Bilayer graphene under pressure: Electron-hole Symmetry Breaking, Valley Hall Effect, and Landau Levels

The electronic structure of bilayer graphene under pressure develops very interesting features with an enhancement of the trigonal warping and a splitting of the parabolic touching bands at the K point of the reciprocal space into four Dirac cones, one at K and three along the T symmetry lines. As pressure is increased, these cones separate in reciprocal space and in energy, breaking the electron-hole symmetry. Due to their energy separation, their opposite Berry curvature can be observed in valley Hall effect experiments and in the structure of the Landau levels. Based on the electronic structure obtained by Density Functional Theory, we develop a low energy Hamiltonian that describes the effects of pressure on measurable quantities such as the Hall conductivity and the Landau levels of the system.Comment: 11 pages, 9 figure

Cumplimiento y obligatoriedad de las Sentencias de la Corte Interamericana de Derechos Humanos

65 p.El presente trabajo tiene por objeto entregar una comprensión acabada de las razones por las cuales Chile, como República Democrática, se ve obligado al cumplimiento efectivo de las resoluciones de la Corte Interamericana de Derechos Humanos, no pudiendo excusar su responsabilidad en la inexistencia de norma interna expresa que contemple su ejecución, pero si de todas maneras el Estado incumple, entendemos que el particular puede intentar otras vías, administrativas o jurisdiccionales, para obtener su ejecución, todo ello considerando las normas contenidas en nuestra Carta Fundamental, incluyendo las recientes modificaciones en atención a los tratados internacionales suscritos por Chile y que se encuentran vigentes, su interacción con el principio de Supremacía Constitucional, la legislación vigente y las normas convencionales internacionales

Mental Models and the Acquisition of a Complex Skill across Individuals and Teams: A Multilevel Study

A mental model reflects the structural relationships between concepts within a specified knowledge domain. Measuring the structure of knowledge is important because it offers the possibility of capturing expert knowledge which is often difficult to assess using traditional declarative knowledge measures. The concept of mental model has been extensively studied over the last decades and it is often acknowledged in the training literature as one of the key antecedents of performance in complex tasks, particularly in the context of teams where the construct of shared mental models has received ample attention. Whereas the training literature has established the validity of mental models for predicting individual and team performance using single-level studies, the extant literature has not yet tested the validity of mental models as a multilevel construct. Consequently, the purpose of the present study was to assess the extent to which the relationships between mental models and performance generalizes across individuals and teams, that is to test a homologous multilevel model. Participants in this study completed a dynamic, networked computer-based simulation. Three-person teams operated the simulator collectively (through specialized roles) and as individuals (performing all roles simultaneously) over the course of a 2-day 48-hour-interval protocol. The sample consisted of 243 individuals nested in 81 3-person teams. Consistent with the multilevel nature of the problem under study, multilevel analyses were conducted to test the study hypotheses. Consistent with theory and previous research on individual and team cognition, it was hypothesized that stronger relationships between mental models and performance would exist at the individual level compared to the team level. In essence, processes occurring at the team level were expected to attenuate the relationship between mental models and performance compared to the individual level of analysis. Contrary to this expectation, the magnitude of the relationship between mental models and performance was similar across levels of analysis. Additionally, consistent with previous research on the effectiveness of declarative knowledge measures for predicting complex performance, the present results indicated that declarative knowledge was more predictive of individual performance than team performance. In addition to performance, an objective measure of behaviors was utilized to further understand of the processes through which mental models translate into effective individual and team performance. It was hypothesized that the relationship between mental models and behaviors would be stronger for individual tasks than team tasks as a function of the additional interaction requirements associated with team tasks. However, contrary to this expectations, mental models and behaviors were more strongly associated at the team level than the individual level

Implementacion de la norma ISO 14001:1996 en una planta manufacturera de Madera

153 p.La Memoria de Título “Implementación de la norma ISO 14001:1996 en una planta manufacturera de madera”, corresponde a un trabajo realizado en la planta Maderas Prosperidad S.A., ubicada en la ciudad de Talca, VII región de Maule. El proceso de implementación de la norma en la Empresa, se inició en mayo de 2003, finalizando en noviembre de 2004, con la recomendación para la certificación por parte de la empresa certificadora de origen noruego DNV. Durante el proceso de certificación se implementó un modelo de sistema degestión ambiental, que cuenta con cinco puntos principales: política ambiental;planificación; implementación y operación; verificación y acción correctiva/preventiva; y revisión gerencial. En lo que corresponde a planificación, se desarrolló la metodología utilizada por la empresa para identificar y evaluar sus impactos ambientales. Se identificaron 1820 aspectos ambientales, de los cuales 182 de ellos, resultaron significativos.Finalmente, se efectuó una descripción del estado actual de la ISO 14001:1996 en las empresas forestales chilenas, obteniéndose como resultado que 36 de ellas se han certificado ambientalmente

InSAR-Based Early Warning Monitoring Framework to Assess Aquifer Deterioration

Aquifer surveillance is key to understanding the dynamics of groundwater reservoirs. Attention should be focused on developing strategies to monitor and mitigate the adverse consequences of overexploitation. In this context, ground surface deformation monitoring allows us to estimate the spatial and temporal distribution of groundwater levels, determine the recharge times of the aquifers, and calibrate the hydrological models. This study proposes a methodology for implementing advanced multitemporal differential interferometry (InSAR) techniques for water withdrawal surveillance and early warning assessment. For this, large open-access images were used, a total of 145 SAR images from the Sentinel 1 C-band satellite provided by the Copernicus mission of the European Space Agency. InSAR processing was carried out with an algorithm based on parallel computing technology implemented in cloud infrastructure, optimizing complex workflows and processing times. The surveillance period records 6-years of satellite observation from September 2016 to December 2021 over the city of Chillan (Chile), an area exposed to urban development and intensive agriculture, where ~80 wells are located. The groundwater flow path spans from the Andes Mountain range to the Pacific Ocean, crossing the Itata river basin in the Chilean central valley. InSAR validation measurements were carried out by comparing the results with the values of continuous GNSS stations available in the area of interest. The performance analysis is based on spatial analysis, time series, meteorological stations data, and static level measurements, as well as hydrogeological structure. The results indicate seasonal variations in winter and summer, which corresponds to the recovery and drawdown periods with velocities > −10 mm/year, and an aquifer deterioration trend of up to 60 mm registered in the satellite SAR observation period. Our results show an efficient tool to monitor aquifer conditions, including irreversible consolidation and storage capacity loss, allowing timely decision making to avoid harmful exploitation

Assessment of Driving Mental Models as a Predictor of Crashes and Moving Violations

The purpose of the current study was to assess the efficacy of mental models as a predictor of driving outcomes. In contrast to more traditional measures of knowledge, mental models capture the configural property of knowledge, that is, an individual's understanding of the interrelationships that exist among critical concepts within a particular knowledge domain. Given that research has consistently shown the usefulness of mental models for the prediction of performance in a number of settings, it was hypothesized that the development of accurate driving mental models would also play an important role in the prediction of driving outcomes, especially in comparison to traditional measures of driving knowledge—such as the multiple-choice type tests typically required to obtain a driver license. Mental models of 130 college students (52 percent females) between 17 and 21 years-old (M = 18.68, SD = 0.80) were analyzed and compared to a subject matter expert (SME) referent structure using Pathfinder. A statistically significant correlation was found for mental model accuracy and moving violations (r = –.18, p <.05), but not for at-fault crashes. Evidence of incremental validity of mental models over commonly used predictors of moving violations (but not for at-fault crashes) was also found. Exploratory analyses revealed that driving knowledge, general mental ability (GMA), and emotional stability were the best predictors of mental model accuracy. Issues related to the measurement of mental models were extensively addressed. First, statistically significant correlations between GMA and several mental model properties (i.e., accuracy scores, within participant similarity, and within participant correlation) suggest that challenges inherent to the task for eliciting mental models may influence mental model scores which, in turn, may lower mental model reliability estimates. Also, the selection of model components (i.e., terms) and the identification of the "best" reference structure for deriving mental model accuracy scores are undoubtedly critical aspects of mental model-related research. Along with illustrating the decisions made in the context of this particular study, some suggestions for conducting mental model-related research are provided

An International Perspective on Changes in Work Due to COVID-19

The very nature and format of work, along with its social and psychological dynamics, the labor market, and economic conditions within which it is embedded have undergone a large change in the months since COVID-19 was declared a global pandemic (Kniffin et al., 2020; Rudolph et al., 2021). No country has been spared the spread of disease and nowhere are workers free from the impact and aftermath of COVID-19. Industrial and organizational psychology (I-O) faculty and practitioners have been keenly observing, tracking, and studying the changing nature of work, but few have been doing so from a cross-cultural and international lens. Given the global nature of the pandemic, here we take a deliberate global, international perspective to understanding the disruption and opportunities for the world of work. An international perspective is imperative to developing a complete and holistic understanding of (a) work psychology in the face of pandemics, (b) the consequent challenges faced by workers and organizations, (c) the future of work post-COVID-19, and (d) how I-O can meaningfully contribute to ease work-oriented disruptions and better prepare for similar future challenges. We apply a cross-cultural and international lens to focus on four areas where scholarship and practice in I-O could help in matters related to employment and the workplace: (a) informal workers, workers in poverty, and precarious work around the world; (b) technology, human resources; (HR) practices, and the digital divide; (c) the intersection of culture, work, health, and well-being; and (d) learning from crises and crisis management during a global pandemic