Miracle-dz/UniFAR-FTUs huggingface dataset:
Aligning Leadership Education: Linking Interpersonal Skills Development to Business Needs

A disconnect has long existed between what is typically taught in management education programs and what real-world organizations seek in their leadership candidates, particularly regarding interpersonal skills. Primary complaints from the business community revolve around issues of curriculum relevance and delivery methodologies that do not facilitate the transfer of skills learned in the classroom to the workplace. A review of the literature yields very few examples of business programs that have added courses, or topics within existing courses, that address interpersonal skills. We describe a graduate-level course designed to intentionally develop interpersonal skills to meet the needs of local hiring managers, maximize organizational outcomes, and enhance leaders’ career opportunities. The course is delivered via active, experiential instructional methodologies to facilitate the transfer of new knowledge and skills to the workplace. A pre- and post-test comparison of students’ results on a competency-based behavioral model of emotional intelligence showed an increase in students’ scores, indicating that the course has been effective in developing students’ practical interpersonal skills. This article describes the fundamental design and delivery elements of this successful leadership course that can be replicated and implemented at other universities to more effectively align what students learn with what organizations need.
Insights into Antiviral Properties and Molecular Mechanisms of Non-Flavonoid Polyphenols against Human Herpesviruses

Herpesviruses are one of the most contagious DNA viruses that threaten human health, causing severe diseases, including, but not limited to, certain types of cancer and neurological complications. The overuse and misuse of anti-herpesvirus drugs are key factors leading to drug resistance. Therefore, targeting human herpesviruses with natural products is an attractive form of therapy, as it might improve treatment efficacy in therapy-resistant herpesviruses. Plant polyphenols are major players in the health arena as they possess diverse bioactivities. Hence, in this article, we comprehensively summarize the recent advances that have been attained in employing plant non-flavonoid polyphenols, such as phenolic acids, tannins and their derivatives, stilbenes and their derivatives, lignans, neolignans, xanthones, anthraquinones and their derivatives, curcuminoids, coumarins, furanocoumarins, and other polyphenols (phloroglucinol) as promising anti-herpesvirus drugs against various types of herpesvirus such as alpha-herpesviruses (herpes simplex virus type 1 and 2 and varicella-zoster virus), beta-herpesviruses (human cytomegalovirus), and gamma-herpesviruses (Epstein–Barr virus and Kaposi sarcoma-associated herpesvirus). The molecular mechanisms of non-flavonoid polyphenols against the reviewed herpesviruses are also documented.
Existence, uniqueness and regularity of the solution of the time-fractional Fokker–Planck equation with general forcing

A time-fractional Fokker-Planck initial-boundary value problem is considered, with differential operator $u_t-\nabla\cdot(\partial_t^{1-\alpha}\kappa_\alpha\nabla u-\textbf{F}\partial_t^{1-\alpha}u)$, where $0<\alpha <1$. The forcing function $\textbf{F} = \textbf{F}(t,x)$, which is more difficult to analyse than the case $\textbf{F}=\textbf{F}(x)$ investigated previously by other authors. The spatial domain $\Omega \subset\mathbb{R}^d$, where $d\ge 1$, has a smooth boundary. Existence, uniqueness and regularity of a mild solution $u$ is proved under the hypothesis that the initial data $u_0$ lies in $L^2(\Omega)$. For $1/2<\alpha<1$ and $u_0\in H^2(\Omega)\cap H_0^1(\Omega)$, it is shown that $u$ becomes a classical solution of the problem. Estimates of time derivatives of the classical solution are derived---these are known to be needed in numerical analyses of this problem.
A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations

For the problem of sparse recovery, it is widely accepted that nonconvex minimizations are better than $\ell_1$ penalty in enhancing the sparsity of solution. However, to date, the theory verifying that nonconvex penalties outperform (or are at least as good as) $\ell_1$ minimization in exact, uniform recovery has mostly been limited to separable cases. In this paper, we establish general recovery guarantees through null space conditions for nonconvex, non-separable regularizations, which are slightly less demanding than the standard null space property for $\ell_1$ minimization.
Existence of solution for a class of fractional Hamiltonian systems

In this work we want to prove the existence of solution for a class of fractional Hamiltonian systems given by {eqnarray*}_{t}D_{\infty}^{\alpha}(_{-\infty}D_{t}^{\alpha}u(t)) + L(t)u(t) = & \nabla W(t,u(t)) u\in H^{\alpha}(\mathbb{R}, \mathbb{R}^{N}) {eqnarray*}
Multiple FBG Wavelength Peaks Detection using Z-score algorithm

The functioning of fiber Bragg grating (FBG) sensors is primarily based on the monitoring of the Bragg wavelength shift. to accomplish this purpose, an expansion of algorithms had been proposed, from conventional most and centroid detection methods to more recently evolved correlation-primarily based techniques. We endorse a beneficial technique for finding FBG peaks based on the Z-rating algorithm. The Z-rating height Detection algorithm chooses the factors (peaks) which are outdoor the threshold the use of a transferring suggests and deviation. as it creates a separate transferring imply and deviation, the set of rules is relatively dependable and ensures that alerts do now not taint the brink. consequently, no matter the number of prior alerts, destiny alerts are detected with kind of the identical accuracy. The proposed method can be used successfully to discover more than one peaks whilst there are numerous cascaded FBGs and weak and noisy FBG signals.
Fast Topology Optimization of PM Motor Using Variational Autoencoder and Neural Networks with Dropout

This paper presents a fast topology optimization of a permanent magnet (PM) motor using variational autoencoder (VAE) and neural network (NN) with dropout. PM Motors generated through topology optimization are embedded into low-dimensional latent space using VAE. For high reliability, the properties of the motor generated from the latent space are evaluated by NN with Monte Carlo dropout. It is shown that the proposed method can provide very fast approximations of the Pareto solutions at good accuracy.
On the Two‐Dimensional Muskat Problem with Monotone Large Initial Data

We consider the evolution of two incompressible, immiscible fluids with different densities in porous media, known as the Muskat problem [21], which in two dimensions is analogous to the Hele‐Shaw cell [24]. We establish, for a class of large and monotone initial data, the global existence of weak solutions. The proof is based on a local well‐posedness result for the initial data with certain specific asymptotics at spatial infinity and a new maximum principle for the first derivative of the graph function. © 2016 Wiley Periodicals, Inc.
VALUE PATTERNS OF MULTIPLICATIVE FUNCTIONS AND RELATED SEQUENCES

We study the existence of various sign and value patterns in sequences defined by multiplicative functions or related objects. For any set $A$ whose indicator function is ‘approximately multiplicative’ and uniformly distributed on short intervals in a suitable sense, we show that the density of the pattern $n+1\in A$ , $n+2\in A$ , $n+3\in A$ is positive as long as $A$ has density greater than $\frac{1}{3}$ . Using an inverse theorem for sumsets and some tools from ergodic theory, we also provide a theorem that deals with the critical case of $A$ having density exactly $\frac{1}{3}$ , below which one would need nontrivial information on the local distribution of $A$ in Bohr sets to proceed. We apply our results first to answer in a stronger form a question of Erdős and Pomerance on the relative orderings of the largest prime factors $P^{+}(n)$ , $P^{+}(n+1),P^{+}(n+2)$ of three consecutive integers. Second, we show that the tuple $(\unicode[STIX]{x1D714}(n+1),\unicode[STIX]{x1D714}(n+2),\unicode[STIX]{x1D714}(n+3))~(\text{mod}~3)$ takes all the $27$ possible patterns in $(\mathbb{Z}/3\mathbb{Z})^{3}$ with positive lower density, with $\unicode[STIX]{x1D714}(n)$ being the number of distinct prime divisors. We also prove a theorem concerning longer patterns $n+i\in A_{i}$ , $i=1,\ldots ,k$ in approximately multiplicative sets $A_{i}$ having large enough densities, generalizing some results of Hildebrand on his ‘stable sets conjecture’. Finally, we consider the sign patterns of the Liouville function $\unicode[STIX]{x1D706}$ and show that there are at least $24$ patterns of length $5$ that occur with positive upper density. In all the proofs, we make extensive use of recent ideas concerning correlations of multiplicative functions.
On derived categories of arithmetic toric varieties

We begin a systematic investigation of derived categories of smooth projective toric varieties defined over an arbitrary base field. We show that, in many cases, toric varieties admit full exceptional collections. Examples include all toric surfaces, all toric Fano 3-folds, some toric Fano 4-folds, the generalized del Pezzo varieties of Voskresenskii and Klyachko, and toric varieties associated to Weyl fans of type $A$. Our main technical tool is a completely general Galois descent result for exceptional collections of objects on (possibly non-toric) varieties over non-closed fields.
Lithium-Ion Battery State of Charge and State of Power Estimation Based on a Partial-Adaptive Fractional-Order Model in Electric Vehicles

In this article, a fractional-order model (FOM)-based online state of charge (SOC) and state of power (SOP) estimation method is proposed for lithium-ion batteries in electric vehicles. First, the model parameters of a second-order FOM are globally optimized under the dynamic stress test profile, where two resistor-constant phase element networks are recognized to represent battery internal dynamics at different timescales. Second, to enhance the model performance in SOC and SOP estimation, a partial-adaptive FOM (PA-FOM) is realized by fixing the parameters of the first resistor-constant phase element network with slow dynamics while allowing the online adaption of the second resistor-constant phase element network with fast dynamics. Based on the PA-FOM, online SOC estimation is implemented using an adaptive extended Kalman filter algorithm while an unscented Kalman filter-based iterative approaching algorithm is devised to estimate SOP. The proposed method is validated under different EV driving profiles. The experimental results show that the PA-FOM has an outstanding performance in interpreting battery dynamics at different timescales and the proposed SOC and SOP estimation method is highly accurate and efficient.
OpenAirInterface as a platform for 5G-NTN Research and Experimentation

Technical advancements and experimental works for the integration of 5G and Non-Terrestrial Networks (NTN) have gained significant traction over the past few years. NTN components have been officially included in the 5G ecosystem by 3GPP in the latest Release-17. 5G-NTN research is ongoing and it is desirable to have a platform that facilitates quick prototyping of the proof-of-concept methods. OpenAirInterface(OAI) is an open-source experimental yet 3GPP standard-compliant Software Defined Radio (SDR) based protocol stack that has been widely known for implementing 4G/5G technologies. Due to its proven capabilities and flexibility, OAI is currently in the developmental process of integrating adaptations for the 5G-NTN. In this work, we discuss the peculiar features of OAI which are shaping it towards becoming a preferred tool for research and experimentation related to 5G-NTN. We provide details of completed/ongoing 5G-NTN projects leveraging OAI to achieve their objectives. In particular, we discuss 5G-GOA and 5G-LEO where critical adaptations in OAI are being done to support 5G-NTN use-cases. Such adaptations enable direct-access between UE and gNB via transparent payload Geostationary (5G-GOA) and Non-geostationary satellites (5G-LEO). Both projects have closely followed 3GPP discussions over 5G-NTN and the adaptations are compliant with the currently frozen 3GPP Release-17. OAI adaptations from both projects will be merged into the main development branch of OAI. We also provide a future roadmap of OAI towards 5G-NTN development. We believe that the pioneering steps taken in the course of the aforementioned projects will establish OAI as a preferred tool for 5G-NTN research and experimentations.
Dynamic Community Detection Based on Evolutionary DeepWalk

To fully characterize the evolution process of the topological structure of dynamic communities, we propose a dynamic community detection based on Evolutionary DeepWalk (DEDW) for the high-dimensional data and dynamic characteristics. First, DEDW solves the problem of data sparseness in the process of dynamic network data representation through graph embedding. Then, DEDW uses the DeepWalk algorithm to generate node embedding feature vectors based on the characteristics of the stable change of the community structure; finally, DEDW integrates historical network structure information to generate evolutionary graph features and implements dynamic community detection with the K-means algorithm. Experiments show that DEDW can mine the time-smooth change characteristics of dynamic communities, solve the problem of data sparseness in the process of node embedding, fully consider historical structure information, and improve the accuracy and stability of dynamic community detection.
Gastrointestinal Bleeding Due to NOACs Use: Exploring the Molecular Mechanisms

Novel oral anticoagulants (NOACs) are drugs approved for the prevention and treatment of many thromboembolic cardiovascular conditions as a safer alternative to warfarin. We reviewed studies published in PubMed®, UpToDate®, Web of Science®, and Cochrane® about NOACs’ risks and benefits in patients requiring anticoagulation, with a focus on gastrointestinal bleeding and on molecular and pathophysiological mechanisms underlying the risk of bleeding in patients treated with them. Apixaban resulted in a lower rate of gastrointestinal bleeding compared to dabigatran and rivaroxaban. However, data reported that gastrointestinal bleeding in patients treated with NOACs was less severe compared to warfarin. Studies show promising results on the increased and widespread use of NOACs in patients who require anticoagulation (for example—in case of atrial fibrillation or high risk of venous thromboembolism), reporting an overall lower risk of major bleeding events. The profile of NOACs was more effective and secure compared to warfarin, but a more careful medical prescription is required in patients who are at high risk of gastrointestinal bleeding.
Exact relaxation for polynomial optimization on semi-algebraic sets

In this paper, we study the problem of computing by relaxation hierarchies the infimum of a real polynomial function f on a closed basic semialgebraic set and the points where this infimum is reached, if they exist. We show that when the infimum is reached, a relaxation hierarchy constructed from the Karush-Kuhn-Tucker ideal is always exact and that the vanishing ideal of the KKT minimizer points is generated by the kernel of the associated moment matrix in that degree, even if this ideal is not zero-dimensional. We also show that this relaxation allows to detect when there is no KKT minimizer. We prove that the exactness of the relaxation depends only on the real points which satisfy these constraints.This exploits representations of positive polynomials as elementsof the preordering modulo the KKT ideal, which only involves polynomials in the initial set of variables. Applications to global optimization, optimization on semialgebraic sets defined by regular sets of constraints, optimization on finite semialgebraic sets, real radical computation are given.
pH-Driven Selective Adsorption of Multi-Dyes Solutions by Loofah Sponge and Polyaniline-Modified Loofah Sponge

In the last decades, sorbent materials characterized by low selectivity have been developed for the removal of pollutants (in particular dyes) from wastewater. However, following the circular economy perspective, the possibility to selectively adsorb and desorb dyes molecules today represents an unavoidable challenge deserving to be faced. Herein, we propose a sequential treatment based on the use of PANI-modified loofah (P-LS) and loofah sponge (LS) to selectively adsorb cationic (rhodamine, RHB, and methylene blue, MB) and anionic (methyl orange, MO) dyes mixed in aqueous solution by tuning the adsorption pH (100% MO removal by P-LS and 100% and 70% abatement of MB and RHB, respectively, by LS). The system maintained high sorption activity for five consecutive cycles. A simple and effective regeneration procedure for the spent adsorbents permits the recovery of the initial sorption capability of the materials (81% for MO, ca. 85% for both RHB and MB, respectively) and, at the same time, the selective release of most of the adsorbed cationic dyes (50% of the adsorbed MB and 50% of the adsorbed RHB), although the procedure failed regarding the release of the anionic component. This approach paved the way to overcome the traditional procedure based on an indiscriminate removal/degradation of pollutants, making the industrial wastewater a potential source of useful chemicals.
Non-convex 4d polytopes in Spin Foam Models

In this article we consider non-convex $4d$ polytopes in $\mathbb{R}^4$. The paper consist of two parts: Firstly, we extend the proof of the formula for the $4d$ volume in terms of $2d$ face bivectors and boundary graph crossings from convex to non-convex polytopes. Secondly, we consider the EPRL-FK spin foam model, and demonstrate that there exists boundary data which leads to non-convex $4d$ polytopes in the asymptotic analysis of the vertex amplitude.
Geometric Discretization of the EPDiff Equations

The main objective of this paper is to develop a general method of geometric discretization for infinite-dimensional systems and apply this method to the EPDiff equation. The method described below extends one developed by Pavlov et al. for incompressible Euler fluids. Here this method is presented in a general case applicable to all, not only divergence-free, vector fields. Also, a different (pseudospectral) representation of the velocity field is used. We will apply this method to the one-dimensional EPDiff equation and present numerical results.
Digitalization of future education: analysis of risks on the way and selection of mechanisms to overcome barriers (Ukrainian experience)

The modern development of the information society has actualized transformations in the system of obtaining education, which, after the quarantine restrictions caused by the COVID-19 pandemic, have become an important trend in the development of the learning system. One of these trends has been digitalization, which in the future may change the essence of knowledge acquisition. The purpose of the article is to analyze the risks of the digitalization of education in the future, to identify ways to overcome these barriers. To write the paper and to disclose its purpose, the following methods were used: analysis, synthesis, method of comparativistic approach, system analysis, SWOT-analysis. Also, attention was paid to empirical methods of research. The results determined that the qualitative use of digital teaching methods requires changes in the paradigm of teaching, updating approaches to the formation of methods, active recourse to the tools of platforms Google Meet, Zoom, and Microsoft Teams. It was determined that the platforms are not without disadvantages in use, but their effective use contributes to digitalization. Among the difficulties are identified a lack of experience in digital learning, the inability to fully use all the tools of online platforms (usually because of paid access to many resources), the lack of stable basic access to the Internet. The conclusions recommend mechanisms to overcome difficulties in the digitalization of education, in particular the need to form national educational platforms.
Analysis of the Refined Mean-Field Approximation for the 802.11 Protocol Model

Mean-field approximation is a method to investigate the behavior of stochastic models formed by a large number of interacting objects. A new approximation was recently established, i.e., the refined mean-field approximation, and its high accuracy when the number of objects is small has been shown. In this work, we consider the model of the 802.11 protocol, which is a discrete-time model and show how the refined mean-field approximation can be adapted to this model. Our results confirm the accuracy of the refined mean-field approximation when the model with N objects is in discrete time.
Assessment of Performance of Photocatalytic Nanostructured Materials with Varied Morphology Based on Reaction Conditions

Synthesis of nanomaterials with specific morphology is an essential aspect for the optimisation of its properties and applications. The application of nanomaterials is being discussed in a wide range of areas, one of which is directly relevant to the environment through photocatalysis. To produce an effective photocatalyst for environmental applications, morphology plays an important role as it affects the surface area, interfaces, crystal facets and active sites, which ultimately affects efficiency. The method of synthesis and synthesis temperature can be the basic considerations for the evaluation of a particular nanomaterial. In this study, we have considered the aspects of morphology with a basic understanding and analyzed them in terms of nanomaterial efficacy in photocatalysis. Different morphologies of specific nanomaterials such as titanium dioxide, zinc oxide, silver phosphate, cadmium sulphide and zinc titanate have been discussed to come to reasonable conclusions. Morphologies such as nanorods, nanoflower, nanospindles, nanosheets, nanospheres and nanoparticles were compared within and outside the domain of given nanomaterials. The different synthesis strategies adopted for a specific morphology have been compared with the photocatalytic performance. It has been observed that nanomaterials with similar band gaps show different performances, which can be linked with the reaction conditions and their nanomorphology as well. Materials with similar morphological structures show different photocatalytic performances. TiO2 nanorods appear to have the best features of efficient photocatalyst, while the nanoflowers show very low efficiency. For CdS, the nanoflower is the best morphology for photocatalysis. It appears that high surface area is the key apart from the morphology, which controls the efficiency. The overall understanding by analyzing all the available information has enumerated a path to select an effective photocatalyst amongst the several nanomaterials available. Such an analysis and comparison is unique and has provided a handle to select the effective morphology of nanomaterials for photocatalytic applications.