Miracle-dz/UniFAR-FTUs huggingface dataset:
Route to chaos and chimera states in a network of memristive Hindmarsh-Rose neurons model with external excitation

In this paper we have introduced and investigated the collective behavior of a network of memristive Hindmarsh-Rose (HR) neurons. The proposed model was built considering the memristive autapse of the traditional 2D HR neuron. Using the one-parameter bifurcation diagram and its corresponding maximal Lyapunov exponent graph, we showed that the proposed model was able to exhibit a reverse period doubling route to chaos, phenomenon of interior and exterior crises. Three different configurations of the ring-star network of the memristive HR neuron model, including ring-star, ring, and star, have been considered. The study of those network configurations revealed incoherent, coherent , chimera and cluster state behaviors. Coherent behavior is characterized by synchronization of the neurons of the network, while incoherent behaviors are characterized by the absence of synchronization. Chimera states refer to a differet state where there is a coexistence of synchroniaed and asynchronized nodes of the network. One of the interesting result of the paper is the prevalence of double-well chimera states in both ring and ring-star network and has been first mentioned in the case of memrisitve HR neuron model.
Disproof of a packing conjecture of Alon and Spencer

A 1992 conjecture of Alon and Spencer says, roughly, that the ordinary random graph Gn,1/2 typically admits a covering of a constant fraction of its edges by edge‐disjoint, nearly maximum cliques. We show that this is not the case. The disproof is based on some (partial) understanding of a more basic question: for k≪n and A1,…,At chosen uniformly and independently from the k‐subsets of {1,…,n}, what can one say about P(|Ai∩Aj|≤1∀i≠j)? Our main concern is trying to understand how closely the answers to this and a related question about matchings follow heuristics gotten by pretending that certain (dependent) choices are made independently.
Unsupervised feature extraction from multivariate time series for outlier detection

Although various feature extraction algorithms have been developed for time series data, it is still challenging to obtain a flat vector representation with incorporating both of time-wise and variable-wise association between multiple time series. Here we develop an algorithm, called Unsupervised Feature Extraction using Kernel and Stacking (UFEKS), that constructs feature vector representation for multiple time series in an unsupervised manner. UFEKS constructs a kernel matrix for the set of subsequences from each time series and horizontally concatenates all matrices. Then we can treat each row as a feature vector representation of its corresponding subsequence of times series. We examine the effectiveness of the extracted features under the unsupervised outlier detection scenario using synthetic and real-world datasets, and show its superiority compared to well-established baselines.
Second Law-Like Inequalities with Quantum Relative Entropy: An Introduction

We review the fundamental properties of the quantum relative entropy for finite-dimensional Hilbert spaces. In particular, we focus on several inequalities that are related to the second law of thermodynamics, where the positivity and the monotonicity of the quantum relative entropy play key roles; these properties are directly applicable to derivations of the second law (e.g., the Clausius inequality). Moreover, the positivity is closely related to the quantum fluctuation theorem, while the monotonicity leads to a quantum version of the Hatano-Sasa inequality for nonequilibrium steady states. Based on the monotonicity, we also discuss the data processing inequality for the quantum mutual information, which has a similar mathematical structure to that of the second law. Moreover, we derive a generalized second law with quantum feedback control. In addition, we review a proof of the monotonicity in line with Petz.
Free actions of connected Lie groups of rank one on certain spaces

Let $G$ be a connected Lie group of rank one. In this paper the existence of free actions of group $G$ on spheres, real projective spaces and lens spaces has been studied. Most of the results have been obtained for finitistic spaces with cohomology ring isomorphic to the cohomology ring of these spaces. The cohomology algebra of the orbit space has been determined in the case of free $G$-action. The non-existence of $G$-equivariant maps from spheres to cohomology spheres has also been established.
Affine ADE bundles over complex surfaces with p_g=0

We study simply-laced simple affine Lie algebra bundles over complex surfaces X. Given any Kodaira curve C in X, we construct such a bundle over X. After deformations, it becomes trivial on every irreducible component of C provided that p_g(X)=0. When X is a blowup of P^2 at nine points, there is a canonical E_8-bundle E over X. We show that the geometry of X can be reflected by the deformability of E.
In Vitro Antioxidant, Antimicrobial, Anticoccidial, and Anti-Inflammatory Study of Essential Oils of Oregano, Thyme, and Sage from Epirus, Greece

Simple Summary In recent years, consumers’ concern over the use of synthetic antioxidants and antibiotics in food is on the rise, prompting extensive research for alternatives of natural origin. Three essential oils from aromatic plants used in Greek traditional medicine were tested for their antioxidant, anti-inflammatory, and antimicrobial activity in order to determine their applicability as feed additives. The in vitro results showed that plants originating from the western part of Greece, the area of Epirus, possess potent anticoccidial, antimicrobial, anti-inflammatory, and antioxidant activity. Abstract Origanum vulgare subsp. hirtum, Thymus vulgaris, and Salvia fructicosa are aromatic plants commonly found in Mediterranean countries and are traditionally used in Greece as a remedy for humans, since they are well known as potent antibacterial, antioxidant, and anti-inflammatory agents. Essential oils (EOs) derived from plants cultivated in the mountainous region of Epirus, Greece, were investigated for their inhibitory activity against key microorganisms with relevance to avian health, while also assessing their antioxidant and anti-inflammatory activity. The total phenolic content (TPC) of the EOs was estimated according to the Folin–Ciocalteu method, while the antioxidant capacity was tested through the EOs’ ability to scavenge free radicals by means of the DPPH, ABTS, and FRAP assays. Antibacterial and anti-inflammatory effects were examined by the agar disc diffusion method and the lipoxygenase (LOX) inhibition test, respectively. Furthermore, the EOs’ ability to inhibit the invasion of sporozoites of Eimeria tenella (Wisconsin strain) along with any toxic effects were assayed in Madin–Darby bovine kidney (MDBK) cells. The antioxidant activity of the EOs was observed in descending order: oregano > thyme > sage. The antimicrobial effects of thyme and oregano were equivalent and higher than that of sage, while the anti-inflammatory effect of thyme was higher compared to both sage and oregano. The intracellular invasion of sporozoites was evaluated by the detection of E. tenella DNA by qPCR from cell monolayers harvested at 2 and 24 h post-infection. Parasite invasion was inhibited by the addition of oregano essential oil at the concentration of 100 μg/mL by 83% or 93% after 2 or 24 h, respectively, and was higher compared to the addition of thyme and sage, which had similar effects, but at a less intensive level. The cytotoxic assessment of all three essential oils revealed that they had no effect on MDBK cells compared to dimethyl sulfoxide (DMSO), used as the control substance. The supplementation of oregano, thyme, and sage essential oils had a potent antioxidant, anti-inflammatory, antimicrobial, and anticoccidial in vitro effect that is comparable to synthetic substances or approved drugs, justifying the need for further evaluation by in vivo studies in broilers reared in the absence of antimicrobial and anticoccidial drugs or synthetic antioxidant and/or anti-inflammatory compounds.
Clinical Impact of Colonization with Carbapenem-Resistant Gram-Negative Bacteria in Critically Ill Patients Admitted for Severe Trauma

Multidrug-resistant (MDR) Gram-negative bacteria (GNB) have raised concerns as common, frequent etiologic agents of nosocomial infections, and patients admitted to intensive care units (ICUs) present the highest risk for colonization and infection. The incidence of colonization and infection in trauma patients remains poorly investigated. The aim of this study was to assess the risk factors for Carbapenem-resistant (CR)-GNB colonization and the clinical impact of colonization acquisition in patients with severe trauma admitted to the ICU in a CR-GNB hyperendemic country. This is a retrospective observational study; clinical and laboratory data were extracted from the nosocomial infection surveillance system database. Among 54 severe trauma patients enrolled in the study, 28 patients were colonized by CR-GNB; 7 (12.96%) patients were already colonized at ICU admission; and 21 (38.89%) patients developed a new colonization during their ICU stay. Risk factors for colonization were the length of stay in the ICU (not colonized, 14.81 days ± 9.1 vs. colonized, 38.19 days ± 27.9; p-value = 0.001) and days of mechanical ventilation (not colonized, 8.46 days ± 7.67 vs. colonized, 22.19 days ± 15.09; p-value < 0.001). There was a strong statistical association between previous colonization and subsequent development of infection (OR = 80.6, 95% CI 4.5–1458.6, p-value < 0.001). Factors associated with the risk of infection in colonized patients also included a higher Charlson comorbidity index, a longer length of stay in the ICU, a longer duration of mechanical ventilation, and a longer duration of treatment with carbapenem and vasopressors (not infected vs. infected: 0(0–4) vs. 1(0–3), p = 0.012; 24.82 ± 16.77 vs. 47 ± 28.51, p = 0.016; 13.54 ± 15.84 vs. 31.7 ± 16.22, p = 0.008; 1.09 ± 1.14 vs. 7.82 ± 9.15, p = 0.008). The adoption of MDR-GNB colonization prevention strategies in critically ill patients with severe trauma is required to improve the quality of care and reduce nosocomial infections, length of hospital stay and mortality.
Unbounded Orbits for Outer Billiards

The question of B.H. Neumann, which dates back to the 1950s, asks if there exists an outer billiards system with an unbounded orbit. We prove that outer billiards for the Penrose kite, the convex quadrilateral from the Penrose tiling, has an unbounded orbit. We also analyze some finer properties of the orbit structure, and in particular produce an uncountable family of unbounded orbits. Our methods relate outer billiards on the Penrose kite to polygon exchange maps, arithmetic dynamics, and self-similar tilings.
Critique of: “A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery” by SCC Team From UC San Diego

Bayesian networks (BNs) have become popular in recent years to describe natural phenomena in situations where causal linkages are important to understand. In order to get around the inherent non-tractability of learning BNs, Srivastava et al. propose a markov blanket discovery-based approach to learning in their paper titled “A Parallel Framework for Constraint-based Bayesian Network Learning via Markov Blanket Discovery. ” We are able to reproduce both the strong and weak scaling experiments from the paper up to 128 cores, and verify communication cost scaling for all three algorithms in the paper. We also introduce methodological improvements to weak scaling that show the paper's findings are unique to the methodology and not the datasets used. Slight variations in performance were observed due to differences in datasets, core count, and job scheduling.
Monitoring Area Coverage Based on Adjusting Node Spacing in Mixed Underwater Mobile Wireless Sensor Networks

Wireless sensor nodes have the characteristics of small size, light weight, simple structure, and limited energy. They are random during deployment in the monitoring area, and the location of nodes is uncertain after deployment. It is easy to have uneven node distribution, resulting in dense nodes in some areas and sparse nodes in some areas. In the area with dense nodes, the monitoring area is covered repeatedly due to the distance between nodes which is too close. In the area with sparse nodes, the problem of covering blind areas appears due to the distance between nodes which is too far. Aiming at the complex structure of underwater wireless sensor networks, a coverage algorithm based on adjusting the nodes spacing is proposed. The algorithm calculates the reasonable distance between adjacent nodes before the wireless sensor node moves. The distance between wireless sensor nodes increases gradually. The simulation results show that the algorithm can make the clustered wireless sensor nodes disperse gradually by reasonably adjusting the distance between wireless sensor nodes, improve the coverage effect of wireless sensor networks, and reduce the energy consumption of wireless sensor nodes.
Modulus of families of walks on graphs

We introduce the notion of modulus of families of walks on graphs. We show how Beurling's famous criterion for extremality, that was formulated in the continuous case, can be interpreted on graphs as an instance of the Karush-Kuhn-Tucker conditions. We then develop an algorithm to numerically compute modulus using Beurling's criterion as our guide.
L p solutions of finite and infinite time interval BSDEs with non-Lipschitz coefficients

In this paper, we are interested in solving multidimensional backward stochastic differential equations (BSDEs) in under weaker assumptions on the coefficients, considering both a finite and an infinite time interval. We establish a general existence and uniqueness result of solutions in to finite and infinite time interval BSDEs with non-Lipschitz coefficients, which includes the corresponding results in Pardoux and Peng [Syst. Control Lett. 14 (1990), pp. 55–61], Mao [Stoch. Proc. Appl. 58 (1995), pp. 281–292], Chen and Wang [Chin. Sci. Bull. 42 (1997), pp. 2379–2383], Constantin [Analele Universităţii din Timişoara, Seria Matematică-Informatică XXXIX (2001), pp. 15–22], Wang and Wang [Chin. J. Appl. Probab. Statist. 19 (2003), pp. 245–251], Chen and Wang [J. Austral. Math. Soc. (Ser. A) 69 (2000), pp. 187–211] and Wang and Huang [Stat. Probability Lett. 79 (2009), pp. 1438–1443] as its particular cases.
Experimental Seismic Assessment of Nonstructural Elements: Testing Protocols and Novel Perspectives

Nonstructural elements (NEs) are generally defined as elements typically housed within buildings/facilities that are not part of the structural system. Nonstructural elements are often classified as architectural elements, mechanical/electrical/hydraulic systems, and building contents. Nonstructural elements are often associated with critical seismic risk, due to their high vulnerability and exposure to seismic actions, especially for critical facilities such as hospitals and nuclear plant facilities. Accordingly, the combination of major exposure and vulnerability makes NEs extremely critical in terms of seismic risk even for low to moderate seismicity. The paper reviews and evaluates the main international testing approaches and protocols for the seismic assessment of NEs by means of experimental methods, which are referred to for seismic qualification. Existing test protocols are technically analyzed considering quasi-static, single-floor dynamic, and multi-floor dynamic procedures, supplying technical and operative guidance for their implementation, according to the latest advances in the field. The study proposes novel perspectives and a unified approach for the seismic assessment and qualification of NEs. The technical recommendations lay the groundwork for a more robust and standardized testing and qualification framework. In particular, the provided data might represent the first step for developing code and regulation criteria for the experimental seismic assessment and qualification of NEs.
A Method for dSTEC Interpolation: Ionosphere Kernel Estimation Algorithm

Ionospheric structure is important for estimating ionospheric delay for user stations in the global navigation satellite system (GNSS). However, most existing parameter estimation methods suffer from challenges due to data inaccuracy and unavailability of limited and sparse scattered data at ground reference stations. The high variability of active low latitude or disturbed ionosphere leads to GNSS signal scintillation. It is critical to capture the ionospheric random structure and estimate the ionospheric parameter using data of disperse receivers to improve the accuracy. This article proposes a unifying method named ionosphere kernel estimation algorithm (IKEA) to retrieve the information of ionospheric spatial structure. The proposed model utilities the semiparametric representation theorem to incorporate prior information and constraints. The multiple kernel technique is adopted first to include physical correlations. In addition, a learning approach is deployed to determine model parameters. The IKEA model has been verified based on simulated and experimental data at active low latitudes from a network of ground GNSS reference stations from all visible global position system (GPS) and GALILEO satellites. The IKEA model reduces approximately 19.5% and 24.2% of differential slant total electron content (dSTEC) in the root-mean-square error with respect to inverse distance weighting (IDW) and the Kriging model during high ionospheric activities. The IKEA architecture has been demonstrated effective to make a robust ionospheric estimation, which may be further extended for various GNSS applications and beyond.
Drag Estimation in the Near Wake of the NREL's Airfoils Based on Hot-Wire Data

This paper presents the results of the drag coefficient estimations for different types of NREL airfoils based on the experimental data. Namely, it was S803, S807, S813, and S817 profiles with the same chord length. The investigations were conducted at three angles of attack α=0°, α=±5°, different chord-based Reynolds numbers 0.6×105, 1.3×105 and 2.6×105. While, measuring cross-sections were placed behind the trailing edge at x∙c−1≈0.2, 0.4 and 1.0. Experimental data were collected using a hot-wire split fiber probe 55R55, which allowed us to estimate the characteristics of turbulent flow in stream-wise and crosswise directions. According to the obtained results, the highest and lowest Cd values correspond to profiles S817 and S803, respectively. Moreover, the results show that more asymmetric profiles S803 and S807 have the lowest resistance at zero angles of attack. Research background: Application of Antonia and Rajagopalan methodology to drag assessment of various stream bodies. Purpose of the article: Comparative evaluation of the drag coefficients of the NREL airfoils based on instantaneous velocity distribution behind. Methods: Hot-wire anemometry with split fiber probe 55R55. Findings & Value added: The highest drag coefficient corresponds to the S817 profile. The asymmetry of the airfoil shape has a significant impact on its drag characteristics.
Explicit formulas for the Riesz energy of the $N$th roots of unity

The paper Brauchart, Hardin and Saff [Bull. Lond. Math. Soc. 41(4) (2009)] gives the complete asymptotic expansions of the Riesz $s$-energy of the $N$th roots of unity which form a universally optimal distribution of points on the unit circle in the sense of Cohn and Kumar [J. Amer. Math. Soc. 20 (2007)]. Here, exact formulas (valid for all $N \geq 2$) are obtained for the case when $s$ is an even integer. In the case of the singular Riesz $s$-potential $1/r^s$, $r$ the Euclidean distance between two points, a continuous modified energy approximation of the Riesz energy is used. Stirling numbers of the first kind, Eulerian numbers and special values of partial Bell polynomials play a central role. Several identities between these quantities are shown.
Strange duality on $\mathbb{P}^2$ via quiver representations

We study Le Potier's strange duality conjecture on $\mathbb{P}^2$. We focus on the strange duality map $SD_{c_n^r,d}$ which involves the moduli space of rank $r$ sheaves with trivial first Chern class and second Chern class $n$, and the moduli space of 1-dimensional sheaves with determinant $\mathcal{O}_{\mathbb{P}^2}(d)$ and Euler characteristic 0. By using tools in quiver representation theory, we show that $SD_{c^r_n,d}$ is an isomorphisms for $r=n$ or $r=n-1$ or $d\leq 3$, and in general $SD_{c^r_n,d}$ is injective for any $n\geq r>0$ and $d>0$.
Eigenvalue hypothesis for Racah matrices and HOMFLY polynomials for 3-strand knots in any symmetric and antisymmetric representations

Character expansion expresses extended HOMFLY polynomials through traces of products of finite dimensional Rand Racah mixing matrices. We conjecture that the mixing matrices are expressed entirely in terms of the eigenvalues of the corresponding R-matrices. Even a weaker (and, perhaps, more reliable) version of this conjecture is sufficient to explicitly calculate HOMFLY polynomials for all the 3-strand braids in arbitrary (anti)symmetric representations. We list the examples of so obtained polynomials for R = [3] and R = [4], and they are in accordance with the known answers for torus and figure-eight knots, as well as for the colored special and Jones polynomials. This provides an indirect evidence in support of our conjecture.
Sparse bounds for the discrete spherical maximal functions

We give a short proof of some sparse bounds for the spherical maximal operator of Magyar, Stein and Wainger. This proof also includes certain endpoint estimates. The new method of proof is inspired by ones by Bourgain and Ionescu, is very efficient, and not been used in the proof of sparse bounds before. The Hardy-Littlewood Circle method is used to decompose the multiplier into major and minor arc components. The efficiency arises as one only needs a single estimate on each element of the decomposition.
Users' Perceptions of Key Blockchain Features in Games

The blockchain is an emerging technology that has the potential to revolutionize the gaming industry among a wide range of different business fields. So far, only a few studies have been conducted about blockchain gaming. This study introduces a mobile game utilizing blockchain asset tokens and smart contracts. It was developed for research purposes and used to demonstrate blockchain-based games using semi-structured interviews. This study follows the exploratory research paradigm, which aims to map research of little-known areas. This study focuses on how participants perceived blockchain attributes such as trust, transparency, and user-generated content and how this affected engagement and their willingness to play the game again. Based on our evaluation, generating blockchain assets positively impacted player retention. According to the results, providing genuine asset ownership through the blockchain contributes to environmental engagement and self-engagement, as well as player retention. Another positive blockchain feature discovered from the interview data is user-generated content implementation into games.