Miracle-dz/UniFAR-FTUs huggingface dataset:
The Successfully Reposition of a Beer Brand Applying Strategic Planning and Transmedia Communication: The Case of Estrella Damm

In the last decade, the Spanish beer market has undergone significant changes. Within this market, the traditional brand Estrella Damm had to simultaneously combat adverse commercial and social trends. Following an in-depth marketing and strategy reflection, the brand achieved a new and improved positioning. Simultaneously, it made the leap to social network communication, generating a considerable volume of downloads and conversations while drastically reducing its investment in conventional media. It also made product consumption highly seasonal linking it to the summer period and launched highly visible and creative communication actions aimed at young audiences. Estrella Damm is an outstanding example of strategic planning and social networks communication techniques. For the purpose of this study, this research applies case study techniques, content analysis of selected representative pieces, and online actions monitoring. It also analyses the market, the brand evolution, and the economic situation of the company through the use of existing scientific and professional literature.
Random walks in random environments of a general type

A notion of (multidimensional) random walk in random environment of functional type is introduced in a semimartingale form. Some estimates (useful for limit theorems) are presented. The inverse problem-the estimation of the parameters of environments given the trajectories of random walks is discussed. A limit theorem for the case of functionally-depending random environment is proved.
Categorical Causal Modeling

Latent class analysis (LCA) is an extremely useful and flexible technique for the analysis of categorical data, measured at the nominal, ordinal, or interval level (the latter with fixed or estimated scores). It is, first, a general measurement model, a particular kind of latent structure model that can be used for the investigation of the reliability and validity of categorical measurements, taking both random and systematic response errors into account. When dealing with test-retest effects, response consistency effects, unobserved heterogeneity, response effects from varying survey (interviewing) conditions, and so on, it is useful to take a consistent causal modeling point of view and to integrate LCA into a general causal log-linear model with latent variables. The resulting directed log-linear modeling approach integrates insights from Goodman's modified path approach, the modified LISREL approach, and directed graphical modeling.
A Buckycatcher in Solution—A Computational Perspective

In this work, we study the buckycatcher (C60H28) in solution using quantum chemical models. We investigate the conformational equilibria in several media and the effects that molecules of solvent might have in interconversion barriers between the different conformers. These are studied in a hypothetical gas phase, in the dielectric of a solvent, as well as with hybrid solvation. In the latter case, due to a disruption of π-stacking interactions, the transition states are destabilized. We also evaluate the complexation of the buckycatcher with solvent-like molecules. In most cases studied, there should be no adducts formed because the enthalpy driving force cannot overcome entropic penalties.
Validation of Doi’s weighted average glucose as a measure of post-load glucose excursion for clinical use

In this study, we examined the performance of a novel index of glucose excursion (Doi’s weighted average glucose [dwAG]) in relation to the conventional measure of area under the oral glucose tolerance test (A-GTT) and the homeostatic model assessment for insulin sensitivity (HOMA-S) and pancreatic beta cell function (HOMA-B). A cross-sectional comparison of the new index was conducted using 66 oral glucose tolerance tests (GTTs) performed at different follow-up times among 27 participants who had undergone surgical subcutaneous fat removal (SSFR). Comparisons across categories were made using box plots and the Kruskal–Wallis one-way ANOVA on ranks. Passing-Bablok regression was used to compare the dwAG against the conventional A-GTT. The Passing-Bablok regression model suggested a cutoff for normality for the A-GTT of 15.14 mmol/L⋅2h−1 compared to the dwAG’s suggested threshold of 6.8 mmol/L. For every 1 mmol/L⋅2h−1 increase in A-GTT, the dwAG value increased by 0.473 mmol/L. The glucose area under the curve correlated well with the four defined dwAG categories, with at least one of the categories having a different median A-GTT value (KW Chi2 ═ 52.8 [df ═ 3], P < 0.001). The HOMA-S tertiles were also associated with significantly different levels of glucose excursion measured through both the dwAG value (KW Chi2 ═ 11.4 [df ═ 2], P ═ 0.003) and A-GTT measure (KW Chi2 ═ 13.1 [df ═ 2], P ═ 0.001). It is concluded that the dwAG value and categories serve as a simple and accurate tool that can be used for interpreting glucose homeostasis across clinical settings.
Understanding the Role of Atmospheric Rivers in Heavy Precipitation in the Southeast United States

AbstractAn analysis of atmospheric rivers (ARs) as defined by an automated AR detection tool based on integrated water vapor transport (IVT) and the connection to heavy precipitation in the southeast United States (SEUS) is performed. Climatological water vapor and water vapor transport fields are compared between the U.S. West Coast (WCUS) and the SEUS, highlighting stronger seasonal variation in integrated water vapor in the SEUS and stronger seasonal variation in IVT in the WCUS. The climatological analysis suggests that IVT values above ~500 kg m−1 s−1 (as incorporated into an objective identification tool such as the AR detection tool used here) may serve as a sensible threshold for defining ARs in the SEUS.Atmospheric river impacts on heavy precipitation in the SEUS are shown to vary on an annual cycle, and a connection between ARs and heavy precipitation during the nonsummer months is demonstrated. When identified ARs are matched to heavy precipitation days (>100 mm day−1), an average match rate of.
Determinism and noise in surface temperature time series

The extent to which surface temperature data can be deterministic is investigated on a time series of hourly temperatures recorded at the National Observatory of Athens, Greece, over a period of 7 years (1984-1990). Using the Grassberger-Procaccia method, we measure, for the full time series, a correlation dimension ν≃3.8, and a positive largest Liapounov exponent. Our series passes also a number of other tests, proposed in the resent literature, for low-dimensional chaos, yet shows evidence of fractral noise in the high-frequency part of its power spectrum. This is explained by showing that our data fails to pass the test of time-differencing, in which the series {ΔT(t i )=T(t i )−T(t i−1 )} is clearly seen to behave like random noise. Theiler's test of time separation also shows that the low-dimensional, deterministic features of our series {T(t i )} may be due to temporal (rather than spatial) correlations. Still, the presence and significance of these deterministic features is supported by singular value decomposition (SVD) analysis and successful prediction results
Bilateral index, power, force, and velocity during bench press with different loads in male handball players

Bilateral index for upper limbs was determined for maximal force, speed and power in 18 male handball players. Variables were individually assessed with a functional electromechanical dynamometer during unilateral and bilateral bench press push-off for 40%, 60%, and 75% of the maximal isometric force. Limb dominance (symmetry indices) and load effects in the bilateral index were analysed. Bilateral index showed a bilateral deficit for power (range = −8.50 to −41.48) and velocity (range = −11.15 to −38.41), that increases with the load (p < 0.05). For maximum force, a bilateral facilitation (range = 2.26–5.57), which did not vary significantly as a function of load, was observed. Symmetry indices showed no association with the bilateral index (40% load: r = 0.45, 60% load: r = 0.05, 75% load: r = 0.39). These results contribute to understanding the phenomenon; however, individual-to-individual observation reflects that caution should be kept when assessing an individual athlete. In conclusion, bilateral deficit or facilitation for bench press depends on the variable considered, whereas its magnitude depends on the load. Moreover, limb dominance does not affect it. This finding must be regarded as a general trend, but a different situation may occur during the assessment of a particular athlete.
QAM Constellations With Fractional Entropy to Gain in Margin Maximization for Frequency Selective Channels

This letter proposes two approaches to increase the energy gain for the procedure of bit and power allocation in the frequency selective channels. The first one is the use of QAM constellations with optimal probabilistic shaping (PS) instead of the conventional QAM constellations. The second approach is the use of an extended set of QAM constellations with fractional entropy, which is named FQAM. These FQAM constellations are first offered in this work. As the channel examples, we used ADSL channel, fiber optic channel with Bessel filter, and the one with chromatic dispersion. It is shown that for the observed use cases the use of QAM with PS provides the energy gain in the range of 0.25–0.40 dB with respect to the conventional QAM constellations, while FQAM provides the gain in the range of 1.05–1.30 dB.
Prognostic Value of Pentraxin-3 Change After Primary Percutaneous Coronary Intervention in Patients with ST-Segment Elevation Myocardial Infarction

Purpose So far, ST-segment elevation myocardial infarction (STEMI) is still the main cause of morbidity and mortality of cardiovascular diseases worldwide. Recent studies showed that pentraxin-3 (PTX3) was related to the early diagnosis and prognosis of coronary heart disease. This study aimed to investigate the dynamical change of PTX3 after primary percutaneous coronary intervention (pPCI) in STEMI patients and its prognostic value. Patients and methods In this prospective cohort study, a total of 350 patients were enrolled. The plasma level of PTX3 was measured at admission, 24-hour and 5-day after pPCI. The primary endpoint was the incidence of major adverse cardiac cerebral events (MACCEs) during 1-year follow-up. Results Compared with the admission, PTX3 levels were significantly increased at 24 hours, and decreased at 5 days after pPCI in the whole cohort. PTX3 levels at these three time points were not significantly different between the patients with and without MACCEs. Notably, the change in PTX3 from admission to post-pPCI 24-hour (ΔPTX3) was higher in patients with MACCEs (112.83 vs 17.94 ng/dl, P = 0.001). The ROC curves showed that the cut-off value was 29.22 ng/dl and the area under curves was 0.622 (95% CI: 0.554–0.690, p = 0.001). Multivariable cox regression models revealed that the high ΔPTX3 group was an independent predictor of MACCEs (adjusted HR = 2.010, 95% CI = 1.280–3.186, p = 0.003). The higher ΔPTX3 group had significantly higher incidences of revascularization (HR = 2.094, 95% CI: 1.056–4.150, p = 0.034) and composite MACCEs (HR = 2.219, 95% CI: 1.425–3.454, p < 0.001). However, the change of PTX3 level from admission to post-pPCI 5-day had no independently predictive value. Conclusion The higher increase of PTX3 level 24-hour after pPCI appeared to have a potential value in independently predicting the incidence of 1-year MACCEs in STEMI patients, especially for coronary revascularization.
Modeling Group Opinion Evolution on Online Social Networks: A Gravitational Field Perspective

The research on group behavior is effective for establishing a good network environment since people in social networks tend to form groups spontaneously. Most studies on group behavior on online social networks assume that all individuals are reduced to one cluster, ignoring the existence of potential clusters and their importance in group opinion dynamics. This article introduces a novel group-gravitational field (GGF) model to investigate the opinion evolution based on group behavior by the following aspects: 1) the GGF model reduces a cluster in the social network into a charge and the whole network into a gravitational field; 2) the GGF model calculates the initial influence of a cluster according to the topology information and further constructs a gravity matrix of the network based on the Coulomb law; and 3) opinion-leader clusters exert the internal field force on common opinion clusters inside the gravitational field. The GGF model simulates the evolution of opinions among clusters in a network and studies the law of group behavior according to the influence between clusters based on Coulomb’s law. Experiments on real social networks verify that the GGF model enhances the speed of opinion evolution significantly. The simulation experiments indicate that the existence of clusters promotes the rapid convergence of opinions, a gathering of followers influences information dissemination in social networks, and the GGF model fits the reality better. This article provides a new approach to network supervision and control.
Numerical modelling of competitive components transport with non-linear adsorption

A characteristic finite element (CFE) algorithm for modelling contaminant transport problems coupled with non-linear competitive adsorption is presented. An alternative algorithm, termed as the transport-equilibrium Petrov–Galerkin (TEPG) methods in this paper, is also presented for comparison. Through analyses of a number of examples with Peclet number ranging from zero to infinity, it is shown that the CFE algorithm is very competitive with the middle–point TEPG method in terms of accuracy, stability and efficiency. The fully explicit and fully implicit TEPG methods are found to be less appropriate for transport problems coupled with non-linear equilibrium equations. Copyright © 2000 John Wiley & Sons, Ltd.
Cutting multiply connected domains

The calculation of electromagnetic fields in three dimensions using discrete finite element methods and potential formulations requires that the topological connectivity of sub-domains of the total problem space be known. There may also be a need to define cutting surfaces such that the sub-domains are simply connected or in order that integral relationships can be imposed on the solutions, methods of determining the cutting surfaces for multiply connected sub-domains are developed in this paper, based on the discrete finite element model of the system. The algorithms are completely general and have an operation count of order n, where n is the number of discrete elements in the sub-domain.
An Iterative High-Accuracy ADI Method for the 3D Parabolic Equation

The alternating direction implicit parabolic equation (ADI-PE) method and the Crank–Nicolson parabolic equation (CN-PE) method have been widely used for solving the 3D parabolic equation (3D-PE) in radio wave propagation. The ADI-PE method is more computationally efficient than the CN-PE method. The accuracy of the ADI-PE method is improved by the higher-order Mitchell–Fairweather (MF)-ADI method. This paper presents an iterative high-accuracy (IHA)-ADI method for the 3D parabolic equation. A derivation of the proposed method is presented. The convergence and stability of the proposed method are estimated. Several numerical examples are considered to illustrate the advantages of the proposed method. The results of error analysis and a comparative study show that the proposed method is unconditionally stable and computationally efficient. The proposed method is more numerically accurate than the MF-ADI method.
Analysis of magnetizing process using discharge current of capacitor by 3-D finite-element method

When permanent magnets are magnetized using the coils in the stator of a motor, it is very important to be able to estimate the residual flux distribution in the permanent magnets. Therefore, we have developed a method to calculate the residual flux distribution using the three-dimensional (3-D) finite-element method taking into account the magnetizing process that uses the discharge current of a capacitor. We have also analyzed the effects of the eddy currents in the permanent magnet during the magnetizing process on the residual flux distribution. The accuracy of the method was confirmed by a comparison between the calculated average magnetization ratios and the measured ones.
Application of machine learning: a recent advancement in plant diseases detection

The world population, and thus the need for food, is increasing every day. This leads to the ultimate question of how to increase food production with limited time and scarce land. Another obstacle to meet the food demand includes the stresses a plant goes through. These may be abiotic or biotic, but the majority are biotic, i.e., plant diseases. The major challenge is to mitigate plant diseases efficiently, more quickly and with less manpower. Recently, artificial intelligence has turned to new frontiers in smart agricultural science. One novel approach in plant science is to detect and diagnose plant disease through deep learning and hyperspectral imaging. This smart technique is very advantageous for monitoring large acres of field where the availability of manpower is a major drawback. Early identification of plant diseases can be achieved through machine learning approaches. Advanced machine learning not only detects diseases but also helps to discover gene regulatory networks and select the genomic sequence to develop resistance in crop species and to mark patho-gen effectors. In this review, new advancements in plant science through machine learning approaches have been discussed.
Morphology and properties of permafrost-affected soils under different tundra vegetation in central Spitsbergen

: The main aim of this study was to determine the morphology, physical, and chemical properties of permafrost-affected soils under different types of tundra in the central part of Spitsbergen. This is a preliminary part of detailed studies focused on the relationship between tundra vegetation and permafrost-affected soils in the Spitsbergen. The obtained results indicate that all the studied soils represent an early stage of formation and the main soil-forming process present in these soils is cryoturbation. Most of the studied soils are shallow and contain a high content of coarse rock fragments. Tundra vegetation type plays controlling role in the development and structure of surface soil horizons. All the studied soils are characterized by loamy texture and acidic or slightly acidic reaction, and these properties are not very different under various tundra vegetation types. The contents of soil organic matter are strongly dependent on the type of tundra vegetation. The highest soil organic matter content occurs at sites with well-developed vegetation such as heath and wet moss tundra. The high carbon-to-nitrogen ratio for the surface soil horizons of the majority of the studied soils indicates that organic matter is poorly decomposed under all the studied tundra vegetation types. This is most likely related to low activity of soil microorganisms in the harsh High Arctic environment. However, the lowest carbon-to-nitrogen ratio was noted for surface soil horizons at sites covered with Arctic meadow, and this indicates that there occur the optimum conditions for soil organic matter decomposition.
The association between information and communication technologies, loneliness and social connectedness: A scoping review

Older adults are at a higher risk of loneliness, compared to other demographics. The use of Internet Communication and Technologies (ICTs) among older adults is steadily increasing and given ICTs provide a means of enhancing social connectedness suggests they may have positive effects on reducing loneliness. Therefore, the aim of this scoping review was to examine the research that explores how ICTs may be implicated in mitigating loneliness and increasing social connectedness among older adults. After the examination of 54 articles, we identified three major themes within the literature: (1) ICTs were associated with a reduction in loneliness and increase in wellbeing. (2) ICTs promoted social connectedness by facilitating conversations. (3) Factors such as training, self-efficacy, self-esteem, autonomy, and the design/features, or affordances, of ICTs contribute toward the associations between ICT use and wellbeing. The heterogeneity of methodologies, statistical reporting, the small sample sizes of interventional and observational studies, and the diversity of the experimental contexts underline the challenges of quantitative research in this field and highlights the necessity of tailoring ICT interventions to the needs and contexts of the older users.
Ten More Years of Error Rate Research

The assessment of the performance of supervised classification rules by estimating their error rate (the proportion of objects misclassified) is an important area of work in statistical pattern recognition. This paper reviews the last ten years of error rate research, bringing up to date the reviews of Hand (1986a) and McLachlan (1987). Since those surveys were published, old estimators have been improved new estimators have been introduced, and new approaches to error rate estimation have been developed. Some of this work has led to deep insights into classification methodology and statistical modelling in general.
Polymorphisms in VDR, CYP27B1, CYP2R1, GC and CYP24A1 Genes as Biomarkers of Survival in Non-Small Cell Lung Cancer: A Systematic Review

The objective of this systematic review was to provide a compilation of all the literature available on the association between single-nucleotide polymorphisms (SNPs) in the genes involved in the metabolic pathway of vitamin D and overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC). This systematic review was conducted in accordance with the PRISMA guidelines. It included all the literature published up to 1 November 2022 and was carried out in four databases (Medline [PubMed], Scopus, Web of Science, and Embase), using the PICO strategy, with relevant keywords related to the objective. The quality of the studies included was evaluated with an assessment tool derived from the Strengthening the Reporting of Genetic Association Studies (STREGA) statement. Six studies were included in this systematic review. Our findings showed that the BsmI (rs1544410), Cdx-2 (rs11568820), FokI (rs2228570), ApaI (rs7975232), TaqI (rs731236), rs4646536, rs6068816, rs7041, and rs10741657 SNPs in the genes that play a part in vitamin D synthesis (CYP2R1, CYP27B1), transport (GC), and metabolism (CYP24A1), as well as in the vitamin D receptor (VDR), are associated with OS and/or PFS in patients with NSCLC. The SNPs in VDR have been the most extensively analyzed. This systematic review summed up the available evidence concerning the association between 13 SNPs in the main genes involved in the vitamin D metabolic pathway and prognosis in NSCLC. It revealed that SNPs in the VDR, CYP27B1, CYP24A1, GC, and CYP2R1 genes could have an impact on survival in this disease. These findings suggest the identification of prognostic biomarkers in NSCLC patients. However, evidence remains sparse for each of the polymorphisms examined, so these findings should be treated with caution.