894 resultados para Illinois Wetland Monitoring and Assessment Program.
Resumo:
Estimation of pasture productivity is an important step for the farmer in terms of planning animal stocking, organizing animal lots, and determining supplementary feeding needs throughout the year. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Two types of sensors were evaluated: an active optical sensor(OptRx®, which measures the NDVI, Normalized Difference Vegetation Index) and a capacitance probe (GrassMaster II which estimates plant mass). The results showed the potential of NDVI for monitoring the evolution of spatial and temporal patterns of vegetative growth of biodiverse pasture. Higher NDVI values were registered as pasture approached its greatest vegetative vigor, with a significant fall in the measured NDVI at the end of Spring, when the pasture began to dry due to the combination of higher temperatures and lower soil moisture content. This index was also effective for identifying different plant species (grasses/legumes) and variability in pasture yield. Furthermore, it was possible to develop calibration equations between the capacitance and the NDVI (R2 = 0.757; p < 0.01), between capacitance and GM (R2 = 0.799; p<0.01), between capacitance and DM (R2 = 0.630; p<0.01), between NDVI and GM (R2=0.745; p < 0.01), and between capacitance and DM (R2=0.524; p<0.01). Finally, a direct relationship was obtained between NDVI and pasture moisture content (PMC, in %) and between capacitance and PMC (respectively, R2 = 0.615; p<0.01 and R2=0.561; p <0.01) in Alentejo dryland farming systems.
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Since the dawn of its presence on earth, the human being has been able to exploit the enzymes for its subsistence. More recent is the meeting between the enzymatic processes and the urgent need for technologies that aim to preserve our planet. In this field nowadays enzymatic catalysis is tested either to depollution/remediation as well as waste disposal. The work presented in this thesis, regarding both these two topics, is tailored on two European projects (EU 2020), MADFORWATER and TERMINUS respectively. Firstly, production of micro- and nanocatalysts via immobilization of laccases (a lignin-degrader enzyme) is performed. In the second part of the thesis laccase is applied to a tertiary treatment of wastewater with the aim to degrade 9 pharmaceutical active compounds in batch reactors. Despite several optimizations, poor degradation is reached and we did not proceed with the study of different bioreactor setups. Therefore, the focus is moved to a project concerning the production of smart multi-layer plastic packaging containing enzymes to improve the possibilities of recycling. In this field shielded nanocatalysts produced via coating techniques able to interact with redox mediators are investigated. The target substrate in this second project is produced in laboratory (i.e. polyurethane like compounds), starting from monomers whose degradation had already been tested, as a proof of concept. The first enzyme studied is still the laccase.
Resumo:
This work study proposes novel and natural inhibitors of the enzyme urease, as more sustainable alternatives to the synthetic ones. Specifically, Deep Eutectic Solvents (DES) were used as an extractants and carriers of polyphenols extracted from waste biomass enriched in antioxidant compounds. The polyphenolic extracts with DES have been tested on lab-scale experiments to verify their effect on the reduction of the hydrolysis rate of urea-based fertilizers catalyzed by urease. The phytotoxicity and the soil ecotoxicity of DES and polyphenols formulations were then tested. DES resulted promising in terms of polyphenols extraction ability from biomass and as carriers of bioactive compounds in the agricultural field, showing non-damaging effects on plants (Avena sativa) and microarthropods in soil.
Resumo:
Modern scientific discoveries are driven by an unsatisfiable demand for computational resources. High-Performance Computing (HPC) systems are an aggregation of computing power to deliver considerably higher performance than one typical desktop computer can provide, to solve large problems in science, engineering, or business. An HPC room in the datacenter is a complex controlled environment that hosts thousands of computing nodes that consume electrical power in the range of megawatts, which gets completely transformed into heat. Although a datacenter contains sophisticated cooling systems, our studies indicate quantitative evidence of thermal bottlenecks in real-life production workload, showing the presence of significant spatial and temporal thermal and power heterogeneity. Therefore minor thermal issues/anomalies can potentially start a chain of events that leads to an unbalance between the amount of heat generated by the computing nodes and the heat removed by the cooling system originating thermal hazards. Although thermal anomalies are rare events, anomaly detection/prediction in time is vital to avoid IT and facility equipment damage and outage of the datacenter, with severe societal and business losses. For this reason, automated approaches to detect thermal anomalies in datacenters have considerable potential. This thesis analyzed and characterized the power and thermal characteristics of a Tier0 datacenter (CINECA) during production and under abnormal thermal conditions. Then, a Deep Learning (DL)-powered thermal hazard prediction framework is proposed. The proposed models are validated against real thermal hazard events reported for the studied HPC cluster while in production. This thesis is the first empirical study of thermal anomaly detection and prediction techniques of a real large-scale HPC system to the best of my knowledge. For this thesis, I used a large-scale dataset, monitoring data of tens of thousands of sensors for around 24 months with a data collection rate of around 20 seconds.
Resumo:
BACKGROUND: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in pregnancy has been associated with multiple adverse pregnancy outcomes, including the risk of in utero mother-to-child transmission. Short- and long-term outcomes of SARS-CoV-2 exposed neonates and the extent to which maternal SARS-CoV-2 antibodies are transferred to neonates are still unclear. METHODS: Prospective observational study enrolling neonates born to mothers with SARS-CoV-2 infection in pregnancy, between April 2020-April 2021. Neonates were evaluated at birth and enrolled in a 12-month follow-up. SARS-CoV-2 IgG transplacental transfer ratio was assessed in mother-neonate dyads at birth. Maternal derived IgG were followed in infants until negativizing. RESULTS: Of 2745 neonates, 106 (3.9%) were delivered by mothers with SARS-CoV-2 infection in pregnancy. Seventy-six of 106 (71.7%) mothers were symptomatic. Median gestational age and mean birth weight were 39 weeks (range 25+5-41+4) and 3305 grams (SD 468). Six of 106 (6%) neonates were born preterm, without significant differences between asymptomatic and symptomatic mothers (P=0.67). No confirmed cases of in utero infection were detected. All infants had normal cerebral ultrasound and clinical evaluation at birth and during follow-up, until a median age of 7 months (range 5-12). All mothers and 96/106 (90.5%) neonates had detectable SARS-CoV-2 IgG at birth. Transplacental transfer ratio was higher following second trimester maternal infections (mean 0.940.46 versus 1.070.64 versus 0.750.44, P=0.039), but was not significantly different between asymptomatic and symptomatic women (P=0.20). IgG level in infants progressively decreased after birth: at 3 months 53% (51/96) and at four months 68% (63/96) had lost maternal antibodies respectively. The durability of maternal antibodies was positively correlated to the IgG level at birth (r=0.66; P<0.00001). CONCLUSIONS: Maternal SARS-CoV-2 infection was not associated with increased neonatal or long-term morbidity. No cases of confirmed in utero infection were detected. Efficient transplacental IgG transfer was found following second trimester maternal infections.
Resumo:
This PhD was driven by an interest for inclusive and participatory approaches. The methodology that bridges science and society is known as 'citizen science' and is experiencing a huge upsurge worldwide, in the scientific and humanities fields. In this thesis, I have focused on three topics: i) assessing the reliability of data collected by volunteers; ii) evaluating the impact of environmental education activities in tourist facilities; and iii) monitoring marine biodiversity through citizen science. In addition to these topics, during my research stay abroad, I developed a questionnaire to investigate people's perceptions of natural areas to promote the implementation of co-management. The results showed that volunteers are not only able to collect sufficiently reliable data, but that during their participation in this type of project, they can also increase their knowledge of marine biology and ecology and their awareness of the impact of human behaviour on the environment. The short-term analysis has shown that volunteers are able to retain what they have learned. In the long term, knowledge is usually forgotten, but awareness is retained. Increased awareness could lead to a change in behaviour and in this case a more environmentally friendly attitude. This aspect could be of interest for the development of environmental education projects in tourism facilities to reduce the impact of tourism on the environment while adding a valuable service to the tourism offer. We also found that nature experiences in childhood are important to connect to nature in adulthood. The results also suggest that membership or volunteering in an environmental education association could be a predictor of people's interest in more participatory approaches to nature management. In most cases, the COVID -19 pandemic had not changed participants' perceptions of the natural environment.
Resumo:
The Smart Grid needs a large amount of information to be operated and day by day new information is required to improve the operation performance. It is also fundamental that the available information is reliable and accurate. Therefore, the role of metrology is crucial, especially if applied to the distribution grid monitoring and the electrical assets diagnostics. This dissertation aims at better understanding the sensors and the instrumentation employed by the power system operators in the above-mentioned applications and studying new solutions. Concerning the research on the measurement applied to the electrical asset diagnostics: an innovative drone-based measurement system is proposed for monitoring medium voltage surge arresters. This system is described, and its metrological characterization is presented. On the other hand, the research regarding the measurements applied to the grid monitoring consists of three parts. The first part concerns the metrological characterization of the electronic energy meters’ operation under off-nominal power conditions. Original test procedures have been designed for both frequency and harmonic distortion as influence quantities, aiming at defining realistic scenarios. The second part deals with medium voltage inductive current transformers. An in-depth investigation on their accuracy behavior in presence of harmonic distortion is carried out by applying realistic current waveforms. The accuracy has been evaluated by means of the composite error index and its approximated version. Based on the same test setup, a closed-form expression for the measured current total harmonic distortion uncertainty estimation has been experimentally validated. The metrological characterization of a virtual phasor measurement unit is the subject of the third and last part: first, a calibrator has been designed and the uncertainty associated with its steady-state reference phasor has been evaluated; then this calibrator acted as a reference, and it has been used to characterize the phasor measurement unit implemented within a real-time simulator.
Resumo:
The rate of diagnosis and treatment of degenerative spine disorders is increasing, increasing the need for surgical intervention. Posterior spine fusion is one surgical intervention used to treat various spine degeneration pathologies To minimize the risk of complications and provide patients with positive outcomes, preoperative planning and postsurgical assessment are necessary. This PhD aimed to investigate techniques for the surgical planning and assessment of spine surgeries. Three main techniques were assessed: stereophotogrammetric motion analysis, 3D printing of complex spine deformities and finite element analysis of the thoracolumbar spine. Upon reviewing the literature on currently available spine kinematics protocol, a comprehensive motion analysis protocol to measure the multi-segmental spine motion was developed. Using this protocol, the patterns of spine motion in patients before and after posterior spine fixation was mapped. The second part investigated the use of virtual and 3D printed spine models for the surgical planning of complex spine deformity correction. Compared to usual radiographic images, the printed model allowed optimal surgical intervention, reduced surgical time and provided better surgeon-patient communication. The third part assessed the use of polyetheretherketone rods auxiliary to titanium rods to reduce the stiffness of posterior spine fusion constructs. Using a finite element model of the thoracolumbar spine, the rods system showed a decrease in the overall stress of the uppermost instrumented vertebra when compared to regular fixation approaches. Finally, a retrospective biomechanical assessment of a lumbopelvic reconstruction technique was investigated to assess the patients' gait following the surgery, the implant deformation over the years and the extent of bony fusion between spine and implant. In conclusion, this thesis highlighted the need to provide surgeons with new planning and assessment techniques to better understand postsurgical complications. The methodologies investigated in this project can be used in the future to establish a patient-specific planning protocol.
Resumo:
The present study investigates the effects of drill cutting discharges on the structure of meiofauna communities in an area of the shelf break at Campos Basin, Southeast Brazil. Drilling activities were operated, in a first phase, with water-based fluid and, in a second phase, with synthetic fluid paraffin-based (NAF-III). A total of 135 samples taken at a pre-drilling situation (MS1) and two post-drilling moments (MS2 and MS3-3 and 22 months post-drilling, respectively) were analyzed. Effects on meiofauna were dependent on two main factors: 1-the impact received during drilling operation, if water-based or synthetic/water-based drilling fluid and 2-the background state, if it already presented signs of previous drilling activities or not. Based on univariate and multivariate analysis, there were evidences that the most affected area after drilling was those under the influence of synthetic-based fluid and that already had signs of previous drillings activities. The region impacted only by water-based fluid was less affected and the only one that completely recovered after 22 months. Nematodes and copepods had different responses to the impact. While copepods flourish in the impacted area and recovered 22 months after drilling, nematodes were adversely affected shortly after drilling and the community structure only recovered where hydrocarbons had been depleted.
Resumo:
The greenhouse effect and resulting increase in the Earth`s temperature may accelerate the mean sea-level rise. The natural response of bays and estuaries to this rise, such as this case study of Santos Bay (Brazil), will include change in shoreline position, land flooding and wetlands impacts. The main impacts of this scenario were studied in a physical model built in the Coastal and Harbour Division of Hydraulic Laboratory, University of Sao Paulo, and the main conclusions are presented in this paper. The model reproduces near 1,000 km(2) of the study area, including Santos, Sao Vicente, Praia Grande, Cubatao, Guaruja and Bertioga cities.
Resumo:
The development of biomonitoring programs based on the macroinvertebrate community requires the understanding of species distribution patterns, as well as of the responses of the community to anthropogenic stressors. In this study, 49 metrics were tested as potential means of assessing the condition of 29 first- and second-order streams located in areas of differing types of land use in So Paulo State, Brazil. Of the sampled streams, 15 were in well-preserved regions in the Atlantic Forest, 5 were among sugarcane cultivations, 5 were in areas of pasture, and 4 were among eucalyptus plantations. The metrics were assessed against the following criteria: (1) predictable response to the impact of human activity; (2) highest taxonomic resolution, and (3) operational and theoretical simplicity. We found that 18 metrics were correlated with the environmental and spatial predictors used, and seven of these satisfied the selection criteria and are thus candidates for inclusion in a multimetric system to assess low-order streams in So Paulo State. These metrics are family richness; Ephemeroptera, Plecoptera and Trichoptera (EPT) richness; proportion of Megaloptera and Hirudinea; proportion of EPT; Shannon diversity index for genus; and adapted Biological Monitoring Work Party biotic index.
Resumo:
Streams located in areas of sugarcane cultivation receive high concentrations of metal ions from soils of the adjacent areas causing accumulation of metals in the aquatic sediment. This impact results in environmental problems and leads to bioaccumulation of metal ions in aquatic organisms. In the present study, metal concentrations in different predatory insects were studied in streams near sugarcane cultivation and compared to reference sites. Possible utilisation of predatory insects as bioindicators of metal contamination due to sugarcane cultivation from 13 neotropical streams was evaluated. Ion concentrations of Al, Cd, Cr, Cu, Zn, Fe, and Mn in adult Belostomatidae (Hemiptera) and in larvae of Libellulidae (Odonata) were analysed. Nine streams are located in areas with sugarcane cultivation, without riparian vegetation (classified as impacted area) and four streams were located in forested areas (reference sites). Metal concentrations in insects were higher near sugarcane cultivations than in control sites. Cluster analysis, complemented by an ANOSIM test, clearly showed that these insect groups are good potential bioindicators of metal contamination in streams located in areas with sugarcane cultivation and can be used in monitoring programmes. We also conclude that Libellulidae appeared to accumulate higher concentrations of metals than Belostomatidae.