Satellite monitoring of bio-fertilizer restoration in olive groves affected by Xylella fastidiosa subsp. pauca.

Xylella fastidiosa subsp. pauca (Xfp), has attacked the olive trees in Southern Italy with severe impacts on the olive agro-ecosystem. To reduce both the Xfp cell concentration and the disease symptom, a bio-fertilizer restoration technique has been used. Our study applied multi-resolution satellite data to evaluate the effectiveness of such technique at both field and tree scale. For field scale, a time series of High Resolution (HR) Sentinel-2 images, acquired in the months of July and August from 2015 to 2020, was employed. First, four spectral indices from treated and untreated fields were compared. Then, their trends were correlated to meteo-events. For tree-scale, Very High Resolution (VHR) Pléiades images were selected at the closest dates of the Sentinel-2 data to investigate the response to treatments of each different cultivar. All indices from HR and VHR images were higher in treated fields than in those untreated. The analysis of VHR indices revealed that Oliarola Salentina can respond better to treatments than Leccino and Cellina cultivars. All findings were in agreement with in-field PCR results. Hence, HR data could be used to evaluate plant conditions at field level after treatments, while VHR imagery could be used to optimize treatment doses per cultivar.

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach.

The efficient and reliable monitoring of the flow of water in open channels provides useful information for preventing water slow-downs due to the deposition of materials within the bed of the channel, which might lead to critical floods. A reliable monitoring system can thus help to protect properties and, in the most critical cases, save lives. A sensing system capable of monitoring the flow conditions and the possible geo-environmental constraints within a channel can operate using still images or video imaging. The latter approach better supports the above two features, but the acquisition of still images can display a better accuracy. To increase the accuracy of the video imaging approach, we propose an improved particle tracking algorithm for flow hydrodynamics supported by a machine learning approach based on a convolutional neural network-evolutionary fuzzy integral (CNN-EFI), with a sub-comparison performed by multi-layer perceptron (MLP). Both algorithms have been applied to process the video signals captured from a CMOS camera, which monitors the water flow of a channel that collects rain water from an upstream area to discharge it into the sea. The channel plays a key role in avoiding upstream floods that might pose a serious threat to the neighboring infrastructures and population. This combined approach displays reliable results in the field of environmental and hydrodynamic safety.

Image Sensors for Wave Monitoring in Shore Protection: Characterization through a Machine Learning Algorithm.

Waves propagating on the water surface can be considered as propagating in a dispersive medium, where gravity and surface tension at the air-water interface act as restoring forces. The velocity at which energy is transported in water waves is defined by the group velocity. The paper reports the use of video-camera observations to study the impact of water waves on an urban shore. The video-monitoring system consists of two separate cameras equipped with progressive RGB CMOS sensors that allow 1080p HDTV video recording. The sensing system delivers video signals that are processed by a machine learning technique. The scope of the research is to identify features of water waves that cannot be normally observed. First, a conventional modelling was performed using data delivered by image sensors together with additional data such as temperature, and wind speed, measured with dedicated sensors. Stealth waves are detected, as are the inverting phenomena encompassed in waves. This latter phenomenon can be detected only through machine learning. This double approach allows us to prevent extreme events that can take place in offshore and onshore areas.

Physical and geochemical characteristics of land mud volcanoes along Colombia's Caribbean coast and their societal impacts.

The Caribbean coast is characterized by the presence of mud volcanoes, a secondary phenomenon of volcanism similar to mud diapirs for its development and evolution, but different in terms of geological features and forms. These mud volcanoes are often located close to tectonic faults and oil and gas deposits. Their geological context is dominated by the presence of clay sediments and brackish water, that favors the decomposition of organic material and the formation of methane. Mud volcanoes can thus be an important reservoir of hydrocarbons. This paper aims to fill the existing gap in the knowledge of mud volcanoes (MVs) of Colombia. We analyze the physical and geochemical characteristics of nine onshore mud volcanoes located in the Departments of Atlántico (La Laguna), Bolívar (Las Palomas, La Bonga, Santa Catalina, Yerbabuena, Clemencia, and Membrillal), Cordóba (Los Olivos), and Magdalena (Cañaveral). These structures present a kaolinitic composition, except for La Laguna mud volcano in which smectite is predominant. Apart from tectonic processes, this influences the shape and size of MVs and, also, the type and frequency of eruptions. The abundance of methane in all sites confirms the thermogenic origin of these structures. MVs are often considered landscape attractions as well as a therapeutic resources, but unfortunately they also represent a serious risk for the local communities, due to the frequent unexpected, eruptions, sometimes accompanied by the release of toxic gases or by landslides, that can damage the infrastructures and hurt the population living in the area. The MVs are classified into five vulnerability classes using a novel synthetic index which could improve the understanding of risks associated with the presence of MVs in proximity to towns and infrastructures.

Spatial and temporal classification of coastal regions using bioclimatic indices in a Mediterranean environment.

Bioclimatic indices combine atmospheric parameters to provide analytical indication of climatic features and their evolution in space and time that can directly relate with natural resource availability, distribution, and related bio-physical processes. The availability of bioclimatic information can provide natural resource managers with analytical means to assess the magnitude and temporal evolution of drought and climate change parameters that could affect the availability, demand and use of natural resources for various sectors. This paper presents a methodology to process bioclimatic data in the space and time domains for assessing the moisture/dryness level and water requirements of a region, and inform water resource planning and management decisions related to drought, climate variability and change. The methodology relies on a modular assembly of statistical tests and methods, and utilizes point scale measurements of meteorological data to perform the analysis of the spatial behavior of derived bioclimatic indicators at the continuous regional scale, and evaluate the significance of the temporal trends. Also, the article presents an application of the proposed methodology to a coastal area of southern Italy (the Apulia Region) that is characterized by recurring water supply limitations, involving the use of the popular De Martonne bioclimatic aridity index. The methodology allowed to obtain qualitative and quantitative information about the aridity level of the Apulia region, the identification of main bioclimatic zones, and the evaluation of spatial pattern and time evolution of aridity. The determination of bioclimatic zones showed that nearly 40% of the regional territory is characterized by dry sub-humid (Mediterranean) climate, about 30% by sub-humid climate, while nearly 10% and 20% are characterized by semi-arid and humid climates, respectively. The temporal analysis revealed that the Salento and the Ionian coastal zone are areas at risk of increasing aridity, with resulting impacts on the water supply and demand for irrigated agriculture.

A palladium iodide-catalyzed carbonylative approach to functionalized pyrrole derivatives.

A novel and convenient approach to functionalized pyrroles is presented, based on Pd-catalyzed oxidative heterocyclization-alkoxycarbonylation of readily available N-Boc-1-amino-3-yn-2-ols. Reactions were carried out in alcoholic solvents at 80-100 °C and under 20 atm (at 25 °C) of a 4:1 mixture of CO-air, in the presence of the PdI(2)-KI catalytic system (2-5 mol % of PdI(2), KI/PdI(2) molar ratio = 10). In the case of N-Boc-1-amino-3-yn-2-ols 3, bearing alkyl or aryl substituents, the carbonylation reaction led to a mixture of Boc-protected and N-unsubstituted pyrrole-3-carboxylic esters 4 and 5, respectively. This mixture could be conveniently and quantitatively converted into deprotected pyrrole-3-carboxylic esters 5 by a simple basic treatment. In the case of diastereomeric (3RS,4RS)- and (3RS,4SR)-N-Boc-3-amino-2-methyldec-5-yn-4-ol (syn-3f and anti-3f, respectively, whose relative configuration was determined by X-ray crystallographic analysis), no particular difference was observed in the reactivity of the two diastereomers between them and with respect to the diastereomeric mixture (3S,4S) + (3S,4R). Interestingly, N-Boc-2-alkynyl-1-amino-3-yn-2-ols 6, bearing an additional alkynyl substituent α to the hydroxyl group, spontaneously underwent N-deprotection under the reaction conditions and regioselective water addition to the alkynyl group at C-3 of the corresponding pyrrole-3-carboxylic ester derivative, thus directly affording highly functionalized pyrrole derivatives 7 in one step. In a similar manner, a novel functionalized dihydropyrrolizine derivative 9 was directly synthesized starting from (S)-7-(pyrrolidin-2-yl)trideca-5,8-diyn-7-ol 8.

The solid state structure and reactivity of NbCl(5) x (N,N'-dicyclohexylurea) in solution: evidence for co-ordinated urea dehydration to the relevant carbodiimide.

NbCl(5) x (N,N'-dicyclohexylurea) 1a owns a distorted octahedral structure due to intramolecular NH...Cl bonding. The unit cell contains four units which are intermolecularly NH...Cl and NH...N bonded. An extended intramolecular network of H-bonding (N-H...Cl, CH...Cl, CH...N) causes the 3D self assembling of the units. Upon addition of base, the HCl release from 1a is observed with the transfer to Nb of the O-atom of the carbonylic function of the starting urea which is converted into the relevant carbodiimide CyN=C=NCy 4. The latter is quantitatively released by adding an excess of NEt(3) at 308 K (py and DBU are less efficient) with formation of the known NbOCl(3)(NEt(3))(2), isolated in quantitative yield. Increasing the temperature leads to a loss in selectivity as the formed DCC undergoes further reactions. At 350 K, the isocyanate CyN=C=O has been isolated in 60% yield besides a mixture of Nb-complexes. DFT calculations have been coupled to IR and NMR experiments for characterizing possible reaction intermediates and the behaviour of 1a. Several other MCl(x) species (ScCl(3), YCl(3), LaCl(3), TiCl(4), TaCl(5), AlCl(3), SnCl(4)) have been shown to be able to co-ordinate DCU but not all of them promote the conversion of urea into DCC.

Correcting electron-density resolution bias in reciprocal space.

Fourier syntheses are always affected by series-termination errors, which generate sets of positive and negative ripples around each main peak in the map. The interaction among the ripples distorts the profile of the map and moves peaks away from their correct positions. In a previous paper [Altomare et al. (2008). Acta Cryst. A64, 326-336] an algorithm was described which reduces the resolution bias by removing the effects of the ripples in direct space. In this paper the correction is performed in reciprocal space: the effect of the ripples on the atomic scattering factors is calculated and subtracted from the usual atomic scattering factors. The modified scattering factors are used to calculate new structure factors, from which more accurate electron-density maps may be obtained. The experimental tests show that the procedure minimizes the effects of the resolution bias and provides atomic positions that are more accurate than those provided by traditional approaches.