Controle biologico do nematoide-das-galhas com bacteria Pasteuria penetrans.

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EFFECT OF ADDING POLYVINYL ACETATE AND COCONUT SHELL ON CONCRETE

Manufacture of concrete with a mixture of coconut shell and polyvinyl acetate. The material used in this study are from the coconut shell coconut waste treatment process which is crushed to a maximum size of 20 mm, whereas polyvinyl acetate condition is milky white emulsion. This study uses laboratory experiments concrete according to standards ISO 7656: 2012 for normal concrete and developed into concrete innovation. Coconut shell as a substitute for gravel with a rate of 8% and 10%, while the addition of polyvinyl acetate in the amount of 8% and 10%. At the time of fresh concrete workmanship, testing the slump test to control the workability and homogeneity. Treatment (Curing) specimen is done by covering the paper specimens with wet cement. Compressive strength testing carried out during the 28 days of the test specimen. The results obtained on the compressive strength with the highest average percentage of materials such as concrete polyvinyl acetate 8% and 8% of coconut shell Amounting to 351 kg/cm2 with an average density of 2199 kg/cm3. In each of the test object with a weight value is the quality efficiency in concrete polyvinyl acetate 8% and 8% of coconut shell

Observations on soil-atmosphere interactions after long-term monitoring at two sample sites subjected to shallow landslides

Soil-atmosphere interaction has implications in different scientific research contexts and is increasingly investigated through field measurements. This paper reports a detailed description of interaction between shallow soil and atmosphere at two test sites in Oltrepò Pavese area (Northern Italy). The two test sites are in the same climatic area but are characterised by different geological features. In fact, the first objective is to compare the behaviour of two different soils, namely a clayey-sandy silt (CL) and a silty clay (CH), under similar meteorological events. Soil-atmosphere interaction is studied on the basis of long-term (about 87 and 42 months for the two test sites, respectively) monitoring data of both volumetric water content and soil water potential, recorded at different depths along two vertical soil profiles in the first two metres from ground level. Field measurements, together with meteorological data such as precipitation and air temperature, allow for clear identification of the seasonal fluctuations of unsaturated soil hydraulic properties. To infer detailed information, the recorded data were processed and relationships between soil water potential and water content were investigated. Different time spans, from several months to a few days, even including single rainy events, are considered to show the hydraulic soil behaviour. The hysteretic cycles of water content with respect to soil water potential and non-equilibrium flow are highlighted. In particular, the measured soil water potential is in the range of 0–800 kPa and of 0–1500 kPa for the CL and CH soil, respectively. At both sites, the observed hysteretic cycles are more frequent in the hot season (summer) than in the cold season (winter) and tend to reduce with depth. The experimental results are compared with the soil water characteristic curves (SWCCs) to assess whether and to what extent the SWCCs are reliable in modelling the hydraulic behaviour of partially saturated soils, under atmospheric forcing, at least in the considered climatic contexts

A data-driven method for the temporal estimation of soil water potential and its application for shallow landslides prediction

Soil water potential is a key factor to study water dynamics in soil and for estimating the occurrence of natural hazards, as landslides. This parameter can be measured in field or estimated through physically-based models, limited by the availability of effective input soil properties and pre-liminary calibrations. Data-driven models, based on machine learning techniques, could overcome these gaps. The aim of this paper is then to develop an innovative machine learning methodology to assess soil water potential trends and to implement them in models to predict shallow landslides. Monitoring data since 2012 from test-sites slopes in Oltrepò Pavese (northern Italy) were used to build the models. Within the tested techniques, Random Forest models allowed an outstanding recon-struction of measured soil water potential temporal trends. Each model is sensitive to meteorological and hydrological characteristics according to soil depths and features. Reliability of the proposed models was confirmed by correct estimation of days when shallow landslides were triggered in the study areas in December 2020, after implementing the modeled trends on a slope stability model, and by the correct choice of physically-based rainfall thresholds. These results confirm the potential application of the developed methodology to estimate hydrological scenarios that could be used for decision-making purposes

Recycled water causes no salinity or toxicity issues in Napa vineyards

In response to Napa Sanitation District's interest in expanding its delivery of recycled water to vineyards for irrigation, we conducted a feasibility study to assess the suitability of the water for this use. We adopted two approaches: comparing the water quality characteristics of the recycled water with those of other local sources of irrigation water, and evaluating soil samples from a vineyard that was irrigated for 8 years with the recycled water. Results indicate that the quality of the recycled water is suitable for irrigation, and also that long-term accumulation of salts and toxic ions have not occurred in the vineyards studied and are unlikely to occur. Nutrients in the recycled water may be beneficial to vineyards, though the levels of nitrogen may need to be reduced by planting cover crops in some vineyards

<b><i>Topoisomerase 1</i></b> Promoter Variants and Benefit from Irinotecan in Metastatic Colorectal Cancer Patients

Objective: Topoisomerase 1 (topo-1) is an important target for the treatment of metastatic colorectal cancer (CRC). The aim of the present study was to evaluate the correlation between topo-1 single-nucleotide polymorphisms (SNPs) and clinical outcome in metastatic CRC (mCRC) patients. Methods: With the use of specific software (PROMO 3.0), we performed an in silico analysis of topo-1 promoter SNPs; the rs6072249 and rs34282819 SNPs were included in the study. DNA was extracted from 105 mCRC patients treated with FOLFIRI ± bevacizumab in the first line. SNP genotyping was performed by real-time PCR. Genotypes were correlated with clinical parameters (objective response rate, progression-free survival, and overall survival). Results: No single genotype was significantly associated with clinical variables. The G allelic variant of rs6072249 topo-1 SNP is responsible for GC factor and X-box-binding protein transcription factor binding. The same allelic variant showed a nonsignificant trend toward a shorter progression-free survival (GG, 7.5 months; other genotypes, 9.3 months; HR 1.823, 95% CI 0.8904-3.734; p = 0.1). Conclusion: Further analyses are needed to confirm that the topo-1 SNP rs6072249 and transcription factor interaction could be a part of tools to predict clinical outcome in mCRC patients treated with irinotecan-based regimens

Recomendação de adubação para aveia, em dois sistemas de plantio, em Latossolo Vermelho distrófico típico.

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