Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic Review on Leadership Styles in Small and Medium-Sized Enterprises

Objective - The purpose of this paper is to conduct a systematic review of the leadership style practiced by leaders in small and medium-sized enterprises. Methodology/Technique - Following the protocol guidance known as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart, a total of six articles were reviewed and analysed after meeting inclusion criteria and being deemed relevant to the goals of this paper. Findings - The results of the study suggested that the leadership styles of leaders in the context of small and medium enterprises are based on the following elements: 1) the background of an organization; 2) the characteristics of the leader; 3) the relationship between leader and followers; and 4) the position of the followers. Novelty - This paper contributes to the knowledge on leadership style in general, specifically in the context of small and medium-sized enterprises. Type of Paper - Review. Keywords: Leader; leadership style; PRISMA; small and medium-sized enterprises; systematic literature review. JEL Classification: L20, L29.
Increasing the Sustainability of Ecological Food Signaling: Are Sustainability Tags More Valuable than Eco-Labels and Other Salient Attributes?

The effectiveness of eco-labels has dominated research on ecological food signaling. Building on signaling theory, we investigate the impact of sustainability tags (i.e., unverified sustainability claims) compared to eco-labels (i.e., actual awarded eco-certificates) on consumers’ choices and willingness to pay (WTP). We add to the underdeveloped “non eco-labels” literature on sustainability signaling by documenting that a green sustainability tag had a higher importance score and utility compared to an eco-label. The tag led to larger “green segments” valuing sustainability as the most important attribute when buying salmon fillets. Furthermore, consumers were willing to pay 23.1% more for fillets with sustainability tags. This was significantly higher than the additional value ascribed to fillets with MSC eco-labels. This increase in WTP was mediated by perceived familiarity, where tags were rated higher in familiarity compared to eco-labels. The majority of consumers were unfamiliar with frequently used seafood eco-labels (ASC/MSC).
Simultaneous Determination of Seven Bisphenol Analogues in Surface Water by Solid-Phase Extraction and Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry

For the simultaneous measurement of seven types of bisphenol analogues (BPs) in surface water, a method combining solid-phase extraction (SPE) with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was developed. The extraction efficiency was improved by optimizing the parameters that affect it, including the solid phase extraction cartridge, pH, enrichment factor, flow rate, rinsing and elution volumes. On the basis of a single factor experiment, an attempt to obtain the result of optimizing by response surface method was made, and the optimal parameters were as follows: at a flow rate of 8 mL/min, 1000 mL of water sample was run through the hydrophilic-lipophilic balancing cartridge, rinsed with 10% methanol, eluted with 9 mL methanol, and concentrated with nitrogen using an automatic solid-phase extraction system. The analytes were separated on an Acquity UPLC BEH C18 column using gradient elution with a mobile phase of acetonitrile and 0.05% (v/v) ammonia, and then analyzed using UPLC-MS/MS using multiple reaction monitoring in the negative-ion mode, with an 8-minute chromatographic run time. In the range of 1-500 μg/L, seven BPs showed good linearity with correlations greater than 0.99. The recovery ranged from 82.3%-96.7%, and the range of matrix effect was 89.2% to 107%. These results indicated excellent recovery and minimal matrix effect. The limits of detection were 0.025-1.5 ng/L, the relative standard deviation ranged were 2.9%-8.5%. Using the developed method, five BPs were detected in Luoma Lake and four BPs were detected in inflow rivers. BPA and BPF were the predominant BPs, and the concentration of BPA was the highest. The method was proved to be sensitive, accurate and efficient, and it was suitable for qualitative and quantitative analysis of seven BPs in surface water.
Platform Oligopoly with Endogenous Homing: Implications for Free Entry and Mergers

Consumer multi-homing is considered to be critical for competition policy regarding digital platforms. To assess the role of consumer multi-homing in competition policy toward platforms, we develop a new framework that embeds consumer multi-homing in two-sided market into the otherwise standard model of Cournot oligopoly and apply it to free entry and mergers. We find that the equilibrium level of platform entry is insufficient given the presence of consumer multi-homing, and a required level of merger-specific cost reduction is larger if the fraction of multi-homing consumers is larger. These results together provide a caution to the popular belief that multi-homing mitigates the need for a strict implementation of competition policy.
Avaliação da toxicidade de solventes e surfactante sobre os estágios imaturos de Rhipicephalus sanguineus e Amblyomma cajennense (Acari: Ixodidae) e estudos preliminares sobre ectoparasitos de aves silvestres de fragmentos de Mata Atlântica da Zona da Mata de Minas Gerais

O presente estudo objetivou avaliar a toxicidade de diferentes solventes e do Tween 80 sobre os estagios imaturos de Rhipicephalus sanguineus e sobre larvas e ninfas ingurgitadas e ninfas nao ingurgitadas de Amblyomma cajennense. Para larvas nao ingurgitadas de R. sanguineus foi utilizado o teste de pacote de larvas modificado e a mortalidade foi avaliada apos 24 horas. O mesmo teste foi adaptado para a realizacao do experimento com ninfas nao ingurgitadas das duas especies e nesses dois experimentos foram testados os solventes etanol, metanol e acetona puros e dimetilsufoxido e tween 80 na concentracao de 50μl/ml. Em relacao aos testes com larvas e ninfas ingurgitadas foi utilizada a metodologia de imersao e a mortalidade foi avaliada apos 15 dias. Os solventes etanol, metanol e acetona foram testados nas concentracoes de 50, 250, 500, 750 e 1000 μl/ml, enquanto que o solvente dimetilsufoxido e o surfactante Tween foram testados somente a 50μl/ml, no entanto, para A.cajennense o surfactante foi acrescido com a concentracao de 25μl/ml para os estagios ingurgitados. Para cada teste foi feito um controle com agua destilada. Foram feitas dez repeticoes por tratamento e os grupos experimentais foram mantidos em câmara climatizada (27±1°C e UR>80±10%). Para R. sanguineus a acetona se mostrou toxica nos estagios ingurgitados na maior concentracao, o etanol e metanol foram toxicos na maior concentracao apenas para larvas ingurgitadas; para as larvas ingurgitadas de A. cajennense o etanol, metanol e a acetona forma toxicos na maior concentracao e o Tween matou 52 e 80% das larvas para as concentracoes de 25 e 50μl/ml respectivamente, ja para ninfas ingurgitadas o metanol matou 17,4 e a acetona 100% quando testados em qualidade pura, as ninfas nao ingurgitadas nao demonstraram sensibilidade aos solventes testados. Quanto a observacao preliminar sobre a presenca de ectoparasitos em aves silvestres, foram examinadas 58 aves de 5 familias com prevalencia de 15,5% de ectoparasitos.
Non-Fundamental Volatility in Financial Markets

I use coarse Bayesian updating to explain three stylized facts: trading anomalies around major stock market milestones, excess price volatility and trade volume, and heavy-tailed prices. When expectations are coarse and traders are heterogeneous, traders make heterogeneous expectation errors. This disagreement generates substantial trade volume and I show that the ensuing price discovery process converges in distribution to an empirically relevant class of Levy processes. Notably, I obtain this result without any exogenous shocks or processes; the only exogenous random variable is a heterogeneity parameter drawn at time zero. I then establish a perfectly non-revealing equilibrium: because traders are different, their aggregated trades generate volatile prices, yet this price process impedes traders from learning their differences.
The prebiotic and protective effects of buckwheat flour and oat bran on Lactobacillus acidophilus

During conservation, the probiotic bacteria currently used in food industry have been shown to have less viability in the matter of fermented products microbiota and also to present lower levels of colonization and survival in vivo. This study describes a new way of improving the behavior and functionality of Lactobacillus acidophilus LA 5® commercial strain by using buckwheat flour (Fagopyrum esculentum) and oat bran (Avena sativa) as fermentation ingredients, in view of their high content of bioactive compounds that have a great impact both on fermentation microorganisms and consumers’ health. The effect of these two raw vegetal products on LA 5® strain was studied by cultivation on MRS broth and on milk. The supplementation of the fermentation medium with 4.0% 6.0% of buckwheat flour or oat bran, respectively, had a positive effect on metabolic activity and viability of lactic acid bacteria. Thus, the rapid decrease of the pH and the increase of the multiplication rate were observed after 6 hours of lactic acid fermentation. Furthermore, the presence of the vegetal substrates substantially improved the cells survival during the storage of the fermented products for 28 days at 4 °C, comparing to samples without supplementation used as control.
Few-Shot Attribute Learning

Semantic concepts are frequently deﬁned by combinations of underlying attributes. As mappings from attributes to classes are often simple, attribute-based representations facilitate novel concept learning with zero or few examples. A signiﬁcant limitation of existing attribute-based learning paradigms, such as zero-shot learning, is that the attributes are assumed to be known and ﬁxed. In this work we study the rapid learning of attributes that were not previously labeled. Compared to standard few-shot learning of semantic classes, in which novel classes may be deﬁned by attributes that were relevant at training time, learning new attributes imposes a stiffer challenge. We found that supervised learning with training attributes does not generalize well to new test attributes, whereas self-supervised pre-training brings signiﬁcant improvement. We further experimented with random splits of the attribute space and found that predictability of test attributes provides an informative estimate of a model’s generalization ability.
Continuum reverberation mapping and a new lag-luminosity relationship for AGN

High cadence, high quality observations of active galactic nuclei (AGN) clearly show continuum variations with lags, relative to the shortest observed variable UV continuum, that increase with wavelength (“lag spectra”). These have been attributed to the irradiation and heating of the central accretion disk by the central X-ray emitting corona. An alternative explanation, connecting the observed lag-spectra to line and continuum emission from gas in the broad line region (BLR), has also been proposed. In this paper I show the clear spectral signature of the time-dependent diffuse gas emission in the lag-spectrum of 6 AGN. I also show a new lag-luminosity relationship for 9 objects which is a scaled down version of the well known τ(Hβ)-L5100 relationship in AGN. The shape of the lag-spectrum, and its normalization, are entirely consisted with diffuse emission from radiation pressure supported clouds in a BLR with a covering factor of about 0.2. While some contributions to the continuum lag from the irradiated disk cannot be excluded, there is no need for this explanation.
Weighing the Darkness. II. Astrometric Measurement of Partial Orbits with Gaia

Over the course of several years, stars trace helical trajectories as they traverse across the sky due to the combined effects of proper motion and parallax. It is well known that the gravitational pull of an unseen companion can cause deviations to these tracks. Several studies have pointed out that the astrometric mission Gaia will be able to identify a slew of new exoplanets, stellar binaries, and compact object companions with orbital periods as short as tens of days to as long as Gaia's lifetime. Here, we use mock astrometric observations to demonstrate that Gaia can identify and characterize black hole companions to luminous stars with orbital periods longer than Gaia's lifetime. Such astrometric binaries have orbital periods too long to exhibit complete orbits, and instead are identified through curvature in their characteristic helical paths. By simultaneously measuring the radius of this curvature and the orbital velocity, constraints can be placed on the underlying orbit. We quantify the precision with which Gaia can measure orbital accelerations and apply that to model predictions for the population of black holes orbiting stars in the stellar neighborhood. Although orbital degeneracies imply that many of the accelerations induced by hidden black holes could also be explained by faint low-mass stars, we discuss how the nature of certain putative black hole companions can be confirmed with high confidence using Gaia data alone.
Information Theoretic Structured Generative Modeling

R\'enyi's information provides a theoretical foundation for tractable and data-efficient non-parametric density estimation, based on pair-wise evaluations in a reproducing kernel Hilbert space (RKHS). This paper extends this framework to parametric probabilistic modeling, motivated by the fact that R\'enyi's information can be estimated in closed-form for Gaussian mixtures. Based on this special connection, a novel generative model framework called the structured generative model (SGM) is proposed that makes straightforward optimization possible, because costs are scale-invariant, avoiding high gradient variance while imposing less restrictions on absolute continuity, which is a huge advantage in parametric information theoretic optimization. The implementation employs a single neural network driven by an orthonormal input appended to a single white noise source adapted to learn an infinite Gaussian mixture model (IMoG), which provides an empirically tractable model distribution in low dimensions. To train SGM, we provide three novel variational cost functions, based on R\'enyi's second-order entropy and divergence, to implement minimization of cross-entropy, minimization of variational representations of $f$-divergence, and maximization of the evidence lower bound (conditional probability). We test the framework for estimation of mutual information and compare the results with the mutual information neural estimation (MINE), for density estimation, for conditional probability estimation in Markov models as well as for training adversarial networks. Our preliminary results show that SGM significantly improves MINE estimation in terms of data efficiency and variance, conventional and variational Gaussian mixture models, as well as the performance of generative adversarial networks.
Nickel doped copper oxide thin films prepared by radiofrequency reactive sputtering: study of the impact of nickel content on the structural, optical and electrical properties

Abstract Nickel doped copper oxide thin films were grown on glass and silicon substrates using radiofrequency sputtering in an argon–oxygen atmosphere. The impact of doping on the structural, optical, and electrical properties of copper oxide was examined for various contents of nickel. The X-ray diffraction results revealed the polycrystalline monoclinic structure of copper oxide for the prepared films. Raman spectroscopy confirmed that only the copper oxide phase is evidenced in nickel-doped copper oxide films. The band gap energy increased with increasing nickel content. All the sputtered films showed p-type conduction and the resistivity depends on the nickel content.
vocadito: A dataset of solo vocals with f0, note, and lyric annotations

To compliment the existing set of datasets, we present a small dataset entitled vocadito, consisting of 40 short excerpts of monophonic singing, sung in 7 different languages by singers with varying of levels of training, and recorded on a variety of devices. We provide several types of annotations, including $f_0$, lyrics, and two different note annotations. All annotations were created by musicians. We provide an analysis of the differences between the two note annotations, and see that the agreement level is low, which has implications for evaluating vocal note estimation algorithms. We also analyze the relation between the $f_0$ and note annotations, and show that quantizing $f_0$ values in frequency does not provide a reasonable note estimate, reinforcing the difficulty of the note estimation task for singing voice. Finally, we provide baseline results from recent algorithms on vocadito for note and $f_0$ transcription. Vocadito is made freely available for public use.
Luminous Millimeter, Radio, and X-Ray Emission from ZTF 20acigmel (AT 2020xnd)

Observations of the extragalactic (z = 0.0141) transient AT 2018cow established a new class of energetic explosions shocking a dense medium, producing luminous emission at millimeter and submillimeter wavelengths. Here we present detailed millimeter- through centimeter-wave observations of a similar transient, ZTF 20acigmel (AT 2020xnd), at z = 0.2433. Using observations from the NOrthern Extended Millimeter Array and the Very Large Array, we model the unusual millimeter and radio emission from AT 2020xnd under several different assumptions and ultimately favor synchrotron radiation from a thermal electron population (relativistic Maxwellian). The thermal electron model implies a fast but subrelativistic (v ≈ 0.3c) shock and a high ambient density (n e ≈ 4 × 103 cm−3) at Δt ≈ 40 days. The X-ray luminosity of L X ≈ 1043 erg s−1 exceeds simple predictions from the radio and UVOIR luminosity and likely has a separate physical origin, such as a central engine. Using the fact that month-long luminous (L ν ≈ 2 × 1030 erg s−1 Hz−1 at 100 GHz) millimeter emission appears to be a generic feature of transients with fast (t 1/2 ≈ 3 days) and luminous (M peak ≈ −21 mag) optical light curves, we estimate the rate at which transients like AT 2018cow and AT 2020xnd will be detected by future wide-field millimeter transient surveys such as CMB-S4 and conclude that energetic explosions in dense environments may represent a significant population of extragalactic transients in the 100 GHz sky.
Towards a Principled Approach for Dynamic Analysis of Android's Middleware

The Android middleware, in particular the so-called systemserver, is a crucial and central component to Android's security and robustness. To understand whether the systemserver provides the demanded security properties, it has to be thoroughly tested and analyzed. A dedicated line of research focuses exclusively on this task. While static analysis builds on established tools, dynamic testing approaches lack a common foundation, which prevents the community from comparing, reproducing, or even re-using existing results from related work. This raises questions about whether the underlying approach of any proposed solution is the only possible or optimal one, if it can be re-used as a building block for future analyses, or whether results generalize. In this work, we argue that in order to steer away from incompatible custom toolchains and towards having comparable analyses with reproducible results, a more principled approach to dynamically analyzing the Android system is required. As an important first step in this direction, we propose a unified dynamic analysis platform that provides re-usable solutions for common challenges as the building blocks for future analyses and allows to compare different approaches under the same assumptions.
M2GAN: A Multi-Stage Self-Attention Network for Image Rain Removal on Autonomous Vehicles

Image deraining is a new challenging problem in applications of autonomous vehicles. In a bad weather condition of heavy rainfall, raindrops, mainly hitting the vehicle's windshield, can significantly reduce observation ability even though the windshield wipers might be able to remove part of it. Moreover, rain flows spreading over the windshield can yield the physical effect of refraction, which seriously impede the sightline or undermine the machine learning system equipped in the vehicle. In this paper, we propose a new multi-stage multi-task recurrent generative adversarial network (M2GAN) to deal with challenging problems of raindrops hitting the car's windshield. This method is also applicable for removing raindrops appearing on a glass window or lens. M2GAN is a multi-stage multi-task generative adversarial network that can utilize prior high-level information, such as semantic segmentation, to boost deraining performance. To demonstrate M2GAN, we introduce the first real-world dataset for rain removal on autonomous vehicles. The experimental results show that our proposed method is superior to other state-of-the-art approaches of deraining raindrops in respect of quantitative metrics and visual quality. M2GAN is considered the first method to deal with challenging problems of real-world rains under unconstrained environments such as autonomous vehicles.
Quasiprobabilities of work and heat in an open quantum system

We discuss an approach to determine averages of the work, dissipated heat and variation of internal energy of an open quantum system driven by an external classical field. These quantities are measured by coupling the quantum system to a quantum detector at different times. This approach allows us to preserve the full quantum features of the evolution. From the measured phase, we are able to obtain a quasi-characteristic function and a quasi-probability density function for the corresponding observables. Despite the fact that these quasiprobability density functions are not the results of direct measurements, they reproduce the expected value of the physical quantities. Analogously to the Wigner function, the negative regions of these quasi-probability density functions are directly related to pure quantum processes which are not interpretable in classical terms. We use this feature to show that in the limit of strong dissipation, the quantum features vanish and interpret this as the emergence of the classical limit of the energy exchange process. Our analysis explains and confirms the behavior observed in recent experiments performed on IBMQ devices [1]. The possibility to discriminate between classical and quantum features makes the proposed approach an excellent tool to determine if, and in which conditions, quantum effects can be exploited to increase the efficiency in an energy exchange process at the quantum level.