Testing a dissipative kinetic k-essence model

In this work, we present a study of a purely kinetic k-essence model, characterized basically by a parameter $\alpha$ in presence of a bulk dissipative term, whose relationship between viscous pressure $\Pi$ and energy density $\rho$ of the background follows a polytropic type law $\Pi \propto \rho^{\lambda+1/2}$, where $\lambda$, in principle, is a parameter without restrictions. Analytical solutions for the energy density of the k-essence field are found in two specific cases: $\lambda=1/2$ and $\lambda=(1-\alpha)/2\alpha$, and then we show that these solutions posses the same functional form than the non-viscous counterpart. Finally, both approach are contrasted with observational data from type Ia supernova, and the most recent Hubble parameter measurements, and therefore, the best values for the parameters of the theory are founds.Comment: 9 pages, 5 figures, accepted in EPJ

Paradigmas De La Gerencia En El Siglo Xxi

El avance de la ciencia y la tecnología ha generado una nueva dinámica en la economía mundial, la cual permitió la globalización de los mercados, el cual ha incrementado la competencia y el crecimiento exagerado en la demanda de bienes y servicios.Hoy este escenario representa una realidad que no se puede ocultar y por consiguiente los gerentes deben reaccionar de manera que adopten nuevas acciones conducentes a hacer frente a nuevos retos, estos derivados de las cambiantes realidades sociales, económicas y demográficas del mercado en constante evolución.El presente documento expone algunos de los principales retos que los gerentes deben enfrentar en la dinámica de la administración del siglo XXI

Theoretical insight on the LK-99 material

Two recent preprints in physics archive (arXiv) have called the attention as they claim experimental evidence that a Cu-substituted apatite material (called LK-99) exhibits superconductivity at room temperature and pressure. If this proves to be true, LK-99 will be the holy grail of superconductors. In this work, we used Density-Functional Theory calculations to elucidate some key features of the electronic structure of LK-99. Although some aspects of our calculations are preliminary, we found that: i) in the ground state of the material the ferromagnetic and antiferromagnetic configurations are practically degenerated, ii) the material is metallic, iii) the Cu atoms seem to be hosts in the lattice with not covalent bonds to other atoms and supporting almost flat bands around the Fermi level, and iv) the electron-phonon coupling of these flat bands seems to be dramatically large

Effects of Gamma Ray Bursts in Earth Biosphere

We continue former work on the modeling of potential effects of Gamma Ray Bursts on Phanerozoic Earth. We focus on global biospheric effects of ozone depletion and show a first modeling of the spectral reduction of light by NO2 formed in the stratosphere. We also illustrate the current complexities involved in the prediction of how terrestrial ecosystems would respond to this kind of burst. We conclude that more biological field and laboratory data are needed to reach even moderate accuracy in this modelingComment: Accepted for publication in Astrophysics & Space Scienc

Examining barriers, motivations, and perceptions of women working in the tourism industry: Case study of Ayampe, Ecuador

The notion of examining gender is gaining momentum across disciplines as an important phenomenon to understand (Kincheloe & Mclaren, 2008). The tourism field is one such area that has made sizeable contributions to the literature; however there is a lack of research focusing on women and tourism in developing countries. This is an exploratory case study of a rural community in Ecuador. Using community-based research methodology and a gender and development framework, this study explores the motivations, barriers and perceptions towards women seeking employment in the tourism industry and identified disparities between the perceptions of men and women in regard to the potential for women securing employment in the industry. The themes that emerged from the data may be grouped as those indicating barriers: gender role expectations, machismo, and poor education; and as motivators: economic benefits, opportunity to learn new things, purpose in life, and education for their children

Evaluating and Explaining Large Language Models for Code Using Syntactic Structures

Large Language Models (LLMs) for code are a family of high-parameter, transformer-based neural networks pre-trained on massive datasets of both natural and programming languages. These models are rapidly being employed in commercial AI-based developer tools, such as GitHub CoPilot. However, measuring and explaining their effectiveness on programming tasks is a challenging proposition, given their size and complexity. The methods for evaluating and explaining LLMs for code are inextricably linked. That is, in order to explain a model's predictions, they must be reliably mapped to fine-grained, understandable concepts. Once this mapping is achieved, new methods for detailed model evaluations are possible. However, most current explainability techniques and evaluation benchmarks focus on model robustness or individual task performance, as opposed to interpreting model predictions. To this end, this paper introduces ASTxplainer, an explainability method specific to LLMs for code that enables both new methods for LLM evaluation and visualizations of LLM predictions that aid end-users in understanding model predictions. At its core, ASTxplainer provides an automated method for aligning token predictions with AST nodes, by extracting and aggregating normalized model logits within AST structures. To demonstrate the practical benefit of ASTxplainer, we illustrate the insights that our framework can provide by performing an empirical evaluation on 12 popular LLMs for code using a curated dataset of the most popular GitHub projects. Additionally, we perform a user study examining the usefulness of an ASTxplainer-derived visualization of model predictions aimed at enabling model users to explain predictions. The results of these studies illustrate the potential for ASTxplainer to provide insights into LLM effectiveness, and aid end-users in understanding predictions

Mapeamento de QTLs associados com a tolerância ao alumínio em milho (Zea mays L.).

xSuplemento. Edição dos resumos do 46º Congresso Nacional de Genética, Águas de Lindóia, SP, 2000

The challenge of modelling nitrogen management at the field scale : simulation and sensitivity analysis of N2O fluxes across nine experimental sites using DailyDayCent

Peer reviewedPublisher PD

Selective herbicide safening in dicot plants: a case study in <em>Arabidopsis</em>

Copyright \ua9 2024 Pingarron-Cardenas, Onkokesung, Goldberg-Cavalleri, Lange, Dittgen and Edwards.Safeners are agrochemicals co-applied with herbicides that facilitate selective control of weeds by protecting monocot crops from chemical injury through enhancing the expression of detoxifying enzymes such as glutathione transferases (GSTs). Even though the application of safeners causes the induction of genes encoding GSTs in model dicots such as Arabidopsis thaliana, safeners do not protect broadleaf crops from herbicide injury. In this study, we proposed that the localized induction of Arabidopsis GSTs and the fundamental differences in their detoxifying activity between dicot and monocot species, underpin the failure of safeners to protect Arabidopsis from herbicide toxicity. Using the herbicide safener, isoxadifen-ethyl, we showed that three tau (U) family GSTs namely AtGSTU7, AtGSTU19 and AtGSTU24 were induced with different magnitude by isoxadifen treatment in root and rosette tissues. The higher magnitude of inducibility of these AtGSTUs in the root tissues coincided with the enhanced metabolism of flufenacet, a herbicide that is active in root tissue, protecting Arabidopsis plants from chemical injury. Assay of the recombinant enzyme activities and the significant reduction in flufenacet metabolism determined in the T-DNA insertion mutant of AtGSTU7 (gstu7) in Arabidopsis plants identified an important function for AtGSTU7 protein in flufenacet detoxification. In-silico structural modeling of AtGSTU7, suggested the unique high activity of this enzyme toward flufenacet was due to a less constrained active site compared to AtGSTU19 and AtGSTU24. We demonstrate here that it is possible to induce herbicide detoxification in dicotyledonous plants by safener treatment, albeit with this activity being restricted to very specific combinations of herbicide chemistry, and the localized induction of enzymes with specific detoxifying activities