Gradient test for generalised linear models with random effects

This work develops the gradient test for parameter selection in generalised linear models with random effects. Asymptotically, the test statistic has a chi-squared distribution and the statistic has a compelling feature: it does not require computation of the Fisher information matrix. Performance of the test is verified through Monte Carlo simulations of size and power, and also compared to the likelihood ratio, Wald and Rao tests. The gradient test provides the best results overall when compared to the traditional tests, especially for smaller sample sizes

Intensification of cattle ranching production systems: Socioeconomic and environmental synergies and risks in Brazil

Intensification of Brazilian cattle ranching systems has attracted both national and international attention due to its direct relation with Amazon deforestation on the one hand and increasing demand of the global population for meat on the other. Since Brazilian cattle ranching is predominantly pasture-based, we particularly focus on pasture management. We summarize the most recurrent opportunities and risks associated with pasture intensification that are brought up within scientific and political dialogues, and discuss them within the Brazilian context. We argue that sustainable intensification of pasturelands in Brazil is a viable way to increase agricultural output while simultaneously sparing land for nature. Since environmental degradation is often associated with low-yield extensive systems in Brazil, it is possible to obtain higher yields, while reversing degradation, by adopting practices like rotational grazing, incorporation of legumes and integrated crop-livestock-forestry systems. Technical assistance is however essential, particularly for small- and medium-scale farmers. Sound complementary policies and good governance must accompany these measures so that a ‘rebound effect’ does not lead to increased deforestation and other adverse social and environmental impacts. It is also important that animal welfare is not compromised. Although the discussion is presented with respect to Brazil, some aspects are relevant to other developing countries

Sensor Surface Design with NanoMaterials: A New Platform in the Diagnosis of COVID-19

Mass testing for COVID-19 is essential to defining patient management strategies, choosing the best clinical management, and dimensioning strategies for controlling viral dissemination and immunization strategies. Thus, it is of utmost importance to search for devices that allow a quick and reliable diagnosis of low cost that can be transposed from the bench to the bedside, such as biosensors. These devices can help choose the correct clinical management to minimize factors that lead to infected patients developing more severe diseases. The use of nanomaterials to modify biosensors’ surfaces to increase these devices’ sensitivity and their biofunctionality enables high-quality nanotechnological platforms. In addition to the diagnostic benefits, nanotechnological platforms that facilitate the monitoring of anti-SARS-CoV-2 antibodies may be the key to determining loss of protective immune response after an episode of COVID-19, which leads to a possible chance of reinfection, as well as how they can be used to assess and monitor the success of immunization strategies, which are beginning to be administered on a large scale and that the extent and duration of their protection will need to be determined. Therefore, in this chapter, we will cover nanomaterials’ use and their functionalities in the surface design of sensors, thus generating nanotechnological platforms in the various facets of the diagnosis of COVID-19