Volatile Composition of Fortification Grape Spirit and Port Wine: Where Do We Stand?

Port wine's prominence worldwide is unequivocal and the grape spirit, which comprises roughly one fifth of the total volume of this fortified wine, is also a contributor to the recognized quality of this beverage. Nonetheless, information about the influence of the grape spirit on the final aroma of Port wine, as well as its volatile composition, is extremely limited. Moreover, the aroma characteristics of Port wines are modulated mainly by their volatile profiles.

Soybean sorting based on protein content using X-ray fluorescence spectrometry.

The purpose of this research was to evaluate performance of an energy-dispersive X-ray fluorescence (XRF) sensor to classify soybean based on protein content. The hypothesis was that sulfur signals and other XRF spectral features can be used as proxies to infer soybean protein content. Sample preparation and equipment settings to optimize detection of S and other specific emission lines were tested for this application.

A multi-sensor human gait dataset captured through an optical system and inertial measurement units.

Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optical motion data from 25 participants free of lower-limb injuries, aged between 18 and 47 years.

Reliability and generalization of gait biometrics using 3D inertial sensor data and 3D optical system trajectories.

Particularities in the individuals' style of walking have been explored for at least three decades as a biometric trait, empowering the automatic gait recognition field. Whereas gait recognition works usually focus on improving end-to-end performance measures, this work aims at understanding which individuals' traces are more relevant to improve subjects' separability. For such, a manifold projection technique and a multi-sensor gait dataset were adopted to investigate the impact of each data source characteristics on this separability.

Spectral data of tropical soils using dry-chemistry techniques (VNIR, XRF, and LIBS): A dataset for soil fertility prediction.

Proximal soil sensing technologies, such as visible and near infrared diffuse reflectance spectroscopy (VNIR), X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS), are dry-chemistry techniques that enable rapid and environmentally friendly soil fertility analyses. The application of XRF and LIBS sensors in an individual or combined manner for soil fertility prediction is quite recent, especially in tropical soils. The shared dataset presents spectral data of VNIR, XRF, and LIBS sensors, even as the characterization of key soil fertility attributes (clay, organic matter, cation exchange capacity, pH, base saturation, and exchangeable P, K, Ca, and Mg) of 102 soil samples.

Information and behavioral responses during a pandemic: Evidence from delays in Covid-19 death reports.

Providing information is important for managing epidemics, but issues with data accuracy may hinder its effectiveness. Focusing on Covid-19 in Mexico, we ask whether delays in death reports affect individuals' beliefs and behavior. Exploiting administrative data and an online survey, we provide evidence that behavior, and consequently the evolution of the pandemic, are considerably different when death counts are presented by date reported rather than by date occurred, due to non-negligible reporting delays.

Combined Use of Vis-NIR and XRF Sensors for Tropical Soil Fertility Analysis: Assessing Different Data Fusion Approaches.

Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are promising proximal soil sensing (PSS) tools for predicting soil key fertility attributes. This work aimed at assessing the performance of the individual and combined use of vis-NIR and XRF sensors to predict clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients (ex-P, ex-K, ex-Ca, and ex-Mg) in Brazilian tropical soils. Individual models using the data of each sensor alone were calibrated using multiple linear regressions (MLR) for the XRF data, and partial least squares (PLS) regressions for the vis-NIR data.

Simplifying Sample Preparation for Soil Fertility Analysis by X-ray Fluorescence Spectrometry.

Portable X-ray fluorescence (pXRF) sensors allow one to collect digital data in a practical and environmentally friendly way, as a complementary method to traditional laboratory analyses. This work aimed to assess the performance of a pXRF sensor to predict exchangeable nutrients in soil samples by using two contrasting strategies of sample preparation: pressed pellets and loose powder (<2 mm). Pellets were prepared using soil and a cellulose binder at 10% w w followed by grinding for 20 min.

The times, movements and operational efficiency of mechanized coffee harvesting in sloped areas.

Coffee farms have been adopting the microterraces system, a technique that reduces the effect of the slope by moving the soil between the crop lines. In this way, all the mechanized operations can be carried out normally, except for harvesting, due to the work limitation of the harvesters, who work in areas with a maximum slope of 20%. One option is to use unilateral harvesters, which crop one side at a time; however, there has been no research on these microterrace machines to evaluate their performance and to compare it with those of the other harvesting methods in those regions.