Existence and Uniqueness results for linear second-order equations in the Heisenberg group

In this manuscript, we prove uniqueness and existence results of viscosity solutions for a class of linear second-order equations in the Heisenberg group. We state uniqueness by proving a comparison result to our class of equations, and existence via an application of Perron’s method adapted to our framework. We also provide the explicit construction of the appropriate sub- and supersolutions employed by Perron’s method for a variety of domains in the Heisenberg group.Fil: Ochoa, Pablo Daniel. Universidad Nacional de Cuyo. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ruiz, Julio Alejo. Universidad Nacional de Cuyo. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

A methodology for the characterization of land use using medium-resolution spatial images

Introducción: La caracterización de los usos del suelo representa uno de los insumos indispensables para el manejo de los recursos naturales a diferentes escalas. Objetivo: Desarrollar una metodología para caracterizar el uso del suelo en la cuenca superior del arroyo del Azul (Buenos Aires, Argentina), a través de la fusión de imágenes satelitales de media resolución espacial. Materiales y métodos: Se utilizó una serie temporal de 23 imágenes del índice de vegetación de diferencia normalizada (NDVI, por sus siglas en inglés) del satélite MODIS-Terra (producto MOD13Q1) para el periodo mayo 2015 - mayo 2016. Además, se emplearon imágenes Landsat 8 para discriminar algunas categorías difíciles de clasificar con NDVI-MODIS. El mapa final de coberturas se validó considerando puntos de verificación independientes al proceso de clasificación; su precisión se evaluó a través del estadístico Kappa. Resultados y discusión: La serie temporal de NDVI permitió reconocer los patrones fenológicos de las coberturas y usos del suelo de mayor representatividad en la región. Se discriminaron siete coberturas; los usos agrícolas representaron 81.5 % de la superficie, siendo el sistema de doble cultivo trigo-soya (soja en Argentina) el predominante (39.4 %). La precisión global del mapa final fue alta (88.9 %, coeficiente Kappa = 0.86). Conclusión: La metodología empleada tiene la ventaja de ser rápida y replicable, para caracterizar los usos del suelo de una región determinada y evaluar sus cambios potenciales a lo largo del tiempo.Introduction: The characterization of land uses represents one of the essential inputs for the management of natural resources at different scales. Objective: To develop a methodology to characterize land use in the upper creek basin from the Azul stream (Buenos Aires, Argentina), through the fusion of satellite images with a medium spatial resolution. Materials and methods: A time-series of 23 images was used from the Normalized Difference Vegetation Index (NDVI) of the MODIS-Terra satellite (product MOD13Q1) for the period May 2015 - May 2016. Landsat 8 images were used to discriminate some categories difficult to classify with NDVI-MODIS. The final cover map was validated regarding verification points independent to the classification process; its accuracy was evaluated by means of the Kappa statistic. Results and discussion: The NDVI time series allowed to recognize the phenological patterns of the covers and land use of greater representativeness in the region. Seven land cover were discriminated; the agricultural uses represented 81.5 % of the surface, double-crop wheat-soya (soybean in Argentina) system predominated (39.4 %). The overall accuracy of the final map was high (88.9 %, Kappa coefficient = 0.86). Conclusion: The methodology used has the advantage of being quick and replicable, to characterize the land uses of a given region and to evaluate its potential changes over time.Fil: Guevara Ochoa, Cristian. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lara, Bruno Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomía. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios en Teledetección de Azul; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Vives, Luis Sebastián. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Azul; ArgentinaFil: Zimmermann, Erik Daniel. Universidad Nacional de Rosario. Facultad de Ciencias Exactas Ingeniería y Agrimensura. Centro Universidad Rosario de Investigaciones Hidroambientales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gandini, Marcelo Luciano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomía. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios en Teledetección de Azul; Argentin

Relationship between carbon footprint and profits: the moderating role of clean energy innovation

Clean energy innovation is critical to the decarbonization of CO2-intensive industries that rely on fossil fuels. Nonetheless, a deeper understanding of the influence of technical innovation on firms' efforts to tackle climate change and improve economic competitiveness is needed, particularly in those industrial sectors with "hard-to-abate" CO2e emissions. This quantitative longitudinal research examines the moderating effect of clean energy innovation on the link between carbon footprint and corporate profits using a global sample of 7,827 firm-year data pertaining to 167 multinational companies between 2018 and 2021. This study uses the Bayesian method, a recommended statistical framework for fitting complex growth curve models with longitudinal data, to specify a multi-indicator latent growth curve (B-LGC) model for longitudinal moderation analysis. The findings indicate that the carbon footprint has a large positive influence on corporate profits. Furthermore, the model results support the prediction that clean energy innovation positively moderates the link between value chain (Scope 3) emissions and gross profit margin when measured using renewable energy consumption. The implications of the findings suggest that executives and managers in heavily polluting companies can achieve greater competitive advantages and transition to a net-zero emissions business by developing a comprehensive understanding of Scope 3 emissions. More significantly, policymakers should pay particular attention to these companies' Scope 3 emissions in order to develop regulation and control systems that encourage clean energy innovation.La innovación en energías limpias es clave hacia la descarbonización de industrias intensivas en el uso de combustibles fósiles. No obstante, existe la necesidad de una mayor comprensión del impacto de la innovación tecnológica en los esfuerzos de las empresas por combatir el cambio climático y mejorar su competitividad, principalmente en aquellos industrias “difíciles de reducir” las emisiones de CO₂e. Usando una muestra global de 7 827 observaciones de empresa-año correspondientes a 167 empresas internacionales entre el 2018 y 2021, esta investigación longitudinal cuantitativa examina el efecto moderador de la innovación en energías limpias en el vínculo entre la huella de carbono y la rentabilidad corporativa. Para este análisis de moderación longitudinal, se emplea el método bayesiano, un marco estadístico recomendado para ajustar modelos de curva de crecimiento complejos con datos longitudinales, estimando para ello un modelo de curva de crecimiento latente (B-LGC) de múltiples indicadores. Los resultados revelan un impacto significativo de la huella de carbono sobre las ganancias. Asimismo, los resultados respaldan la hipótesis de que la innovación en energías limpias, cuando es medida usando el consumo de energías renovables, modera positivamente la relación entre las emisiones de la cadena de valor (Alcance 3) y el margen de utilidad bruta. Estos hallazgos implican que una comprensión más detallada de las emisiones de toda la cadena de valor (Alcance 3) por parte de los ejecutivos y gerentes de las empresas, representa un mecanismo efectivo para obtener mayores ventajas competitivas, y al mismo tiempo llegar a ser un negocio con cero emisiones netas. Mas importante aún, los formuladores de políticas deberían prestar especial atención a las emisiones de Alcance 3, para formular mecanismos regulatorios y de control que estimulen la innovación en energías limpias

Heat Mapping Crime: A Data-Driven Approach to Policing in New York

In the aftermath of the COVID-19 pandemic, New York City has seen a surge in criminal activities. In 2023, major crime continues to be higher compared to pre-pandemic levels. Although progress is being made to reduce the number of murders and robberies, law enforcement is continuing to struggle with increases in felony assaults and car thefts. Our project serves to benefit members of the community and law enforcement alike. We created a heat map, which is a visual representation of data that uses colors to represent different values. In the context of crime mapping, our heat map is used to show the density of crimes in a particular area. As of today, the NYPD utilizes two databases: Compstat 2.0 & Excel. Compstat 2.0, updated on a weekly basis, shows a change in the number of crimes compared to the week’s prior across several boroughs and precincts. The Excel data spans from 2000 to 2022 with the same type of information. The drawback here is that the average community member in New York City can’t draw any conclusions from the data available to them. This means that they have access to this data, but with no means to interpret the data in a simple manner. In our approach, we created a visual, animated representation of the data from 2000 to 2022. Thus, we have simplified the process for anybody who wishes to understand how crime rates evolve over the years, especially for those who live in neighborhoods that are high risk. In addition, we believe law enforcement can also utilize this resource as a means to better allocate resources to underserved neighborhoods. If successful, any individual in New York City, including tourists, can analyze the heat map to study which neighborhoods are at risk for crime so that they can be wary of their surroundings. It’s important to understand that with graphics the average community member will be more inclined to take safety precautions when commuting around New York City

Detection of leaf structures in close-range hyperspectral images using morphological fusion

Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods

Equivalence of solutions for non-homogeneous p(x)-Laplace equationsy

We establish the equivalence between weak and viscosity solutions for non-homogeneous p(x)-Laplace equations with a right-hand side term depending on the spatial variable, the unknown, and its gradient. We employ inf- and sup-convolution techniques to state that viscosity solutions are also weak solutions, and comparison principles to prove the converse. The new aspects of the p(x)- Laplacian compared to the constant case are the presence of log-terms and the lack of the invariance under translations.Fil: Medina, Maria. Universidad Autónoma de Madrid; EspañaFil: Ochoa, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Nacional de Cuyo. Facultad de Ingeniería; Argentin

Unveiling E-bike potential for commuting trips from GPS traces

Common goals of sustainable mobility approaches are to reduce the need for travel, to facilitate modal shifts, to decrease trip distances and to improve energy efficiency in the transportation systems. Among these issues, modal shift plays an important role for the adoption of vehicles with fewer or zero emissions. Nowadays, the electric bike (e-bike) is becoming a valid alternative to cars in urban areas. However, to promote modal shift, a better understanding of the mobility behaviour of e-bike users is required. In this paper, we investigate the mobility habits of e-bikers using GPS data collected in Belgium from 2014 to 2015. By analysing more than 10,000 trips, we provide insights about e-bike trip features such as: distance, duration and speed. In addition, we offer a deep look into which routes are preferred by bike owners in terms of their physical characteristics and how weather influences e-bike usage. Results show that trips with higher travel distances are performed during working days and are correlated with higher average speeds. Usage patterns extracted from our data set also indicate that e-bikes are preferred for commuting (home-work) and business (work related) trips rather than for recreational trips