Universidade Anhembi Morumbi is a Brazilian private university located in São Paulo and member of the Laureate International Universities group. Ranked one of the top three private universities in the state of São Paulo, the university is one of the most prestigious in various areas of knowledge such as medicine, engineering, business, communication, gastronomy and fashion design. UAM is also known as the first international university of Brazil.UAM is ranked 351st out of about 800 colleges in Latin America by Top Universities. It is also ranked 76th in Brazil by Unirank.
This study aims to examine the pricing objectives and pricing strategies that hospitality companies use to price their products and services. In addition, this study examines whether the pricing objectives are linked to the pricing strategies adopted. This research employed a descriptive approach utilizing quantitative techniques and surveyed 417 hospitality industry companies in a tourist destination. The quantitative methodologies employed encompassed Exploratory Factor Analysis, followed by Logit Regression. The results of this study revealed that companies actively pursue pricing objectives which were condensed into three factors or dimensions, namely Price for increasing sales, Price for market enhancement, and Price for achieving financial targets. These three pricing objectives are associated with a repertoire of four distinct pricing strategies: Cost-Based Pricing, Image-Based Pricing, Differentiation Pricing, and Cash-Based Pricing. This research is subject to several limitations, with the foremost being the dynamic nature of pricing objectives and strategies over time.
The distance duality relation (DDR) relates two independent ways of measuring cosmological distances, namely the angular diameter distance and the luminosity distance. These can be measured with baryon acoustic oscillations (BAO) and Type Ia supernovae (SNe Ia), respectively. Here, we use recent DESI DR1, Pantheon+, SH0ES and DES-SN5YR data to test this fundamental relation. We employ a parametrised approach and also use model-independent Generic Algorithms (GA), which are a machine learning method where functions evolve loosely based on biological evolution. When we use DESI and Pantheon+ data without Cepheid calibration or big bang nucleosynthesis (BBN), there is a 2 sigma discrepancy with the DDR in the parametrised approach. Then, we add high-redshift BBN data and the low-redshift SH0ES Cepheid calibration. This reflects the Hubble tension since both data sets are in tension in the standard cosmological model Lambda CDM. In this case, we find a significant violation of the DDR in the parametrised case at 6 sigma. Replacing the Pantheon+ SNe Ia data by DES-SN5YR, we find similar results. For the model-independent approach, we find no deviation in the uncalibrated case and a small deviation with BBN and Cepheids which remains at 1 sigma. This shows the importance of considering model-independent approaches for the DDR.
Demographic bias in high-performance face recognition (FR) systems often eludes detection by existing metrics, especially with respect to subtle disparities in the tails of the score distribution. We introduce the Comprehensive Equity Index (CEI), a novel metric designed to address this limitation. CEI uniquely analyzes genuine and impostor score distributions separately, enabling a configurable focus on tail probabilities while also considering overall distribution shapes. Our extensive experiments (evaluating state-of-the-art FR systems, intentionally biased models, and diverse datasets) confirm CEI's superior ability to detect nuanced biases where previous methods fall short. Furthermore, we present CEI^A, an automated version of the metric that enhances objectivity and simplifies practical application. CEI provides a robust and sensitive tool for operational FR fairness assessment. The proposed methods have been developed particularly for bias evaluation in face biometrics but, in general, they are applicable for comparing statistical distributions in any problem where one is interested in analyzing the distribution tails.
Neutrinos are the least known particle in the Standard Model of elementary particle physics. They play a crucial role in cosmology, governing the universe's evolution and shaping the large-scale structures we observe today. In this chapter, we review crucial topics in neutrino cosmology, such as the neutrino decoupling process in the very early universe. We shall also revisit the current constraints on the number of effective relativistic degrees of freedom and the departures from its standard expectation of 3. Neutrino masses represent the very first departure from the Standard Model of elementary particle physics and may imply the existence of new unexplored mass generation mechanisms. Cosmology provides the tightest bound on the sum of neutrino masses, and we shall carefully present the nature of these constraints, both on the total mass of the neutrinos and on their precise spectrum. The ordering of the neutrino masses plays a major role in the design of future neutrino mass searches from laboratory experiments, such as neutrinoless double beta decay probes. Finally, we shall also present the futuristic perspectives for an eventual direct detection of cosmic, relic neutrinos.
