Delineation of Management Zones in Precision Agriculture by Integration of Proximal Sensing with Multivariate Geostatistics. Examples of Sensor Data Fusion

Fundamental to the philosophy of Precision Agriculture (PA) is the concept of matching inputs to needs. Recent research in PA has focused on use of Management Zones (MZ) that are field areas characterised by homogeneous attributes in landscape and soil conditions. Proximal sensing (such as Electromagnetic Induction (EMI), Ground Penetrating Radar (GPR) and X-ray fluorescence) can complement direct sampling and a multisensory platform can enable us to map soil features unambiguously. Several methods of multi-sensor data analysis have been developed to determine the location of subfield areas. Modern geostatistical techniques, treating variables as continua in a joint attribute and geographic space, offer the potential to analyse such data effectively. The objective of the paper is to show the potential of multivariate geostatistics to create MZ in the perspective of PA by integrating field data from different types of sensors, describing two study cases. In particular, in the first case study, cokriging and factorial cokriging were employed to produce thematic maps of soil trace elements and to delineate homogenous zones, respectively. In the second case, a multivariate geostatistical data-fusion technique (multi collocated cokriging) was applied to different geophysical sensor data (GPR and EMI), for stationary estimation of soil water content and for delineating within-field zone with different wetting degree. The results have shown that linking sensors of different type improves the overall assessment of soil and sensor data fusion could be effectively applied to delineate MZs in Precision Agriculture. However, techniques of data integration are urgently required as a result of the proliferation of data from different sources

Delineation of Management Zones in Precision Agriculture by Integration of Proximal Sensing with Multivariate Geostatistics. Examples of Sensor Data Fusion

Fundamental to the philosophy of Precision Agriculture (PA) is the concept of matching inputs to needs. Recent research in PA has focused on use of Management Zones (MZ) that are field areas characterised by homogeneous attributes in landscape and soil conditions. Proximal sensing (such as Electromagnetic Induction (EMI), Ground Penetrating Radar (GPR) and X-ray fluorescence) can complement direct sampling and a multisensory platform can enable us to map soil features unambiguously. Several methods of multi-sensor data analysis have been developed to determine the location of subfield areas. Modern geostatistical techniques, treating variables as continua in a joint attribute and geographic space, offer the potential to analyse such data effectively. The objective of the paper is to show the potential of multivariate geostatistics to create MZ in the perspective of PA by integrating field data from different types of sensors, describing two study cases. In particular, in the first case study, cokriging and factorial cokriging were employed to produce thematic maps of soil trace elements and to delineate homogenous zones, respectively. In the second case, a multivariate geostatistical data-fusion technique (multi collocated cokriging) was applied to different geophysical sensor data (GPR and EMI), for stationary estimation of soil water content and for delineating within-field zone with different wetting degree. The results have shown that linking sensors of different type improves the overall assessment of soil and sensor data fusion could be effectively applied to delineate MZs in Precision Agriculture. However, techniques of data integration are urgently required as a result of the proliferation of data from different sources

Occupational Burden of Asbestos-related Cancer in Argentina, Brazil, Colombia, and Mexico

Background: An estimate at the national level of the occupational cancer burden brought about by the industrial use of asbestos requires detailed routine information on such uses as well as on vital statistics of good quality. A causal association with asbestos exposure has been established for mesothelioma and cancers of the lung, larynx, and ovary. Objectives: The aim of this study was to provide estimates of the occupational burden of asbestos-related cancer for the Latin American countries that are or have been the highest asbestos consumers in the region: Argentina, Brazil, Colombia, and Mexico. Methods: The burden of multifactorial cancers has been estimated through the approach suggested for the World Health Organization using the population attributable fraction. The following data were used: • Proportion of workforce employed in each economic sector • Proportion of workers exposed to asbestos in each sector • Occupational turnover • Levels of exposure • Proportion of the population in the workforce • Relative risk for each considered disease for 1 or more levels of exposure Data on the proportion of workers exposed to asbestos in each sector are not available for Latin American countries; therefore, data from the European CAREX database (carcinogen exposure database) were used. Findings: Using mortality data of the World Health Organization Health Statistics database for the year 2009 and applying the estimated values for population attributable fractions, the number of estimated deaths in 5 years for mesothelioma and for lung, larynx, and ovary cancers attributable to occupational asbestos exposures, were respectively 735, 233, 29, and 14 for Argentina; 340, 611, 68, and 43 for Brazil; 255, 97, 14, and 9 for Colombia, and 1075, 219, 18, and 22 for Mexico. Conclusions: The limitations in compiling the estimates highlight the need for improvement in the quality of asbestos-related environmental and health data. Nevertheless, the figures are already usable to promote a ban on asbestos use

International scientific cooperation on asbestos-related disease prevention in Latin America.

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Integrating multimodal Raman and photoluminescence microscopy with enhanced insights through multivariate analysis

This paper introduces a novel multimodal optical microscope, integrating Raman and laser-induced photoluminescence (PL) spectroscopy for the analysis of micro-samples relevant in Heritage Science. Micro-samples extracted from artworks, such as paintings, exhibit intricate material compositions characterized by high complexity and spatial heterogeneity, featuring multiple layers of paint that may be also affected by degradation phenomena. Employing a multimodal strategy becomes imperative for a comprehensive understanding of their material composition and condition. The effectiveness of the proposed setup derives from synergistically harnessing the distinct strengths of Raman and laser-induced PL spectroscopy. The capacity to identify various chemical species through the latter technique is enhanced by using multiple excitation wavelengths and two distinct excitation fluence regimes. The combination of the two complementary techniques allows the setup to effectively achieve comprehensive chemical mapping of sample through a raster scanning approach. To attain a competitive overall measurement time, we employ a short integration time for each measurement point. We further propose an analysis protocol rooted in a multivariate approach. Specifically, we employ non-negative matrix factorization as the spectral decomposition method. This enables the identification of spectral endmembers, effectively correlated with specific chemical compounds present in samples. To demonstrate its efficacy in Heritage Science, we present examples involving pigment powder dispersions and stratigraphic micro-samples from paintings. Through these examples, we show how the multimodal approach reinforces material identification and, more importantly, facilitates the extraction of complementary information. This is pivotal as the two optical techniques exhibit sensitivity to different materials. Looking ahead, our method holds potential applications in diverse research fields, including material science and biology

La enseñanza de metodología para la práctica profesional : Reflexiones a partir de la experiencia en una institución de tecnología agropecuaria y desarrollo rural, Argentina

El presente trabajo reúne una serie de reflexiones a partir de la realización de capacitaciones sobre construcción de tipologías sociales en un ámbito no académico. De este modo, se inscribe en el área temática de enseñanza de metodología destinada a profesionales, en este caso pertenecientes a una institución de tecnología agropecuaria y desarrollo rural cuya necesidad es generar conocimiento para la toma de decisiones e intervenciones en territorios rurales. El trabajo está estructurado en dos partes. En la primera se realiza una descripción del contexto a partir del cual surgen estas reflexiones, es decir, un relato sobre el ámbito donde se promueven estas capacitaciones y el perfil de los participantes, para luego abordar la experiencia, objeto de este trabajo. En la segunda parte, se avanza con un análisis más general sobre la metodología específica para la construcción de tipologías sociales, por un lado, y por el otro, con aspectos que rescatamos como prioritarios para reflexionar respecto a cómo debe ser la enseñanza en metodología en contextos no académicos.Facultad de Humanidades y Ciencias de la Educació

The study of the mural painting in the 12th century monastery of Santa Maria delle Cerrate (Puglia-Italy): characterization of materials and techniques used

none6A multidisciplinary research was conducted by the University of Salento in collaboration with the Lecce Provincial Museum, in order to study different forms of art widespread in the Salento peninsula (Southern Italy) very valuable from an artistic point of view and important as driving force for the tourism of the area. In this research, the archaeometrical analysis was used to study the first cycle of paintings of the church of Santa Maria delle Cerrate, an italo-greek monastery located in the country about 15 km north-east of Lecce, probably built in the 12th century. Microscopic, chromatographic and spectrometric techniques were used: optical microscopy was used to study samples and the relevant stratigraphy, micro-Raman Spectroscopy to identify pigments and Gas Chromatography with Mass Spectrometric Detection to investigate the techniques masters used to decorate the monastery church. Further information on organic and inorganic materials present in the samples were obtained from Fourier transform infrared analysis in attenuated total reflectance. Materials and techniques were clearly ascertained, and, interestingly, pigments were applied both by fresco and egg-based tempera. Among the various pigments detected, the identification of both lapis lazuli and lead white opened new perspectives both from the historical and conservative points of view. Copyright © 2013 John Wiley & Sons, Ltd.Giuseppe E. De Benedetto;Daniela Fico;Eleonora Margapoti;Antonio Pennetta;Antonio Cassiano;Brizia MinervaDE BENEDETTO, Giuseppe, Egidio; Fico, Daniela; Eleonora, Margapoti; Pennetta, Antonio; Antonio, Cassiano; Brizia, Minerv

Malus pumila Mill. cv Annurca apple extract might be therapeutically useful against oxidative stress and patterned hair loss

: Patterned hair loss (PHL) or androgenetic alopecia is a condition affecting about 50% of people worldwide. Several pharmacological medications have been developed over the years, but few studies have investigated their effectiveness. Therefore, new, safer and more effective strategies are required. Recent investigations showed that Annurca apple extract application could induce keratin production and promote hair growth thanks to the high amount of procyanidin B2 contained in. Hence, this study aimed to investigate the role of an Annurca apple extract in preventing PHL by testing it on human follicle dermal papilla cells (HFDPCs) for the first time. Treatment of HFDPCs with Annurca apple extract counteracted intracellular reactive oxygen species accumulation by increasing the activity of antioxidant enzymes such as superoxide dismutase 2 and catalase. Furthermore, treatment with Annurca apple extract increased β-catenin and fibroblast growth factor 2, which are involved in hair growth stimulation. These data suggest that Annurca apple extract may be a potential therapeutically useful nutraceutical product for preventing or treating hair loss by reducing oxidative stress and inducing the expression of hair growth-related factors