation is made for the respective CONSs of the input Hilbert space ℋ and the output Hilbert space ℋ◊ of . This band-diagonal matrix enables the construction of a recursive algorithm for solving the ODE. However, a solution of the simultaneous linear equations represented by this matrix does not necessarily correspond to the true solution of ODE. We show that when this solution is an ℓ2 sequence, it corresponds to the true solution of ODE. We invent a method based on an integer-type algorithm for extracting only ℓ2 components. Further, the concrete choice of Hilbert spaces ℋ and ℋ◊ is also given for our algorithm when p m is a polynomial or a rational function with rational coefficients. We check how our algorithm works based on several numerical demonstrations related to special functions, where the results show that the accuracy of our method is extremely high (with several hundred or several thousand significant digits).
Fukaya A_\infty-structures associated to Lefschetz fibrations. II 1/2

We consider a version of the relative Fukaya category for anticanonical Lefschetz pencils. There are direct connections between the behaviour of this category and enumerative geometry: some of these are results announced here, others remain conjectural. The ultimate aim of this approach is to determine the Fukaya category of the Calabi-Yau hypersurfaces that constitute the pencil.
Web Privacy Measurement: Early Results, Engineering Challenges and Selected Applications

Web Privacy Measurement experiments have heavily inﬂuenced privacy debates by shedding light into practices such as third party online tracking and price discrimination. However, these research experiments have typically been one-oﬀ projects, with diﬀerent groups encountering similar methodological and engineering challenges without forming an institutional knowledge base. As an illustrative example of this trend of repeating eﬀort through self-contained experiments, we present the results of one study comparing mobile and desktop tracking and discuss how challenges from this study and other works in the literature shaped the formation of general design principles intended to improve the eﬃciency of such experiments. We present a robust and modular web measurement platform that enables scalable and repeatable experiments while avoiding many common pitfalls observed by the research community. We describe case studies performed on this framework, including the detection of unique cookie identiﬁers, the detection of third-party synchronization of these IDs and an examination into the personalization of the content on news sites based on user history.
Gamma Radiation (60Co) Induces Mutation during In Vitro Multiplication of Vanilla (Vanilla planifolia Jacks. ex Andrews)

In vitro mutagenesis is an alternative to induce genetic variation in vanilla (Vanilla planifolia Jacks. ex Andrews), which is characterized by low genetic diversity. The objective of this study was to induce somaclonal variation in V. planifolia by gamma radiation and detect it using inter-simple sequence repeat (ISSR) molecular markers. Shoots previously established in vitro were multiplied in Murashige and Skoog culture medium supplemented with 2 mg·L−1 BAP (6-benzylaminopurine). Explants were irradiated with different doses (0, 20, 40, 60, 80 and 100 Gy) of 60Co gamma rays. Survival percentage, number of shoots per explant, shoot length, number of leaves per shoot, and lethal dose (LD50) were recorded after 60 d of culture. For molecular analysis, ten shoots were used for each dose and the donor plant as a control. Eight ISSR primers were selected, and 43 fragments were obtained. The percentage of polymorphism (% P) was estimated. A dendrogram based on Jaccard’s coefficient and the neighbor joining clustering method was obtained. Results showed a hormetic effect on the explants, promoting development at low dose (20 Gy) and inhibition and death at high doses (60–100 Gy). The LD50 was observed at the 60 Gy. Primers UBC-808, UBC-836 and UBC-840 showed the highest % P, with 42.6%, 34.7% and 28.7%, respectively. Genetic distance analysis showed that treatments without irradiation and with irradiation presented somaclonal variation. The use of gamma rays during in vitro culture is an alternative to broaden genetic diversity for vanilla breeding.